Data-driven reverse engineering of signaling pathways using ensembles of dynamic models.

PubMed

Henriques, David; Villaverde, Alejandro F; Rocha, Miguel; Saez-Rodriguez, Julio; Banga, Julio R

2017-02-01

Despite significant efforts and remarkable progress, the inference of signaling networks from experimental data remains very challenging. The problem is particularly difficult when the objective is to obtain a dynamic model capable of predicting the effect of novel perturbations not considered during model training. The problem is ill-posed due to the nonlinear nature of these systems, the fact that only a fraction of the involved proteins and their post-translational modifications can be measured, and limitations on the technologies used for growing cells in vitro, perturbing them, and measuring their variations. As a consequence, there is a pervasive lack of identifiability. To overcome these issues, we present a methodology called SELDOM (enSEmbLe of Dynamic lOgic-based Models), which builds an ensemble of logic-based dynamic models, trains them to experimental data, and combines their individual simulations into an ensemble prediction. It also includes a model reduction step to prune spurious interactions and mitigate overfitting. SELDOM is a data-driven method, in the sense that it does not require any prior knowledge of the system: the interaction networks that act as scaffolds for the dynamic models are inferred from data using mutual information. We have tested SELDOM on a number of experimental and in silico signal transduction case-studies, including the recent HPN-DREAM breast cancer challenge. We found that its performance is highly competitive compared to state-of-the-art methods for the purpose of recovering network topology. More importantly, the utility of SELDOM goes beyond basic network inference (i.e. uncovering static interaction networks): it builds dynamic (based on ordinary differential equation) models, which can be used for mechanistic interpretations and reliable dynamic predictions in new experimental conditions (i.e. not used in the training). For this task, SELDOM's ensemble prediction is not only consistently better than predictions from individual models, but also often outperforms the state of the art represented by the methods used in the HPN-DREAM challenge.

Data-driven reverse engineering of signaling pathways using ensembles of dynamic models

PubMed Central

Henriques, David; Villaverde, Alejandro F.; Banga, Julio R.

2017-01-01

Despite significant efforts and remarkable progress, the inference of signaling networks from experimental data remains very challenging. The problem is particularly difficult when the objective is to obtain a dynamic model capable of predicting the effect of novel perturbations not considered during model training. The problem is ill-posed due to the nonlinear nature of these systems, the fact that only a fraction of the involved proteins and their post-translational modifications can be measured, and limitations on the technologies used for growing cells in vitro, perturbing them, and measuring their variations. As a consequence, there is a pervasive lack of identifiability. To overcome these issues, we present a methodology called SELDOM (enSEmbLe of Dynamic lOgic-based Models), which builds an ensemble of logic-based dynamic models, trains them to experimental data, and combines their individual simulations into an ensemble prediction. It also includes a model reduction step to prune spurious interactions and mitigate overfitting. SELDOM is a data-driven method, in the sense that it does not require any prior knowledge of the system: the interaction networks that act as scaffolds for the dynamic models are inferred from data using mutual information. We have tested SELDOM on a number of experimental and in silico signal transduction case-studies, including the recent HPN-DREAM breast cancer challenge. We found that its performance is highly competitive compared to state-of-the-art methods for the purpose of recovering network topology. More importantly, the utility of SELDOM goes beyond basic network inference (i.e. uncovering static interaction networks): it builds dynamic (based on ordinary differential equation) models, which can be used for mechanistic interpretations and reliable dynamic predictions in new experimental conditions (i.e. not used in the training). For this task, SELDOM’s ensemble prediction is not only consistently better than predictions from individual models, but also often outperforms the state of the art represented by the methods used in the HPN-DREAM challenge. PMID:28166222

Numerical Modelling of Femur Fracture and Experimental Validation Using Bone Simulant.

PubMed

Marco, Miguel; Giner, Eugenio; Larraínzar-Garijo, Ricardo; Caeiro, José Ramón; Miguélez, María Henar

2017-10-01

Bone fracture pattern prediction is still a challenge and an active field of research. The main goal of this article is to present a combined methodology (experimental and numerical) for femur fracture onset analysis. Experimental work includes the characterization of the mechanical properties and fracture testing on a bone simulant. The numerical work focuses on the development of a model whose material properties are provided by the characterization tests. The fracture location and the early stages of the crack propagation are modelled using the extended finite element method and the model is validated by fracture tests developed in the experimental work. It is shown that the accuracy of the numerical results strongly depends on a proper bone behaviour characterization.

Efficient Lane Boundary Detection with Spatial-Temporal Knowledge Filtering

PubMed Central

Nan, Zhixiong; Wei, Ping; Xu, Linhai; Zheng, Nanning

2016-01-01

Lane boundary detection technology has progressed rapidly over the past few decades. However, many challenges that often lead to lane detection unavailability remain to be solved. In this paper, we propose a spatial-temporal knowledge filtering model to detect lane boundaries in videos. To address the challenges of structure variation, large noise and complex illumination, this model incorporates prior spatial-temporal knowledge with lane appearance features to jointly identify lane boundaries. The model first extracts line segments in video frames. Two novel filters—the Crossing Point Filter (CPF) and the Structure Triangle Filter (STF)—are proposed to filter out the noisy line segments. The two filters introduce spatial structure constraints and temporal location constraints into lane detection, which represent the spatial-temporal knowledge about lanes. A straight line or curve model determined by a state machine is used to fit the line segments to finally output the lane boundaries. We collected a challenging realistic traffic scene dataset. The experimental results on this dataset and other standard dataset demonstrate the strength of our method. The proposed method has been successfully applied to our autonomous experimental vehicle. PMID:27529248

A Robust Adaptive Autonomous Approach to Optimal Experimental Design

NASA Astrophysics Data System (ADS)

Gu, Hairong

Experimentation is the fundamental tool of scientific inquiries to understand the laws governing the nature and human behaviors. Many complex real-world experimental scenarios, particularly in quest of prediction accuracy, often encounter difficulties to conduct experiments using an existing experimental procedure for the following two reasons. First, the existing experimental procedures require a parametric model to serve as the proxy of the latent data structure or data-generating mechanism at the beginning of an experiment. However, for those experimental scenarios of concern, a sound model is often unavailable before an experiment. Second, those experimental scenarios usually contain a large number of design variables, which potentially leads to a lengthy and costly data collection cycle. Incompetently, the existing experimental procedures are unable to optimize large-scale experiments so as to minimize the experimental length and cost. Facing the two challenges in those experimental scenarios, the aim of the present study is to develop a new experimental procedure that allows an experiment to be conducted without the assumption of a parametric model while still achieving satisfactory prediction, and performs optimization of experimental designs to improve the efficiency of an experiment. The new experimental procedure developed in the present study is named robust adaptive autonomous system (RAAS). RAAS is a procedure for sequential experiments composed of multiple experimental trials, which performs function estimation, variable selection, reverse prediction and design optimization on each trial. Directly addressing the challenges in those experimental scenarios of concern, function estimation and variable selection are performed by data-driven modeling methods to generate a predictive model from data collected during the course of an experiment, thus exempting the requirement of a parametric model at the beginning of an experiment; design optimization is performed to select experimental designs on the fly of an experiment based on their usefulness so that fewest designs are needed to reach useful inferential conclusions. Technically, function estimation is realized by Bayesian P-splines, variable selection is realized by Bayesian spike-and-slab prior, reverse prediction is realized by grid-search and design optimization is realized by the concepts of active learning. The present study demonstrated that RAAS achieves statistical robustness by making accurate predictions without the assumption of a parametric model serving as the proxy of latent data structure while the existing procedures can draw poor statistical inferences if a misspecified model is assumed; RAAS also achieves inferential efficiency by taking fewer designs to acquire useful statistical inferences than non-optimal procedures. Thus, RAAS is expected to be a principled solution to real-world experimental scenarios pursuing robust prediction and efficient experimentation.

Mathematical modelling of clostridial acetone-butanol-ethanol fermentation.

PubMed

Millat, Thomas; Winzer, Klaus

2017-03-01

Clostridial acetone-butanol-ethanol (ABE) fermentation features a remarkable shift in the cellular metabolic activity from acid formation, acidogenesis, to the production of industrial-relevant solvents, solventogensis. In recent decades, mathematical models have been employed to elucidate the complex interlinked regulation and conditions that determine these two distinct metabolic states and govern the transition between them. In this review, we discuss these models with a focus on the mechanisms controlling intra- and extracellular changes between acidogenesis and solventogenesis. In particular, we critically evaluate underlying model assumptions and predictions in the light of current experimental knowledge. Towards this end, we briefly introduce key ideas and assumptions applied in the discussed modelling approaches, but waive a comprehensive mathematical presentation. We distinguish between structural and dynamical models, which will be discussed in their chronological order to illustrate how new biological information facilitates the 'evolution' of mathematical models. Mathematical models and their analysis have significantly contributed to our knowledge of ABE fermentation and the underlying regulatory network which spans all levels of biological organization. However, the ties between the different levels of cellular regulation are not well understood. Furthermore, contradictory experimental and theoretical results challenge our current notion of ABE metabolic network structure. Thus, clostridial ABE fermentation still poses theoretical as well as experimental challenges which are best approached in close collaboration between modellers and experimentalists.

A Tutorial on Adaptive Design Optimization

PubMed Central

Myung, Jay I.; Cavagnaro, Daniel R.; Pitt, Mark A.

2013-01-01

Experimentation is ubiquitous in the field of psychology and fundamental to the advancement of its science, and one of the biggest challenges for researchers is designing experiments that can conclusively discriminate the theoretical hypotheses or models under investigation. The recognition of this challenge has led to the development of sophisticated statistical methods that aid in the design of experiments and that are within the reach of everyday experimental scientists. This tutorial paper introduces the reader to an implementable experimentation methodology, dubbed Adaptive Design Optimization, that can help scientists to conduct “smart” experiments that are maximally informative and highly efficient, which in turn should accelerate scientific discovery in psychology and beyond. PMID:23997275

Evaluation of novel oral vaccine candidates and validation of a caprine model of Johne's disease

PubMed Central

Hines, Murray E.; Turnquist, Sue E.; Ilha, Marcia R. S.; Rajeev, Sreekumari; Jones, Arthur L.; Whittington, Lisa; Bannantine, John P.; Barletta, Raúl G.; Gröhn, Yrjö T.; Katani, Robab; Talaat, Adel M.; Li, Lingling; Kapur, Vivek

2014-01-01

Johne's disease (JD) caused by Mycobacterium avium subspecies paratuberculosis (MAP) is a major threat to the dairy industry and possibly some cases of Crohn's disease in humans. A MAP vaccine that reduced of clinical disease and/or reduced fecal shedding would aid in the control of JD. The objectives of this study were (1) to evaluate the efficacy of 5 attenuated strains of MAP as vaccine candidates compared to a commercial control vaccine using the protocol proposed by the Johne's Disease Integrated Program (JDIP) Animal Model Standardization Committee (AMSC), and (2) to validate the AMSC Johne's disease goat challenge model. Eighty goat kids were vaccinated orally twice at 8 and 10 weeks of age with an experimental vaccine or once subcutaneously at 8 weeks with Silirum® (Zoetis), or a sham control oral vaccine at 8 and 10 weeks. Kids were challenged orally with a total of approximately 1.44 × 109 CFU divided in two consecutive daily doses using MAP ATCC-700535 (K10-like bovine isolate). All kids were necropsied at 13 months post-challenge. Results indicated that the AMSC goat challenge model is a highly efficient and valid model for JD challenge studies. None of the experimental or control vaccines evaluated prevented MAP infection or eliminated fecal shedding, although the 329 vaccine lowered the incidence of infection, fecal shedding, tissue colonization and reduced lesion scores, but less than the control vaccine. Based on our results the relative performance ranking of the experimental live-attenuated vaccines evaluated, the 329 vaccine was the best performer, followed by the 318 vaccine, then 316 vaccine, 315 vaccine and finally the 319 vaccine was the worst performer. The subcutaneously injected control vaccine outperformed the orally-delivered mutant vaccine candidates. Two vaccines (329 and 318) do reduce presence of JD gross and microscopic lesions, slow progression of disease, and one vaccine (329) reduced fecal shedding and tissue colonization. PMID:24624365

Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models.

PubMed

Karr, Jonathan R; Williams, Alex H; Zucker, Jeremy D; Raue, Andreas; Steiert, Bernhard; Timmer, Jens; Kreutz, Clemens; Wilkinson, Simon; Allgood, Brandon A; Bot, Brian M; Hoff, Bruce R; Kellen, Michael R; Covert, Markus W; Stolovitzky, Gustavo A; Meyer, Pablo

2015-05-01

Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM) 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model's structure and in silico "experimental" data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation.

Report of a consultation on the optimization of clinical challenge trials for evaluation of candidate blood stage malaria vaccines, 18-19 March 2009, Bethesda, MD, USA.

PubMed

Moorthy, V S; Diggs, C; Ferro, S; Good, M F; Herrera, S; Hill, A V; Imoukhuede, E B; Kumar, S; Loucq, C; Marsh, K; Ockenhouse, C F; Richie, T L; Sauerwein, R W

2009-09-25

Development and optimization of first generation malaria vaccine candidates has been facilitated by the existence of a well-established Plasmodium falciparum clinical challenge model in which infectious sporozoites are administered to human subjects via mosquito bite. While ideal for testing pre-erythrocytic stage vaccines, some researchers believe that the sporozoite challenge model is less appropriate for testing blood stage vaccines. Here we report a consultation, co-sponsored by PATH MVI, USAID, EMVI and WHO, where scientists from all institutions globally that have conducted such clinical challenges in recent years and representatives from regulatory agencies and funding agencies met to discuss clinical malaria challenge models. Participants discussed strengthening and harmonizing the sporozoite challenge model and considered the pros and cons of further developing a blood stage challenge possibly better suited for evaluating the efficacy of blood stage vaccines. This report summarizes major findings and recommendations, including an update on the Plasmodium vivax clinical challenge model, the prospects for performing experimental challenge trials in malaria endemic countries and an update on clinical safety data. While the focus of the meeting was on the optimization of clinical challenge models for evaluation of blood stage candidate malaria vaccines, many of the considerations are relevant for the application of challenge trials to other purposes.

Development, Testing, and Validation of a Model-Based Tool to Predict Operator Responses in Unexpected Workload Transitions

NASA Technical Reports Server (NTRS)

Sebok, Angelia; Wickens, Christopher; Sargent, Robert

2015-01-01

One human factors challenge is predicting operator performance in novel situations. Approaches such as drawing on relevant previous experience, and developing computational models to predict operator performance in complex situations, offer potential methods to address this challenge. A few concerns with modeling operator performance are that models need to realistic, and they need to be tested empirically and validated. In addition, many existing human performance modeling tools are complex and require that an analyst gain significant experience to be able to develop models for meaningful data collection. This paper describes an effort to address these challenges by developing an easy to use model-based tool, using models that were developed from a review of existing human performance literature and targeted experimental studies, and performing an empirical validation of key model predictions.

Challenging Density Functional Theory Calculations with Hemes and Porphyrins.

PubMed

de Visser, Sam P; Stillman, Martin J

2016-04-07

In this paper we review recent advances in computational chemistry and specifically focus on the chemical description of heme proteins and synthetic porphyrins that act as both mimics of natural processes and technological uses. These are challenging biochemical systems involved in electron transfer as well as biocatalysis processes. In recent years computational tools have improved considerably and now can reproduce experimental spectroscopic and reactivity studies within a reasonable error margin (several kcal·mol(-1)). This paper gives recent examples from our groups, where we investigated heme and synthetic metal-porphyrin systems. The four case studies highlight how computational modelling can correctly reproduce experimental product distributions, predicted reactivity trends and guide interpretation of electronic structures of complex systems. The case studies focus on the calculations of a variety of spectroscopic features of porphyrins and show how computational modelling gives important insight that explains the experimental spectra and can lead to the design of porphyrins with tuned properties.

The mathematics of cancer: integrating quantitative models.

PubMed

Altrock, Philipp M; Liu, Lin L; Michor, Franziska

2015-12-01

Mathematical modelling approaches have become increasingly abundant in cancer research. The complexity of cancer is well suited to quantitative approaches as it provides challenges and opportunities for new developments. In turn, mathematical modelling contributes to cancer research by helping to elucidate mechanisms and by providing quantitative predictions that can be validated. The recent expansion of quantitative models addresses many questions regarding tumour initiation, progression and metastases as well as intra-tumour heterogeneity, treatment responses and resistance. Mathematical models can complement experimental and clinical studies, but also challenge current paradigms, redefine our understanding of mechanisms driving tumorigenesis and shape future research in cancer biology.

A Novel Laboratory Activity for Teaching about the Evolution of Multicellularity

ERIC Educational Resources Information Center

Ratcliff, William C.; Raney, Allison; Westreich, Sam; Cotner, Sehoya

2014-01-01

The evolution of complexity remains one of the most challenging topics in biology to teach effectively. We present a novel laboratory activity, modeled on a recent experimental breakthrough, in which students experimentally evolve simple multicellularity using single-celled yeast ("Saccharomyces cerevisiae"). By simply selecting for…

Improving the physiological realism of experimental models.

PubMed

Vinnakota, Kalyan C; Cha, Chae Y; Rorsman, Patrik; Balaban, Robert S; La Gerche, Andre; Wade-Martins, Richard; Beard, Daniel A; Jeneson, Jeroen A L

2016-04-06

The Virtual Physiological Human (VPH) project aims to develop integrative, explanatory and predictive computational models (C-Models) as numerical investigational tools to study disease, identify and design effective therapies and provide an in silico platform for drug screening. Ultimately, these models rely on the analysis and integration of experimental data. As such, the success of VPH depends on the availability of physiologically realistic experimental models (E-Models) of human organ function that can be parametrized to test the numerical models. Here, the current state of suitable E-models, ranging from in vitro non-human cell organelles to in vivo human organ systems, is discussed. Specifically, challenges and recent progress in improving the physiological realism of E-models that may benefit the VPH project are highlighted and discussed using examples from the field of research on cardiovascular disease, musculoskeletal disorders, diabetes and Parkinson's disease.

South Oxnard Challenge Project: Report of What Works.

ERIC Educational Resources Information Center

Lane, Jodi; Schroeder, Amber; Turner, Susan; Fain, Terry

RAND Criminal Justice conducted a randomized experimental evaluation of the South Oxnard Challenge Project (SOCP), a collaborative project between county, city and private non-profit agencies based on the "Corrections of Place" (COP) model. The project targets youth who live in South Oxnard or Port Hueneme, are between 12 and 18 years old, have a…

Comparative experimental subcutaneous glanders and melioidosis in the common marmoset (Callithrix jacchus).

PubMed

Nelson, Michelle; Salguero, Francisco J; Dean, Rachel E; Ngugi, Sarah A; Smither, Sophie J; Atkins, Timothy P; Lever, Mark S

2014-12-01

Glanders and melioidosis are caused by two distinct Burkholderia species and have generally been considered to have similar disease progression. While both of these pathogens are HHS/CDC Tier 1 agents, natural infection with both these pathogens is primarily through skin inoculation. The common marmoset (Callithrix jacchus) was used to compare disease following experimental subcutaneous challenge. Acute, lethal disease was observed in marmosets following challenge with between 26 and 1.2 × 10(8) cfu Burkholderia pseudomallei within 22-85 h. The reproducibility and progression of the disease were assessed following a challenge of 1 × 10(2) cfu of B. pseudomallei. Melioidosis was characterised by high levels of bacteraemia, focal microgranuloma progressing to non-necrotic multifocal solid lesions in the livers and spleens and multi-organ failure. Lethal disease was observed in 93% of animals challenged with Burkholderia mallei, occurring between 5 and 10.6 days. Following challenge with 1 × 10(2) cfu of B. mallei, glanders was characterised with lymphatic spread of the bacteria and non-necrotic, multifocal solid lesions progressing to a multifocal lesion with severe necrosis and pneumonia. The experimental results confirmed that the disease pathology and presentation is strikingly different between the two pathogens. The marmoset provides a model of the human syndrome for both diseases facilitating the development of medical countermeasures. © 2014 Crown copyright. International Journal of Experimental Pathology © 2014 Company of the International Journal of Experimental Pathology (CIJEP).

Field validation of experimental challenge models for IPN vaccines.

PubMed

Ramstad, A; Romstad, A B; Knappskog, D H; Midtlyng, P J

2007-12-01

Atlantic salmon S1/2 pre-smolts from the VESO Vikan hatchery were assigned to study groups, i.p. immunized with commercially available, multivalent oil-adjuvanted vaccines with (Norvax Compact 6 - NC-6) or without (Norvax Compact 4 - NC-4) recombinant infectious pancreatic necrosis virus (IPNV) antigen. A control group received saline solution. When ready for sea, the fish were transported to the VESO Vikan experimental laboratory, where two identical tanks were stocked with 75 fish per group before being transferred to 10 degrees C sea water and exposed by bath to first passage IPNV grown in CHSE-214 cells. The third tank containing 40 fish from each group was challenged by the introduction of 116 fish that had received an i.p injection of IPNV-challenge material. The remaining vaccinated fish were transported to the VESO Vikan marine field trial site and placed in two identical pens, each containing approximately 53 000 fish from the NC-6 group and 9000 fish from the NC-4 group. In the experimental bath challenge trial, the cumulative mortality was 75% and 78% in the control groups, and the relative percentage survival (RPS) of the NC-6-immunized fish vs. the reference vaccine groups was 60% and 82%, respectively. In the cohabitation challenge, the control mortality reached 74% and the IPNV-specific vaccine RPS was 72%. In both models, the reference vaccine lacking IPNV antigen gave a moderate but statistically significant non-specific protection. In the field, a natural outbreak of infectious pancreatic necrosis (IPN) occurred after 7 weeks lasting for approximately 3.5 months before problems due to winter ulcers became dominating. During this outbreak, mortality in the NC-4 groups were 33.5% and 31.6%, respectively, whereas mortality in the NC-6 groups were 6.9% and 5.3%, respectively, amounting to 81% IPNV-specific protection. In conclusion, the IPN protection estimates obtained by experimental challenges were consistent between tanks, and were confirmed by the field results.

Undergraduate Teaching of Ideal and Real Fluid Flows: The Value of Real-World Experimental Projects

ERIC Educational Resources Information Center

Baldock, Tom E.; Chanson, Hubert

2006-01-01

This paper describes the pedagogical impact of real-world experimental projects undertaken as part of an advanced undergraduate fluid mechanics subject at an Australian university. The projects have been organized to complement traditional lectures and introduce students to the challenges of professional design, physical modelling, data collection…

DNFB-DNS hapten-induced colitis in mice should not be considered a model of inflammatory bowel disease.

PubMed

Bailón, Elvira; Cueto-Sola, Margarita; Utrilla, Pilar; Nieto, Ana; Garrido-Mesa, Natividad; Celada, Antonio; Zarzuelo, Antonio; Xaus, Jordi; Gálvez, Julio; Comalada, Mònica

2011-10-01

The dinitrofluorobenzene/dinitrosulfonic acid (DNFB/DNS) model was originally described as an experimental model of intestinal inflammation resembling human ulcerative colitis (UC). Due to the absence of acceptable UC experimental models for pharmacological preclinical assays, here we examine the immune response induced in this model. Balb/c mice were sensitized by skin application of DNFB on day 1, followed by an intrarectal challenge with DNS on day 5. We further expanded this model by administering a second DNS challenge on day 15. The features of colonic inflammation and immune response were evaluated. The changes observed in colonic tissue corresponded, in comparison to the trinitrobenzene sulfonic acid (TNBS) colitis model, to a mild mucosal effect in the colon, which spontaneously resolved in less than 5 days. Furthermore, the second hapten challenge did not exacerbate the inflammatory response. In contrast to other studies, we did not observe any clear involvement of tumor necrosis factor alpha (TNF-α) or other Th1 cytokines during the initial inflammatory response; however, we found that a more Th2-humoral response appeared to mediate the first contact with the hapten. An increased humoral response was detected during the second challenge, although an increased Th1/Th17-cytokine expression profile was also simultaneously observed. On the basis of these results, although the DNFB/DNS model can display some features found in human UC, it should be considered as a model for the study of the intestinal hypersensitivity seen, for example, during food allergy or irritable bowel syndrome but not intestinal inflammation per se. Copyright © 2010 Crohn's & Colitis Foundation of America, Inc.

Neutronics Conversion Analyses of the Laue-Langevin Institute (ILL) High Flux Reactor (RHF)

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

Bergeron, A.; Dionne, B.; Calzavara, Y.

2014-09-30

The following report describes the neutronics results obtained with the MCNP model of the RHF U7Mo LEU reference design that has been established in 2010 during the feasibility analysis. This work constitutes a complete and detailed neutronics analysis of that LEU design using models that have been significantly improved since 2010 and the release of the feasibility report. When possible, the credibility of the neutronics model is tested by comparing the HEU model results with experimental data or other codes calculations results. The results obtained with the LEU model are systematically compared to the HEU model. The changes applied tomore » the neutronics model lead to better comparisons with experimental data or improved the calculation efficiency but do not challenge the conclusion of the feasibility analysis. If the U7Mo fuel is commercially available, not cost prohibitive, a back-end solution is established and if it is possible to manufacture the proposed element, neutronics analyses show that the performance of the reactor would not be challenged by the conversion to LEU fuel.« less

Evaluation of Full Reynolds Stress Turbulence Models in FUN3D

NASA Technical Reports Server (NTRS)

Dudek, Julianne C.; Carlson, Jan-Renee

2017-01-01

Full seven-equation Reynolds stress turbulence models are a relatively new and promising tool for todays aerospace technology challenges. This paper uses two stress-omega full Reynolds stress models to evaluate challenging flows including shock-wave boundary layer interactions, separation and mixing layers. The Wilcox and the SSGLRR full second-moment Reynolds stress models are evaluated for four problems: a transonic two-dimensional diffuser, a supersonic axisymmetric compression corner, a compressible planar shear layer, and a subsonic axisymmetric jet. Simulation results are compared with experimental data and results using the more commonly used Spalart-Allmaras (SA) one-equation and the Menter Shear Stress Transport (SST) two-equation models.

MaRIE: A facility for time-dependent materials science at the mesoscale

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

Barnes, Cris William; Kippen, Karen Elizabeth

To meet new and emerging national security issues the Laboratory is stepping up to meet another grand challenge—transitioning from observing to controlling a material’s performance. This challenge requires the best of experiment, modeling, simulation, and computational tools. MaRIE is the Laboratory’s proposed flagship experimental facility intended to meet the challenge.

Improving the physiological realism of experimental models

PubMed Central

Vinnakota, Kalyan C.; Cha, Chae Y.; Rorsman, Patrik; Balaban, Robert S.; La Gerche, Andre; Wade-Martins, Richard; Beard, Daniel A.

2016-01-01

The Virtual Physiological Human (VPH) project aims to develop integrative, explanatory and predictive computational models (C-Models) as numerical investigational tools to study disease, identify and design effective therapies and provide an in silico platform for drug screening. Ultimately, these models rely on the analysis and integration of experimental data. As such, the success of VPH depends on the availability of physiologically realistic experimental models (E-Models) of human organ function that can be parametrized to test the numerical models. Here, the current state of suitable E-models, ranging from in vitro non-human cell organelles to in vivo human organ systems, is discussed. Specifically, challenges and recent progress in improving the physiological realism of E-models that may benefit the VPH project are highlighted and discussed using examples from the field of research on cardiovascular disease, musculoskeletal disorders, diabetes and Parkinson's disease. PMID:27051507

Passive Immunization with a Polyclonal Antiserum to the Hemoglobin Receptor of Haemophilus ducreyi Confers Protection against a Homologous Challenge in the Experimental Swine Model of Chancroid▿

PubMed Central

Leduc, Isabelle; Fusco, William G.; Choudhary, Neelima; Routh, Patty A.; Cholon, Deborah M.; Hobbs, Marcia M.; Almond, Glen W.; Orndorff, Paul E.; Elkins, Christopher

2011-01-01

Haemophilus ducreyi, the etiologic agent of chancroid, has an obligate requirement for heme. Heme is acquired by H. ducreyi from its human host via TonB-dependent transporters expressed at its bacterial surface. Of 3 TonB-dependent transporters encoded in the genome of H. ducreyi, only the hemoglobin receptor, HgbA, is required to establish infection during the early stages of the experimental human model of chancroid. Active immunization with a native preparation of HgbA (nHgbA) confers complete protection in the experimental swine model of chancroid, using either Freund's or monophosphoryl lipid A as adjuvants. To determine if transfer of anti-nHgbA serum is sufficient to confer protection, a passive immunization experiment using pooled nHgbA antiserum was conducted in the experimental swine model of chancroid. Pigs receiving this pooled nHgbA antiserum were protected from a homologous, but not a heterologous, challenge. Passively transferred polyclonal antibodies elicited to nHgbA bound the surface of H. ducreyi and partially blocked hemoglobin binding by nHgbA, but were not bactericidal. Taken together, these data suggest that the humoral immune response to the HgbA vaccine is protective against an H. ducreyi infection, possibly by preventing acquisition of the essential nutrient heme. PMID:21646451

Passive immunization with a polyclonal antiserum to the hemoglobin receptor of Haemophilus ducreyi confers protection against a homologous challenge in the experimental swine model of chancroid.

PubMed

Leduc, Isabelle; Fusco, William G; Choudhary, Neelima; Routh, Patty A; Cholon, Deborah M; Hobbs, Marcia M; Almond, Glen W; Orndorff, Paul E; Elkins, Christopher

2011-08-01

Haemophilus ducreyi, the etiologic agent of chancroid, has an obligate requirement for heme. Heme is acquired by H. ducreyi from its human host via TonB-dependent transporters expressed at its bacterial surface. Of 3 TonB-dependent transporters encoded in the genome of H. ducreyi, only the hemoglobin receptor, HgbA, is required to establish infection during the early stages of the experimental human model of chancroid. Active immunization with a native preparation of HgbA (nHgbA) confers complete protection in the experimental swine model of chancroid, using either Freund's or monophosphoryl lipid A as adjuvants. To determine if transfer of anti-nHgbA serum is sufficient to confer protection, a passive immunization experiment using pooled nHgbA antiserum was conducted in the experimental swine model of chancroid. Pigs receiving this pooled nHgbA antiserum were protected from a homologous, but not a heterologous, challenge. Passively transferred polyclonal antibodies elicited to nHgbA bound the surface of H. ducreyi and partially blocked hemoglobin binding by nHgbA, but were not bactericidal. Taken together, these data suggest that the humoral immune response to the HgbA vaccine is protective against an H. ducreyi infection, possibly by preventing acquisition of the essential nutrient heme.

Irradiation Design for an Experimental Murine Model

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

Ballesteros-Zebadua, P.; Moreno-Jimenez, S.; Suarez-Campos, J. E.

2010-12-07

In radiotherapy and stereotactic radiosurgery, small animal experimental models are frequently used, since there are still a lot of unsolved questions about the biological and biochemical effects of ionizing radiation. This work presents a method for small-animal brain radiotherapy compatible with a dedicated 6MV Linac. This rodent model is focused on the research of the inflammatory effects produced by ionizing radiation in the brain. In this work comparisons between Pencil Beam and Monte Carlo techniques, were used in order to evaluate accuracy of the calculated dose using a commercial planning system. Challenges in this murine model are discussed.

Protein loop modeling using a new hybrid energy function and its application to modeling in inaccurate structural environments.

PubMed

Park, Hahnbeom; Lee, Gyu Rie; Heo, Lim; Seok, Chaok

2014-01-01

Protein loop modeling is a tool for predicting protein local structures of particular interest, providing opportunities for applications involving protein structure prediction and de novo protein design. Until recently, the majority of loop modeling methods have been developed and tested by reconstructing loops in frameworks of experimentally resolved structures. In many practical applications, however, the protein loops to be modeled are located in inaccurate structural environments. These include loops in model structures, low-resolution experimental structures, or experimental structures of different functional forms. Accordingly, discrepancies in the accuracy of the structural environment assumed in development of the method and that in practical applications present additional challenges to modern loop modeling methods. This study demonstrates a new strategy for employing a hybrid energy function combining physics-based and knowledge-based components to help tackle this challenge. The hybrid energy function is designed to combine the strengths of each energy component, simultaneously maintaining accurate loop structure prediction in a high-resolution framework structure and tolerating minor environmental errors in low-resolution structures. A loop modeling method based on global optimization of this new energy function is tested on loop targets situated in different levels of environmental errors, ranging from experimental structures to structures perturbed in backbone as well as side chains and template-based model structures. The new method performs comparably to force field-based approaches in loop reconstruction in crystal structures and better in loop prediction in inaccurate framework structures. This result suggests that higher-accuracy predictions would be possible for a broader range of applications. The web server for this method is available at http://galaxy.seoklab.org/loop with the PS2 option for the scoring function.

Challenging Density Functional Theory Calculations with Hemes and Porphyrins

PubMed Central

de Visser, Sam P.; Stillman, Martin J.

2016-01-01

In this paper we review recent advances in computational chemistry and specifically focus on the chemical description of heme proteins and synthetic porphyrins that act as both mimics of natural processes and technological uses. These are challenging biochemical systems involved in electron transfer as well as biocatalysis processes. In recent years computational tools have improved considerably and now can reproduce experimental spectroscopic and reactivity studies within a reasonable error margin (several kcal·mol−1). This paper gives recent examples from our groups, where we investigated heme and synthetic metal-porphyrin systems. The four case studies highlight how computational modelling can correctly reproduce experimental product distributions, predicted reactivity trends and guide interpretation of electronic structures of complex systems. The case studies focus on the calculations of a variety of spectroscopic features of porphyrins and show how computational modelling gives important insight that explains the experimental spectra and can lead to the design of porphyrins with tuned properties. PMID:27070578

Self-regulation of common age-related challenges: benefits for older adults' psychological and physical health.

PubMed

Wrosch, Carsten; Dunne, Erin; Scheier, Michael F; Schulz, Richard

2006-06-01

This article addresses the role played by adaptive self-regulation in protecting older adults' psychological and physical health. A theoretical model is outlined illustrating how common age-related challenges (i.e., physical challenges and life regrets) can influence older adults' health. In addition, the proposed model suggests that older adults can avoid the adverse health effects of encountering these problems if they engage in adaptive self-regulation. Finally, this article reviews recent studies that examined the adaptive value of self-regulation processes for managing physical challenges and life regrets in the elderly. The findings from cross-sectional, longitudinal, and experimental studies document the importance of adaptive self-regulation for maintaining older adults' health.

A Tool for Investigating Asthma and COPD Exacerbations: A Newly Manufactured and Well Characterised GMP Wild-Type Human Rhinovirus for Use in the Human Viral Challenge Model

PubMed Central

Fullen, Daniel J.; Murray, Bryan; Mori, Julie; Catchpole, Andrew; Borley, Daryl W.; Murray, Edward J.; Balaratnam, Ganesh; Gilbert, Anthony; Mann, Alex; Hughes, Fiona; Lambkin-Williams, Rob

2016-01-01

Background Human Rhinovirus infection is an important precursor to asthma and chronic obstructive pulmonary disease exacerbations and the Human Viral Challenge model may provide a powerful tool in studying these and other chronic respiratory diseases. In this study we have reported the production and human characterisation of a new Wild-Type HRV-16 challenge virus produced specifically for this purpose. Methods and Stock Development A HRV-16 isolate from an 18 year old experimentally infected healthy female volunteer (University of Virginia Children’s Hospital, USA) was obtained with appropriate medical history and consent. We manufactured a new HRV-16 stock by minimal passage in a WI-38 cell line under Good Manufacturing Practice conditions. Having first subjected the stock to rigorous adventitious agent testing and determining the virus suitability for human use, we conducted an initial safety and pathogenicity clinical study in adult volunteers in our dedicated clinical quarantine facility in London. Human Challenge and Conclusions In this study we have demonstrated the new Wild-Type HRV-16 Challenge Virus to be both safe and pathogenic, causing an appropriate level of disease in experimentally inoculated healthy adult volunteers. Furthermore, by inoculating volunteers with a range of different inoculum titres, we have established the minimum inoculum titre required to achieve reproducible disease. We have demonstrated that although inoculation titres as low as 1 TCID50 can produce relatively high infection rates, the optimal titre for progression with future HRV challenge model development with this virus stock was 10 TCID50. Studies currently underway are evaluating the use of this virus as a challenge agent in asthmatics. Trial Registration ClinicalTrials.gov NCT02522832 PMID:27936016

Laboratory-based Interpretation of Seismological Models: Dealing with Incomplete or Incompatible Experimental Data (Invited)

NASA Astrophysics Data System (ADS)

Jackson, I.; Kennett, B. L.; Faul, U. H.

2009-12-01

In parallel with cooperative developments in seismology during the past 25 years, there have been phenomenal advances in mineral/rock physics making laboratory-based interpretation of seismological models increasingly useful. However, the assimilation of diverse experimental data into a physically sound framework for seismological application is not without its challenges as demonstrated by two examples. In the first example, that of equation-of-state and elasticity data, an appropriate, thermodynamically consistent framework involves finite-strain expansion of the Helmholz free energy incorporating the Debye approximation to the lattice vibrational energy, as advocated by Stixrude and Lithgow-Bertelloni. Within this context, pressure, specific heat and entropy, thermal expansion, elastic constants and their adiabatic and isothermal pressure derivatives are all calculable without further approximation in an internally consistent manner. The opportunities and challenges of assimilating a wide range of sometimes marginally incompatible experimental data into a single model of this type will be demonstrated with reference to MgO, unquestionably the most thoroughly studied mantle mineral. A neighbourhood-algorithm inversion has identified a broadly satisfactory model, but uncertainties in key parameters associated particularly with pressure calibration remain sufficiently large as to preclude definitive conclusions concerning lower-mantle chemical composition and departures from adiabaticity. The second example is the much less complete dataset concerning seismic-wave dispersion and attenuation emerging from low-frequency forced-oscillation experiments. Significant progress has been made during the past decade towards an understanding of high-temperature, micro-strain viscoelastic relaxation in upper-mantle materials, especially as regards the roles of oscillation period, temperature, grain size and melt fraction. However, the influence of other potentially important variables such as dislocation density and the concentration of structurally bound water remain as targets for ongoing research. The state-of-the-art will be illustrated by highlighting the challenge in reconciling the substantial and growing amount of experimental data concerning grain-size sensitive relaxation in fine-grained olivine with micro-mechanical models of grain-boundary sliding.

The untapped potential of genetically-engineered mouse models in chemoprevention research: Opportunities and challenges

PubMed Central

Abate-Shen, Cory; Brown, Powel H.; Colburn, Nancy H.; Gerner, Eugene W.; Green, Jeffery E.; Lipkin, Martin; Nelson, William G.; Threadgill, David

2009-01-01

Summary The past decade has witnessed the unveiling of a powerful new generation of genetically-engineered mouse (GEM) models of human cancer, which are proving to be highly effective for elucidating cancer mechanisms and interrogating novel experimental therapeutics. This new generation of GEM models are well-suited for chemoprevention research, particularly for investigating progressive stages of carcinogenesis, identifying biomarkers for early detection and intervention, and pre-clinical assessment of novel agents or combinations of agents. Here we discuss opportunities and challenges for the application of GEM models in prevention research, as well as strategies to maximize their relevance for human cancer. PMID:19138951

Methodologies for Verification and Validation of Space Launch System (SLS) Structural Dynamic Models: Appendices

NASA Technical Reports Server (NTRS)

Coppolino, Robert N.

2018-01-01

Verification and validation (V&V) is a highly challenging undertaking for SLS structural dynamics models due to the magnitude and complexity of SLS subassemblies and subassemblies. Responses to challenges associated with V&V of Space Launch System (SLS) structural dynamics models are presented in Volume I of this paper. Four methodologies addressing specific requirements for V&V are discussed. (1) Residual Mode Augmentation (RMA). (2) Modified Guyan Reduction (MGR) and Harmonic Reduction (HR, introduced in 1976). (3) Mode Consolidation (MC). Finally, (4) Experimental Mode Verification (EMV). This document contains the appendices to Volume I.

Impact of High-Level Daptomycin Resistance in the Streptococcus mitis Group on Virulence and Survivability during Daptomycin Treatment in Experimental Infective Endocarditis

PubMed Central

Garcia-de-la-Maria, C.; Xiong, Y. Q.; Pericas, J. M.; Armero, Y.; Moreno, A.; Mishra, N. N.; Rybak, M. J.; Tran, T. T.; Arias, C. A.; Sullam, P. M.; Bayer, A. S.

2017-01-01

ABSTRACT Among the viridans group streptococci, the Streptococcus mitis group is the most common cause of infective endocarditis. These bacteria have a propensity to be β-lactam resistant, as well as to rapidly develop high-level and durable resistance to daptomycin (DAP). We compared a parental, daptomycin-susceptible (DAPs) S. mitis/S. oralis strain and its daptomycin-resistant (DAPr) variant in a model of experimental endocarditis in terms of (i) their relative fitness in multiple target organs in this model (vegetations, kidneys, spleen) when animals were challenged individually and in a coinfection strategy and (ii) their survivability during therapy with daptomycin-gentamicin (an in vitro combination synergistic against the parental strain). The DAPr variant was initially isolated from the cardiac vegetations of animals with experimental endocarditis caused by the parental DAPs strain following treatment with daptomycin. The parental strain and the DAPr variant were comparably virulent when animals were individually challenged. In contrast, in the coinfection model without daptomycin therapy, at both the 106- and 107-CFU/ml challenge inocula, the parental strain outcompeted the DAPr variant in all target organs, especially the kidneys and spleen. When the animals in the coinfection model of endocarditis were treated with DAP-gentamicin, the DAPs strain was completely eliminated, while the DAPr variant persisted in all target tissues. These data underscore that the acquisition of DAPr in S. mitis/S. oralis does come at an intrinsic fitness cost, although this resistance phenotype is completely protective against therapy with a potentially synergistic DAP regimen. PMID:28264848

Fulfilling the promise of the materials genome initiative with high-throughput experimental methodologies

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

Green, Martin L.; Choi, C. L.; Hattrick-Simpers, J. R.

The Materials Genome Initiative, a national effort to introduce new materials into the market faster and at lower cost, has made significant progress in computational simulation and modeling of materials. To build on this progress, a large amount of experimental data for validating these models, and informing more sophisticated ones, will be required. High-throughput experimentation generates large volumes of experimental data using combinatorial materials synthesis and rapid measurement techniques, making it an ideal experimental complement to bring the Materials Genome Initiative vision to fruition. This paper reviews the state-of-the-art results, opportunities, and challenges in high-throughput experimentation for materials design. Asmore » a result, a major conclusion is that an effort to deploy a federated network of high-throughput experimental (synthesis and characterization) tools, which are integrated with a modern materials data infrastructure, is needed.« less

Fulfilling the promise of the materials genome initiative with high-throughput experimental methodologies

DOE PAGES

Green, Martin L.; Choi, C. L.; Hattrick-Simpers, J. R.; ...

2017-03-28

The Materials Genome Initiative, a national effort to introduce new materials into the market faster and at lower cost, has made significant progress in computational simulation and modeling of materials. To build on this progress, a large amount of experimental data for validating these models, and informing more sophisticated ones, will be required. High-throughput experimentation generates large volumes of experimental data using combinatorial materials synthesis and rapid measurement techniques, making it an ideal experimental complement to bring the Materials Genome Initiative vision to fruition. This paper reviews the state-of-the-art results, opportunities, and challenges in high-throughput experimentation for materials design. Asmore » a result, a major conclusion is that an effort to deploy a federated network of high-throughput experimental (synthesis and characterization) tools, which are integrated with a modern materials data infrastructure, is needed.« less

Evaluating psychological interventions in a novel experimental human model of anxiety

PubMed Central

Ainsworth, Ben; Marshall, Jemma E.; Meron, Daniel; Baldwin, David S.; Chadwick, Paul; Munafò, Marcus R.; Garner, Matthew

2015-01-01

Inhalation of 7.5% carbon dioxide increases anxiety and autonomic arousal and provides a novel experimental model of anxiety with which to evaluate pharmacological and psychological treatments for anxiety. To date several psychotropic drugs including benzodiazepines, SSRIs and SNRIs have been evaluated using the 7.5% CO2 model; however, it has yet to be used to evaluate psychological interventions. We compared the effects of two core psychological components of mindfulness-meditation (open monitoring and focused attention) against general relaxation, on subjective, autonomic and neuropsychological outcomes in the 7.5% CO2 experimental model. 32 healthy screened adults were randomized to complete 10 min of guided open monitoring, focused attention or relaxation, immediately before inhaling 7.5% CO2 for 20 min. During CO2-challenge participants completed an eye-tracking measure of attention control and selective attention. Measures of subjective anxiety, blood pressure and heart rate were taken at baseline and immediately following intervention and CO2-challenge. OM and FA practice reduced subjective feelings of anxiety during 20-min inhalation of 7.5% CO2 compared to relaxation control. OM practice produced a strong anxiolytic effect, whereas the effect of FA was more modest. Anxiolytic OM and FA effects occurred in the absence of group differences in autonomic arousal and eye-movement measures of attention. Our findings are consistent with neuropsychological models of mindfulness-meditation that propose OM and FA activate prefrontal mechanisms that support emotion regulation during periods of anxiety and physiological hyper-arousal. Our findings complement those from pharmacological treatment studies, further supporting the use of CO2 challenge to evaluate future therapeutic interventions for anxiety. PMID:25765144

Animal models of post-ischemic forced use rehabilitation: methods, considerations, and limitations

PubMed Central

2013-01-01

Many survivors of stroke experience arm impairments, which can severely impact their quality of life. Forcing use of the impaired arm appears to improve functional recovery in post-stroke hemiplegic patients, however the mechanisms underlying improved recovery remain unclear. Animal models of post-stroke rehabilitation could prove critical to investigating such mechanisms, however modeling forced use in animals has proven challenging. Potential problems associated with reported experimental models include variability between stroke methods, rehabilitation paradigms, and reported outcome measures. Herein, we provide an overview of commonly used stroke models, including advantages and disadvantages of each with respect to studying rehabilitation. We then review various forced use rehabilitation paradigms, and highlight potential difficulties and translational problems. Lastly, we discuss the variety of functional outcome measures described by experimental researchers. To conclude, we outline ongoing challenges faced by researchers, and the importance of translational communication. Many stroke patients rely critically on rehabilitation of post-stroke impairments, and continued effort toward progression of rehabilitative techniques is warranted to ensure best possible treatment of the devastating effects of stroke. PMID:23343500

Measuring experimental cyclohexane-water distribution coefficients for the SAMPL5 challenge

NASA Astrophysics Data System (ADS)

Rustenburg, Ariën S.; Dancer, Justin; Lin, Baiwei; Feng, Jianwen A.; Ortwine, Daniel F.; Mobley, David L.; Chodera, John D.

2016-11-01

Small molecule distribution coefficients between immiscible nonaqueuous and aqueous phases—such as cyclohexane and water—measure the degree to which small molecules prefer one phase over another at a given pH. As distribution coefficients capture both thermodynamic effects (the free energy of transfer between phases) and chemical effects (protonation state and tautomer effects in aqueous solution), they provide an exacting test of the thermodynamic and chemical accuracy of physical models without the long correlation times inherent to the prediction of more complex properties of relevance to drug discovery, such as protein-ligand binding affinities. For the SAMPL5 challenge, we carried out a blind prediction exercise in which participants were tasked with the prediction of distribution coefficients to assess its potential as a new route for the evaluation and systematic improvement of predictive physical models. These measurements are typically performed for octanol-water, but we opted to utilize cyclohexane for the nonpolar phase. Cyclohexane was suggested to avoid issues with the high water content and persistent heterogeneous structure of water-saturated octanol phases, since it has greatly reduced water content and a homogeneous liquid structure. Using a modified shake-flask LC-MS/MS protocol, we collected cyclohexane/water distribution coefficients for a set of 53 druglike compounds at pH 7.4. These measurements were used as the basis for the SAMPL5 Distribution Coefficient Challenge, where 18 research groups predicted these measurements before the experimental values reported here were released. In this work, we describe the experimental protocol we utilized for measurement of cyclohexane-water distribution coefficients, report the measured data, propose a new bootstrap-based data analysis procedure to incorporate multiple sources of experimental error, and provide insights to help guide future iterations of this valuable exercise in predictive modeling.

Prevention of hepatocellular carcinoma: potential targets, experimental models, and clinical challenges

PubMed Central

Hoshida, Yujin; Fuchs, Bryan C.; Tanabe, Kenneth K.

2013-01-01

Chronic fibrotic liver diseases such as viral hepatitis eventually develop liver cirrhosis, which causes occurrence of hepatocellular carcinoma (HCC). Given the limited therapeutic efficacy in advanced HCC, prevention of HCC development could be an effective strategy for improving patient prognosis. However, there is still no established therapy to meet the goal. Studies have elucidated a wide variety of molecular mechanisms and signaling pathways involved in HCC development. Genetically-engineered or chemically-treated experimental models of cirrhosis and HCC have been developed and shown their potential value in investigating molecular therapeutic targets and diagnostic biomarkers for HCC prevention. In this review, we overview potential targets of prevention and currently available experimental models, and discuss strategies to translate the findings into clinical practice. PMID:22873223

Effects of low-level chronic irradiation on radiosensitivity of mammals: modeling and experimental studies

NASA Astrophysics Data System (ADS)

Smirnova, O. A.; Yonezawa, M.

Effects of low dose rate chronic irradiation on radiosensitivity of mammals mice are studied by experimental and modeling methods Own and reference experiments show that priming chronic low-level short-term and long-term exposures to radiation induce respectively elevated radiosensitivity and lowered radiosensitivity radioresistance in mice The manifestation of these radiosensitization and radioprotection effects are respectively increased and decreased mortality of preirradiated specimens after challenge acute irradiation in comparison with those for previously unexposed ones Taking into account that the reason of the animal death in the experiments was the hematopoietic syndrome the biophysical models of the critical body system hematopoiesis are used to simulate the dynamics of the major hematopoietic lines in mice exposed to challenge acute irradiation following the chronic one Juxtaposition of the modeling results obtained and the relevant experimental data shows that the radiosensitization effect of chronic low-level short-term less than 1 month preirradiation on mice is due to increased radiosensitivity of lymphopoietic granulocytopoietic and erythropoietic systems accompanied by increased or close to the normal level radiosensitivity of thrombocytopoietic system which are induced by the above-indicated exposure In turn the radioprotection effect of chronic low-level long-term more than 1 month preirradiation on mice is caused by decreased radiosensitivity radioresistance of the granulocytopoietic system which

Metainference: A Bayesian inference method for heterogeneous systems.

PubMed

Bonomi, Massimiliano; Camilloni, Carlo; Cavalli, Andrea; Vendruscolo, Michele

2016-01-01

Modeling a complex system is almost invariably a challenging task. The incorporation of experimental observations can be used to improve the quality of a model and thus to obtain better predictions about the behavior of the corresponding system. This approach, however, is affected by a variety of different errors, especially when a system simultaneously populates an ensemble of different states and experimental data are measured as averages over such states. To address this problem, we present a Bayesian inference method, called "metainference," that is able to deal with errors in experimental measurements and with experimental measurements averaged over multiple states. To achieve this goal, metainference models a finite sample of the distribution of models using a replica approach, in the spirit of the replica-averaging modeling based on the maximum entropy principle. To illustrate the method, we present its application to a heterogeneous model system and to the determination of an ensemble of structures corresponding to the thermal fluctuations of a protein molecule. Metainference thus provides an approach to modeling complex systems with heterogeneous components and interconverting between different states by taking into account all possible sources of errors.

Modeling nanomaterial environmental fate in aquatic systems.

PubMed

Dale, Amy L; Casman, Elizabeth A; Lowry, Gregory V; Lead, Jamie R; Viparelli, Enrica; Baalousha, Mohammed

2015-03-03

Mathematical models improve our fundamental understanding of the environmental behavior, fate, and transport of engineered nanomaterials (NMs, chemical substances or materials roughly 1-100 nm in size) and facilitate risk assessment and management activities. Although today's large-scale environmental fate models for NMs are a considerable improvement over early efforts, a gap still remains between the experimental research performed to date on the environmental fate of NMs and its incorporation into models. This article provides an introduction to the current state of the science in modeling the fate and behavior of NMs in aquatic environments. We address the strengths and weaknesses of existing fate models, identify the challenges facing researchers in developing and validating these models, and offer a perspective on how these challenges can be addressed through the combined efforts of modelers and experimentalists.

Experimental Escherichia coli peritonitis in immunosuppressed mice: the role of specific and non-specific immunity.

PubMed

Vuopio-Varkila, J

1988-01-01

An experimental Escherichia coli septicaemia-peritonitis model was adapted to immunosuppressed mice. The mice were made neutropenic by a sublethal dose of cyclophosphamide, which resulted in a 100-fold increase in their susceptibility to intraperitoneal injection of E. coli O18:K1. A lethal infection could be prevented by passive immunisation with anti-K1 capsular or anti-O18 LPS antibodies but not with anti-J5 bacterial antibodies. The anti-K1 and anti-O18 antisera were able to increase the LD50 of the E. coli challenge by factors of 50 and 5, respectively. The role of non-specific, lipopolysaccharide (LPS)-mediated resistance to infection was also investigated in this model, in which only long-living phagocytic cells such as macrophages are believed to be functional. Pretreatment of mice with LPS was shown to prevent growth of the bacterial challenge in the peritoneal cavity and blood and to result in a five-fold increase in the LD50 of the challenge strain. These findings suggest an important role for macrophages as effector cells in defence against E. coli infection.

Mastitomics, the integrated omics of bovine milk in an experimental model of Streptococcus uberis mastitis: 2. Label-free relative quantitative proteomics.

PubMed

Mudaliar, Manikhandan; Tassi, Riccardo; Thomas, Funmilola C; McNeilly, Tom N; Weidt, Stefan K; McLaughlin, Mark; Wilson, David; Burchmore, Richard; Herzyk, Pawel; Eckersall, P David; Zadoks, Ruth N

2016-08-16

Mastitis, inflammation of the mammary gland, is the most common and costly disease of dairy cattle in the western world. It is primarily caused by bacteria, with Streptococcus uberis as one of the most prevalent causative agents. To characterize the proteome during Streptococcus uberis mastitis, an experimentally induced model of intramammary infection was used. Milk whey samples obtained from 6 cows at 6 time points were processed using label-free relative quantitative proteomics. This proteomic analysis complements clinical, bacteriological and immunological studies as well as peptidomic and metabolomic analysis of the same challenge model. A total of 2552 non-redundant bovine peptides were identified, and from these, 570 bovine proteins were quantified. Hierarchical cluster analysis and principal component analysis showed clear clustering of results by stage of infection, with similarities between pre-infection and resolution stages (0 and 312 h post challenge), early infection stages (36 and 42 h post challenge) and late infection stages (57 and 81 h post challenge). Ingenuity pathway analysis identified upregulation of acute phase protein pathways over the course of infection, with dominance of different acute phase proteins at different time points based on differential expression analysis. Antimicrobial peptides, notably cathelicidins and peptidoglycan recognition protein, were upregulated at all time points post challenge and peaked at 57 h, which coincided with 10 000-fold decrease in average bacterial counts. The integration of clinical, bacteriological, immunological and quantitative proteomics and other-omic data provides a more detailed systems level view of the host response to mastitis than has been achieved previously.

Physics of human cooperation: experimental evidence and theoretical models

NASA Astrophysics Data System (ADS)

Sánchez, Angel

2018-02-01

In recent years, many physicists have used evolutionary game theory combined with a complex systems perspective in an attempt to understand social phenomena and challenges. Prominent among such phenomena is the issue of the emergence and sustainability of cooperation in a networked world of selfish or self-focused individuals. The vast majority of research done by physicists on these questions is theoretical, and is almost always posed in terms of agent-based models. Unfortunately, more often than not such models ignore a number of facts that are well established experimentally, and are thus rendered irrelevant to actual social applications. I here summarize some of the facts that any realistic model should incorporate and take into account, discuss important aspects underlying the relation between theory and experiments, and discuss future directions for research based on the available experimental knowledge.

Statistical modelling of networked human-automation performance using working memory capacity.

PubMed

Ahmed, Nisar; de Visser, Ewart; Shaw, Tyler; Mohamed-Ameen, Amira; Campbell, Mark; Parasuraman, Raja

2014-01-01

This study examines the challenging problem of modelling the interaction between individual attentional limitations and decision-making performance in networked human-automation system tasks. Analysis of real experimental data from a task involving networked supervision of multiple unmanned aerial vehicles by human participants shows that both task load and network message quality affect performance, but that these effects are modulated by individual differences in working memory (WM) capacity. These insights were used to assess three statistical approaches for modelling and making predictions with real experimental networked supervisory performance data: classical linear regression, non-parametric Gaussian processes and probabilistic Bayesian networks. It is shown that each of these approaches can help designers of networked human-automated systems cope with various uncertainties in order to accommodate future users by linking expected operating conditions and performance from real experimental data to observable cognitive traits like WM capacity. Practitioner Summary: Working memory (WM) capacity helps account for inter-individual variability in operator performance in networked unmanned aerial vehicle supervisory tasks. This is useful for reliable performance prediction near experimental conditions via linear models; robust statistical prediction beyond experimental conditions via Gaussian process models and probabilistic inference about unknown task conditions/WM capacities via Bayesian network models.

Experimental Evaluation of a Serious Game for Teaching Software Process Modeling

ERIC Educational Resources Information Center

Chaves, Rafael Oliveira; von Wangenheim, Christiane Gresse; Furtado, Julio Cezar Costa; Oliveira, Sandro Ronaldo Bezerra; Santos, Alex; Favero, Eloi Luiz

2015-01-01

Software process modeling (SPM) is an important area of software engineering because it provides a basis for managing, automating, and supporting software process improvement (SPI). Teaching SPM is a challenging task, mainly because it lays great emphasis on theory and offers few practical exercises. Furthermore, as yet few teaching approaches…

Visible Machine Learning for Biomedicine.

PubMed

Yu, Michael K; Ma, Jianzhu; Fisher, Jasmin; Kreisberg, Jason F; Raphael, Benjamin J; Ideker, Trey

2018-06-14

A major ambition of artificial intelligence lies in translating patient data to successful therapies. Machine learning models face particular challenges in biomedicine, however, including handling of extreme data heterogeneity and lack of mechanistic insight into predictions. Here, we argue for "visible" approaches that guide model structure with experimental biology. Copyright © 2018. Published by Elsevier Inc.

Challenging the Fructose Hypothesis: New Perspectives on Fructose Consumption and Metabolism123

PubMed Central

White, John S.

2013-01-01

The field of sugar metabolism, and fructose metabolism in particular, has experienced a resurgence of interest in the past decade. The “fructose hypothesis” alleges that the fructose component common to all major caloric sweeteners (sucrose, high-fructose corn syrup, honey, and fruit juice concentrates) plays a unique and causative role in the increasing rates of cardiovascular disease, hypertension, diabetes, cancer, and nonalcoholic fatty liver disease. This review challenges the fructose hypothesis by comparing normal U.S. levels and patterns of fructose intake with contemporary experimental models and looking for substantive cause-and-effect evidence from real-world diets. It is concluded that 1) fructose intake at normal population levels and patterns does not cause biochemical outcomes substantially different from other dietary sugars and 2) extreme experimental models that feature hyperdosing or significantly alter the usual dietary glucose-to-fructose ratio are not predictive of typical human outcomes or useful to public health policymakers. It is recommended that granting agencies and journal editors require more physiologically relevant experimental designs and clinically important outcomes for fructose research. PMID:23493541

Kinetics of Leptospira interrogans Infection in Hamsters after Intradermal and Subcutaneous Challenge

PubMed Central

Coutinho, Mariana L.; Matsunaga, James; Wang, Long-Chieh; de la Peña Moctezuma, Alejandro; Lewis, Michael S.; Babbitt, Jane T.; Aleixo, Jose Antonio G.; Haake, David A.

2014-01-01

Background Leptospirosis is a zoonosis caused by highly motile, helically shaped bacteria that penetrate the skin and mucous membranes through lesions or abrasions, and rapidly disseminate throughout the body. Although the intraperitoneal route of infection is widely used to experimentally inoculate hamsters, this challenge route does not represent a natural route of infection. Methodology/Principal Findings Here we describe the kinetics of disease and infection in hamster model of leptospirosis after subcutaneous and intradermal inoculation of Leptospira interrogans serovar Copenhageni, strain Fiocruz L1-130. Histopathologic changes in and around the kidney, including glomerular and tubular damage and interstitial inflammatory changes, began on day 5, and preceded deterioration in renal function as measured by serum creatinine. Weight loss, hemoconcentration, increased absolute neutrophil counts (ANC) in the blood and hepatic dysfunction were first noted on day 6. Vascular endothelial growth factor, a serum marker of sepsis severity, became elevated during the later stages of infection. The burden of infection, as measured by quantitative PCR, was highest in the kidney and peaked on day 5 after intradermal challenge and on day 6 after subcutaneous challenge. Compared to subcutaneous challenge, intradermal challenge resulted in a lower burden of infection in both the kidney and liver on day 6, lower ANC and less weight loss on day 7. Conclusions/Significance The intradermal and subcutaneous challenge routes result in significant differences in the kinetics of dissemination and disease after challenge with L. interrogans serovar Copenhageni strain Fiocruz L1-130 at an experimental dose of 2×106 leptospires. These results provide new information regarding infection kinetics in the hamster model of leptospirosis. PMID:25411782

Data archiving and availability in an era of open science.

PubMed

Baker, Edward N

2017-01-01

The importance of preserving and making available the original experimental data underlying biological structural models is discussed, both for crystallography, where the raw data images pose particular challenges, and for other structure determination techniques.

Experimental Models to Study the Role of Microbes in Host-Parasite Interactions.

PubMed

Hahn, Megan A; Dheilly, Nolwenn M

2016-01-01

Until recently, parasitic infections have been primarily studied as interactions between the parasite and the host, leaving out crucial players: microbes. The recent realization that microbes play key roles in the biology of all living organisms is not only challenging our understanding of host-parasite evolution, but it also provides new clues to develop new therapies and remediation strategies. In this paper we provide a review of promising and advanced experimental organismal systems to examine the dynamic of host-parasite-microbe interactions. We address the benefits of developing new experimental models appropriate to this new research area and identify systems that offer the best promises considering the nature of the interactions among hosts, parasites, and microbes. Based on these systems, we identify key criteria for selecting experimental models to elucidate the fundamental principles of these complex webs of interactions. It appears that no model is ideal and that complementary studies should be performed on different systems in order to understand the driving roles of microbes in host and parasite evolution.

Transient feeding of a concentrate-rich diet increases the severity of subacute ruminal acidosis in dairy cattle.

PubMed

Pourazad, P; Khiaosa-Ard, R; Qumar, M; Wetzels, S U; Klevenhusen, F; Metzler-Zebeli, B U; Zebeli, Q

2016-02-01

The objective of this study was to investigate the effect of the pattern of concentrate-rich feeding on subacute ruminal acidosis (SARA), its severity, and the corresponding changes in VFA concentration. Eight rumen-cannulated Holstein cows were assigned to a 2 × 2 crossover design with 2 SARA challenge models and 2 experimental runs ( = 8 per treatment). Each run lasted for 40 d, consisting of a 6-d baseline, a 6-d gradual grain adaptation, and a 28-d SARA challenge period. The 2 SARA challenge models were transient (TRA) and persistent (PER) SARA. Initially, all cows were subjected to a forage-only diet (baseline) and gradually switched to 60% concentrate (DM basis). Then, cows in the PER model were continuously challenged for 28 d, whereas cows in the TRA model had a 7-d break from the SARA diet and were fed the forage-only diet after the first 7 d of SARA challenge. Thereafter, the TRA cows were rechallenged with the SARA diet. Wireless ruminal pH sensors were used to obtain ruminal pH profiles and temperature over the experimental period. For the determination of VFA, free ruminal liquid (FRL) and particle-associated ruminal liquid (PARL) were collected once for the baseline and twice (d 20 and 40 for the PER model) or 3 times (d 13, 30, and 40 for the TRA model) during SARA, each time at 0, 4, and 8 h after the morning feeding. Cows in both models experienced SARA albeit with day-to-day variation. From the start until the first 7-d SARA, cows of both models had similar pH profiles, but during the rechallenge, SARA was more severe in the TRA model than in the PER model based on lower daily mean ruminal pH (5.93 vs. 6.15; SEM 0.058) and double the amount of time at pH < 5.8 (497 vs. 278 min; SEM 68.61, < 0.05). Mean ruminal temperature was raised during SARA compared with the baseline (38.9 vs. 38.7°C; SEM 0.057, < 0.001). Concentrations of VFA increased with increasing time after feeding ( < 0.001). In general, SARA challenge (d 40 vs. the baseline), but not the challenge model, altered VFA concentrations and profile of both FRL and PARL by increasing the amounts of propionate and butyrate, whereas total VFA concentration was less affected. Proportions of VFA shifted over the duration of SARA challenge with more propionate but less acetate and butyrate proportions with advancing days of SARA challenge, leading to the values of the last SARA day being different from the earlier days ( < 0.05). In conclusion, the TRA condition led to the higher severity of SARA, but factors beyond feed intake and VFA alterations seemed to play a role.

Evaluation of the efficacy of an autogenous Escherichia coli vaccine in broiler breeders.

PubMed

Li, Lili; Thøfner, Ida; Christensen, Jens Peter; Ronco, Troels; Pedersen, Karl; Olsen, Rikke H

2017-06-01

In poultry production Escherichia coli autogenous vaccines are often used. However, the efficacy of autogenous E. coli vaccinations has not been evaluated experimentally in chickens after start of lay. The aim of the present study was to evaluate the protective effect of an autogenous E. coli vaccine in broiler breeders. Three groups of 28-week-old broiler breeders (unvaccinated, vaccinated once and twice, respectively) were challenged with a homologous E. coli strain (same strain as included in the vaccine) or a heterologous challenge strain in an experimental ascending model. The clinical outcome was most pronounced in the unvaccinated group; however, the vast majority of chickens in the vaccinated groups had severe pathological manifestations similar to findings in the unvaccinated group after challenge with a homologous as well as a heterologous E. coli strain. Although significant titre rises in IgY antibodies were observed in the twice vaccinated group, antibodies did not confer significant protection in terms of pathological impact. Neither could transfer of maternal-derived antibodies to offspring be demonstrated. In conclusion, with the use of the present model for ascending infection, significant protection of an autogenous E. coli vaccine against neither a homologous nor a heterologous E. coli challenge could not be documented.

Pore-scale and Continuum Simulations of Solute Transport Micromodel Benchmark Experiments

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

Oostrom, Martinus; Mehmani, Yashar; Romero Gomez, Pedro DJ

Four sets of micromodel nonreactive solute transport experiments were conducted with flow velocity, grain diameter, pore-aspect ratio, and flow focusing heterogeneity as the variables. The data sets were offered to pore-scale modeling groups to test their simulators. Each set consisted of two learning experiments, for which all results was made available, and a challenge experiment, for which only the experimental description and base input parameters were provided. The experimental results showed a nonlinear dependence of the dispersion coefficient on the Peclet number, a negligible effect of the pore-aspect ratio on transverse mixing, and considerably enhanced mixing due to flow focusing.more » Five pore-scale models and one continuum-scale model were used to simulate the experiments. Of the pore-scale models, two used a pore-network (PN) method, two others are based on a lattice-Boltzmann (LB) approach, and one employed a computational fluid dynamics (CFD) technique. The learning experiments were used by the PN models to modify the standard perfect mixing approach in pore bodies into approaches to simulate the observed incomplete mixing. The LB and CFD models used these experiments to appropriately discretize the grid representations. The continuum model use published non-linear relations between transverse dispersion coefficients and Peclet numbers to compute the required dispersivity input values. Comparisons between experimental and numerical results for the four challenge experiments show that all pore-scale models were all able to satisfactorily simulate the experiments. The continuum model underestimated the required dispersivity values and, resulting in less dispersion. The PN models were able to complete the simulations in a few minutes, whereas the direct models needed up to several days on supercomputers to resolve the more complex problems.« less

Comparative experimental subcutaneous glanders and melioidosis in the common marmoset (Callithrix jacchus)

PubMed Central

Nelson, Michelle; Salguero, Francisco J; Dean, Rachel E; Ngugi, Sarah A; Smither, Sophie J; Atkins, Timothy P; Lever, Mark S

2014-01-01

Glanders and melioidosis are caused by two distinct Burkholderia species and have generally been considered to have similar disease progression. While both of these pathogens are HHS/CDC Tier 1 agents, natural infection with both these pathogens is primarily through skin inoculation. The common marmoset (Callithrix jacchus) was used to compare disease following experimental subcutaneous challenge. Acute, lethal disease was observed in marmosets following challenge with between 26 and 1.2 × 108 cfu Burkholderia pseudomallei within 22–85 h. The reproducibility and progression of the disease were assessed following a challenge of 1 × 102 cfu of B. pseudomallei. Melioidosis was characterised by high levels of bacteraemia, focal microgranuloma progressing to non-necrotic multifocal solid lesions in the livers and spleens and multi-organ failure. Lethal disease was observed in 93% of animals challenged with Burkholderia mallei, occurring between 5 and 10.6 days. Following challenge with 1 × 102 cfu of B. mallei, glanders was characterised with lymphatic spread of the bacteria and non-necrotic, multifocal solid lesions progressing to a multifocal lesion with severe necrosis and pneumonia. The experimental results confirmed that the disease pathology and presentation is strikingly different between the two pathogens. The marmoset provides a model of the human syndrome for both diseases facilitating the development of medical countermeasures. PMID:25477002

Accounting for reciprocal host-microbiome interactions in experimental science.

PubMed

Stappenbeck, Thaddeus S; Virgin, Herbert W

2016-06-09

Mammals are defined by their metagenome, a combination of host and microbiome genes. This knowledge presents opportunities to further basic biology with translation to human diseases. However, the now-documented influence of the metagenome on experimental results and the reproducibility of in vivo mammalian models present new challenges. Here we provide the scientific basis for calling on all investigators, editors and funding agencies to embrace changes that will enhance reproducible and interpretable experiments by accounting for metagenomic effects. Implementation of new reporting and experimental design principles will improve experimental work, speed discovery and translation, and properly use substantial investments in biomedical research.

Wires in the soup: quantitative models of cell signaling

PubMed Central

Cheong, Raymond; Levchenko, Andre

2014-01-01

Living cells are capable of extracting information from their environments and mounting appropriate responses to a variety of associated challenges. The underlying signal transduction networks enabling this can be quite complex, necessitating for their unraveling by sophisticated computational modeling coupled with precise experimentation. Although we are still at the beginning of this process, some recent examples of integrative analysis of cell signaling are very encouraging. This review highlights the case of the NF-κB pathway in order to illustrate how a quantitative model of a signaling pathway can be gradually constructed through continuous experimental validation, and what lessons one might learn from such exercises. PMID:18291655

Quasi-experimental study designs series-paper 10: synthesizing evidence for effects collected from quasi-experimental studies presents surmountable challenges.

PubMed

Becker, Betsy Jane; Aloe, Ariel M; Duvendack, Maren; Stanley, T D; Valentine, Jeffrey C; Fretheim, Atle; Tugwell, Peter

2017-09-01

To outline issues of importance to analytic approaches to the synthesis of quasi-experiments (QEs) and to provide a statistical model for use in analysis. We drew on studies of statistics, epidemiology, and social-science methodology to outline methods for synthesis of QE studies. The design and conduct of QEs, effect sizes from QEs, and moderator variables for the analysis of those effect sizes were discussed. Biases, confounding, design complexities, and comparisons across designs offer serious challenges to syntheses of QEs. Key components of meta-analyses of QEs were identified, including the aspects of QE study design to be coded and analyzed. Of utmost importance are the design and statistical controls implemented in the QEs. Such controls and any potential sources of bias and confounding must be modeled in analyses, along with aspects of the interventions and populations studied. Because of such controls, effect sizes from QEs are more complex than those from randomized experiments. A statistical meta-regression model that incorporates important features of the QEs under review was presented. Meta-analyses of QEs provide particular challenges, but thorough coding of intervention characteristics and study methods, along with careful analysis, should allow for sound inferences. Copyright © 2017 Elsevier Inc. All rights reserved.

Large-scale flow experiments for managing river systems

USGS Publications Warehouse

Konrad, Christopher P.; Olden, Julian D.; Lytle, David A.; Melis, Theodore S.; Schmidt, John C.; Bray, Erin N.; Freeman, Mary C.; Gido, Keith B.; Hemphill, Nina P.; Kennard, Mark J.; McMullen, Laura E.; Mims, Meryl C.; Pyron, Mark; Robinson, Christopher T.; Williams, John G.

2011-01-01

Experimental manipulations of streamflow have been used globally in recent decades to mitigate the impacts of dam operations on river systems. Rivers are challenging subjects for experimentation, because they are open systems that cannot be isolated from their social context. We identify principles to address the challenges of conducting effective large-scale flow experiments. Flow experiments have both scientific and social value when they help to resolve specific questions about the ecological action of flow with a clear nexus to water policies and decisions. Water managers must integrate new information into operating policies for large-scale experiments to be effective. Modeling and monitoring can be integrated with experiments to analyze long-term ecological responses. Experimental design should include spatially extensive observations and well-defined, repeated treatments. Large-scale flow manipulations are only a part of dam operations that affect river systems. Scientists can ensure that experimental manipulations continue to be a valuable approach for the scientifically based management of river systems.

Experimental Definition and Validation of Protein Coding Transcripts in Chlamydomonas reinhardtii

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

Kourosh Salehi-Ashtiani; Jason A. Papin

Algal fuel sources promise unsurpassed yields in a carbon neutral manner that minimizes resource competition between agriculture and fuel crops. Many challenges must be addressed before algal biofuels can be accepted as a component of the fossil fuel replacement strategy. One significant challenge is that the cost of algal fuel production must become competitive with existing fuel alternatives. Algal biofuel production presents the opportunity to fine-tune microbial metabolic machinery for an optimal blend of biomass constituents and desired fuel molecules. Genome-scale model-driven algal metabolic design promises to facilitate both goals by directing the utilization of metabolites in the complex, interconnectedmore » metabolic networks to optimize production of the compounds of interest. Using Chlamydomonas reinhardtii as a model, we developed a systems-level methodology bridging metabolic network reconstruction with annotation and experimental verification of enzyme encoding open reading frames. We reconstructed a genome-scale metabolic network for this alga and devised a novel light-modeling approach that enables quantitative growth prediction for a given light source, resolving wavelength and photon flux. We experimentally verified transcripts accounted for in the network and physiologically validated model function through simulation and generation of new experimental growth data, providing high confidence in network contents and predictive applications. The network offers insight into algal metabolism and potential for genetic engineering and efficient light source design, a pioneering resource for studying light-driven metabolism and quantitative systems biology. Our approach to generate a predictive metabolic model integrated with cloned open reading frames, provides a cost-effective platform to generate metabolic engineering resources. While the generated resources are specific to algal systems, the approach that we have developed is not specific to algae and can be readily expanded to other microbial systems as well as higher plants and animals.« less

Validation of pore network simulations of ex-situ water distributions in a gas diffusion layer of proton exchange membrane fuel cells with X-ray tomographic images

NASA Astrophysics Data System (ADS)

Agaesse, Tristan; Lamibrac, Adrien; Büchi, Felix N.; Pauchet, Joel; Prat, Marc

2016-11-01

Understanding and modeling two-phase flows in the gas diffusion layer (GDL) of proton exchange membrane fuel cells are important in order to improve fuel cells performance. They are scientifically challenging because of the peculiarities of GDLs microstructures. In the present work, simulations on a pore network model are compared to X-ray tomographic images of water distributions during an ex-situ water invasion experiment. A method based on watershed segmentation was developed to extract a pore network from the 3D segmented image of the dry GDL. Pore network modeling and a full morphology model were then used to perform two-phase simulations and compared to the experimental data. The results show good agreement between experimental and simulated microscopic water distributions. Pore network extraction parameters were also benchmarked using the experimental data and results from full morphology simulations.

Experimental models of hepatotoxicity related to acute liver failure

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

Maes, Michaël; Vinken, Mathieu, E-mail: mvinken@vub.ac.be; Jaeschke, Hartmut

Acute liver failure can be the consequence of various etiologies, with most cases arising from drug-induced hepatotoxicity in Western countries. Despite advances in this field, the management of acute liver failure continues to be one of the most challenging problems in clinical medicine. The availability of adequate experimental models is of crucial importance to provide a better understanding of this condition and to allow identification of novel drug targets, testing the efficacy of new therapeutic interventions and acting as models for assessing mechanisms of toxicity. Experimental models of hepatotoxicity related to acute liver failure rely on surgical procedures, chemical exposuremore » or viral infection. Each of these models has a number of strengths and weaknesses. This paper specifically reviews commonly used chemical in vivo and in vitro models of hepatotoxicity associated with acute liver failure. - Highlights: • The murine APAP model is very close to what is observed in patients. • The Gal/ET model is useful to study TNFα-mediated apoptotic signaling mechanisms. • Fas receptor activation is an effective model of apoptosis and secondary necrosis. • The ConA model is a relevant model of auto-immune hepatitis and viral hepatitis. • Multiple time point evaluation needed in experimental models of acute liver injury.« less

Exploring charge density analysis in crystals at high pressure: data collection, data analysis and advanced modelling.

PubMed

Casati, Nicola; Genoni, Alessandro; Meyer, Benjamin; Krawczuk, Anna; Macchi, Piero

2017-08-01

The possibility to determine electron-density distribution in crystals has been an enormous breakthrough, stimulated by a favourable combination of equipment for X-ray and neutron diffraction at low temperature, by the development of simplified, though accurate, electron-density models refined from the experimental data and by the progress in charge density analysis often in combination with theoretical work. Many years after the first successful charge density determination and analysis, scientists face new challenges, for example: (i) determination of the finer details of the electron-density distribution in the atomic cores, (ii) simultaneous refinement of electron charge and spin density or (iii) measuring crystals under perturbation. In this context, the possibility of obtaining experimental charge density at high pressure has recently been demonstrated [Casati et al. (2016). Nat. Commun. 7, 10901]. This paper reports on the necessities and pitfalls of this new challenge, focusing on the species syn-1,6:8,13-biscarbonyl[14]annulene. The experimental requirements, the expected data quality and data corrections are discussed in detail, including warnings about possible shortcomings. At the same time, new modelling techniques are proposed, which could enable specific information to be extracted, from the limited and less accurate observations, like the degree of localization of double bonds, which is fundamental to the scientific case under examination.

A self-cognizant dynamic system approach for prognostics and health management

NASA Astrophysics Data System (ADS)

Bai, Guangxing; Wang, Pingfeng; Hu, Chao

2015-03-01

Prognostics and health management (PHM) is an emerging engineering discipline that diagnoses and predicts how and when a system will degrade its performance and lose its partial or whole functionality. Due to the complexity and invisibility of rules and states of most dynamic systems, developing an effective approach to track evolving system states becomes a major challenge. This paper presents a new self-cognizant dynamic system (SCDS) approach that incorporates artificial intelligence into dynamic system modeling for PHM. A feed-forward neural network (FFNN) is selected to approximate a complex system response which is challenging task in general due to inaccessible system physics. The trained FFNN model is then embedded into a dual extended Kalman filter algorithm to track down system dynamics. A recursive computation technique used to update the FFNN model using online measurements is also derived. To validate the proposed SCDS approach, a battery dynamic system is considered as an experimental application. After modeling the battery system by a FFNN model and a state-space model, the state-of-charge (SoC) and state-of-health (SoH) are estimated by updating the FFNN model using the proposed approach. Experimental results suggest that the proposed approach improves the efficiency and accuracy for battery health management.

Review: mechanical behavior of metal/ceramic interfaces in nanolayered composites—experiments and modeling

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

Li, Nan; Liu, Xiang-Yang

In this study, recent experimental and modeling studies in nanolayered metal/ceramic composites are reviewed, with focus on the mechanical behaviors of metal/nitrides interfaces. The experimental and modeling studies of the slip systems in bulk TiN are reviewed first. Then, the experimental studies of interfaces, including co-deformation mechanism by micropillar compression tests, in situ TEM straining tests for the dynamic process of the co-deformation, thickness-dependent fracture behavior, and interrelationship among the interfacial bonding, microstructure, and mechanical response, are reviewed for the specific material systems of Al/TiN and Cu/TiN multilayers at nanoscale. The modeling studies reviewed cover first-principles density functional theory-based modeling,more » atomistic molecular dynamics simulations, and mesoscale modeling of nanolayered composites using discrete dislocation dynamics. The phase transformation between zinc-blende and wurtzite AlN phases in Al/AlN multilayers at nanoscale is also reviewed. Finally, a summary and perspective of possible research directions and challenges are given.« less

Review: mechanical behavior of metal/ceramic interfaces in nanolayered composites—experiments and modeling

DOE PAGES

Li, Nan; Liu, Xiang-Yang

2017-11-03

In this study, recent experimental and modeling studies in nanolayered metal/ceramic composites are reviewed, with focus on the mechanical behaviors of metal/nitrides interfaces. The experimental and modeling studies of the slip systems in bulk TiN are reviewed first. Then, the experimental studies of interfaces, including co-deformation mechanism by micropillar compression tests, in situ TEM straining tests for the dynamic process of the co-deformation, thickness-dependent fracture behavior, and interrelationship among the interfacial bonding, microstructure, and mechanical response, are reviewed for the specific material systems of Al/TiN and Cu/TiN multilayers at nanoscale. The modeling studies reviewed cover first-principles density functional theory-based modeling,more » atomistic molecular dynamics simulations, and mesoscale modeling of nanolayered composites using discrete dislocation dynamics. The phase transformation between zinc-blende and wurtzite AlN phases in Al/AlN multilayers at nanoscale is also reviewed. Finally, a summary and perspective of possible research directions and challenges are given.« less

Multiphysics and multiscale modelling, data-model fusion and integration of organ physiology in the clinic: ventricular cardiac mechanics.

PubMed

Chabiniok, Radomir; Wang, Vicky Y; Hadjicharalambous, Myrianthi; Asner, Liya; Lee, Jack; Sermesant, Maxime; Kuhl, Ellen; Young, Alistair A; Moireau, Philippe; Nash, Martyn P; Chapelle, Dominique; Nordsletten, David A

2016-04-06

With heart and cardiovascular diseases continually challenging healthcare systems worldwide, translating basic research on cardiac (patho)physiology into clinical care is essential. Exacerbating this already extensive challenge is the complexity of the heart, relying on its hierarchical structure and function to maintain cardiovascular flow. Computational modelling has been proposed and actively pursued as a tool for accelerating research and translation. Allowing exploration of the relationships between physics, multiscale mechanisms and function, computational modelling provides a platform for improving our understanding of the heart. Further integration of experimental and clinical data through data assimilation and parameter estimation techniques is bringing computational models closer to use in routine clinical practice. This article reviews developments in computational cardiac modelling and how their integration with medical imaging data is providing new pathways for translational cardiac modelling.

Advances and perspectives in in vitro human gut fermentation modeling.

PubMed

Payne, Amanda N; Zihler, Annina; Chassard, Christophe; Lacroix, Christophe

2012-01-01

The gut microbiota is a highly specialized organ containing host-specific assemblages of microbes whereby metabolic activity directly impacts human health and disease. In vitro gut fermentation models present an unmatched opportunity of performing studies frequently challenged in humans and animals owing to ethical concerns. Multidisciplinary systems biology analyses supported by '-omics' platforms remain widely neglected in the field of in vitro gut fermentation modeling but are key to advancing the significance of these models. Model-driven experimentation using a combination of in vitro gut fermentation and in vitro human cell models represent an advanced approach in identifying complex host-microbe interactions and niches central to gut fermentation processes. The aim of this review is to highlight the advances and challenges exhibited by in vitro human gut fermentation modeling. Copyright © 2011 Elsevier Ltd. All rights reserved.

Mock Data Challenge for the MPD/NICA Experiment on the HybriLIT Cluster

NASA Astrophysics Data System (ADS)

Gertsenberger, Konstantin; Rogachevsky, Oleg

2018-02-01

Simulation of data processing before receiving first experimental data is an important issue in high-energy physics experiments. This article presents the current Event Data Model and the Mock Data Challenge for the MPD experiment at the NICA accelerator complex which uses ongoing simulation studies to exercise in a stress-testing the distributed computing infrastructure and experiment software in the full production environment from simulated data through the physical analysis.

Metainference: A Bayesian inference method for heterogeneous systems

PubMed Central

Bonomi, Massimiliano; Camilloni, Carlo; Cavalli, Andrea; Vendruscolo, Michele

2016-01-01

Modeling a complex system is almost invariably a challenging task. The incorporation of experimental observations can be used to improve the quality of a model and thus to obtain better predictions about the behavior of the corresponding system. This approach, however, is affected by a variety of different errors, especially when a system simultaneously populates an ensemble of different states and experimental data are measured as averages over such states. To address this problem, we present a Bayesian inference method, called “metainference,” that is able to deal with errors in experimental measurements and with experimental measurements averaged over multiple states. To achieve this goal, metainference models a finite sample of the distribution of models using a replica approach, in the spirit of the replica-averaging modeling based on the maximum entropy principle. To illustrate the method, we present its application to a heterogeneous model system and to the determination of an ensemble of structures corresponding to the thermal fluctuations of a protein molecule. Metainference thus provides an approach to modeling complex systems with heterogeneous components and interconverting between different states by taking into account all possible sources of errors. PMID:26844300

Model-driven analysis of experimentally determined growth phenotypes for 465 yeast gene deletion mutants under 16 different conditions

PubMed Central

Snitkin, Evan S; Dudley, Aimée M; Janse, Daniel M; Wong, Kaisheen; Church, George M; Segrè, Daniel

2008-01-01

Background Understanding the response of complex biochemical networks to genetic perturbations and environmental variability is a fundamental challenge in biology. Integration of high-throughput experimental assays and genome-scale computational methods is likely to produce insight otherwise unreachable, but specific examples of such integration have only begun to be explored. Results In this study, we measured growth phenotypes of 465 Saccharomyces cerevisiae gene deletion mutants under 16 metabolically relevant conditions and integrated them with the corresponding flux balance model predictions. We first used discordance between experimental results and model predictions to guide a stage of experimental refinement, which resulted in a significant improvement in the quality of the experimental data. Next, we used discordance still present in the refined experimental data to assess the reliability of yeast metabolism models under different conditions. In addition to estimating predictive capacity based on growth phenotypes, we sought to explain these discordances by examining predicted flux distributions visualized through a new, freely available platform. This analysis led to insight into the glycerol utilization pathway and the potential effects of metabolic shortcuts on model results. Finally, we used model predictions and experimental data to discriminate between alternative raffinose catabolism routes. Conclusions Our study demonstrates how a new level of integration between high throughput measurements and flux balance model predictions can improve understanding of both experimental and computational results. The added value of a joint analysis is a more reliable platform for specific testing of biological hypotheses, such as the catabolic routes of different carbon sources. PMID:18808699

An improved swarm optimization for parameter estimation and biological model selection.

PubMed

Abdullah, Afnizanfaizal; Deris, Safaai; Mohamad, Mohd Saberi; Anwar, Sohail

2013-01-01

One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This study is hoped to provide a new insight in developing more accurate and reliable biological models based on limited and low quality experimental data.

Evaluation of Full Reynolds Stress Turbulence Models in FUN3D

NASA Technical Reports Server (NTRS)

Dudek, Julianne C.; Carlson, Jan-Renee

2017-01-01

Full seven-equation Reynolds stress turbulence models are promising tools for today’s aerospace technology challenges. This paper examines two such models for computing challenging turbulent flows including shock-wave boundary layer interactions, separation and mixing layers. The Wilcox and the SSG/LRR full second-moment Reynolds stress models have been implemented into the FUN3D (Fully Unstructured Navier-Stokes Three Dimensional) unstructured Navier-Stokes code and were evaluated for four problems: a transonic two-dimensional diffuser, a supersonic axisymmetric compression corner, a compressible planar shear layer, and a subsonic axisymmetric jet. Simulation results are compared with experimental data and results computed using the more commonly used Spalart-Allmaras (SA) one-equation and the Menter Shear Stress Transport (SST-V) two-equation turbulence models.

Evaluation of Full Reynolds Stress Turbulence Models in FUN3D

NASA Technical Reports Server (NTRS)

Dudek, Julianne C.; Carlson, Jan-Renee

2017-01-01

Full seven-equation Reynolds stress turbulence models are a relatively new and promising tool for todays aerospace technology challenges. This paper uses two stress-omega full Reynolds stress models to evaluate challenging flows including shock-wave boundary layer interactions, separation and mixing layers. The Wilcox and the SSG/LRR full second-moment Reynolds stress models have been implemented into the FUN3D (Fully Unstructured Navier-Stokes Three Dimensional) unstructured Navier-Stokes code and are evaluated for four problems: a transonic two-dimensional diffuser, a supersonic axisymmetric compression corner, a compressible planar shear layer, and a subsonic axisymmetric jet. Simulation results are compared with experimental data and results using the more commonly used Spalart-Allmaras (SA) one-equation and the Menter Shear Stress Transport (SST-V) two-equation turbulence models.

Mastitomics, the integrated omics of bovine milk in an experimental model of Streptococcus uberis mastitis: 2. Label-free relative quantitative proteomics† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c6mb00290k Click here for additional data file.

PubMed Central

Mudaliar, Manikhandan; Tassi, Riccardo; Thomas, Funmilola C.; McNeilly, Tom N.; Weidt, Stefan K.; McLaughlin, Mark; Wilson, David; Burchmore, Richard; Herzyk, Pawel; Eckersall, P. David

2016-01-01

Mastitis, inflammation of the mammary gland, is the most common and costly disease of dairy cattle in the western world. It is primarily caused by bacteria, with Streptococcus uberis as one of the most prevalent causative agents. To characterize the proteome during Streptococcus uberis mastitis, an experimentally induced model of intramammary infection was used. Milk whey samples obtained from 6 cows at 6 time points were processed using label-free relative quantitative proteomics. This proteomic analysis complements clinical, bacteriological and immunological studies as well as peptidomic and metabolomic analysis of the same challenge model. A total of 2552 non-redundant bovine peptides were identified, and from these, 570 bovine proteins were quantified. Hierarchical cluster analysis and principal component analysis showed clear clustering of results by stage of infection, with similarities between pre-infection and resolution stages (0 and 312 h post challenge), early infection stages (36 and 42 h post challenge) and late infection stages (57 and 81 h post challenge). Ingenuity pathway analysis identified upregulation of acute phase protein pathways over the course of infection, with dominance of different acute phase proteins at different time points based on differential expression analysis. Antimicrobial peptides, notably cathelicidins and peptidoglycan recognition protein, were upregulated at all time points post challenge and peaked at 57 h, which coincided with 10 000-fold decrease in average bacterial counts. The integration of clinical, bacteriological, immunological and quantitative proteomics and other-omic data provides a more detailed systems level view of the host response to mastitis than has been achieved previously. PMID:27412694

Exploring theory space with Monte Carlo reweighting

DOE PAGES

Gainer, James S.; Lykken, Joseph; Matchev, Konstantin T.; ...

2014-10-13

Theories of new physics often involve a large number of unknown parameters which need to be scanned. Additionally, a putative signal in a particular channel may be due to a variety of distinct models of new physics. This makes experimental attempts to constrain the parameter space of motivated new physics models with a high degree of generality quite challenging. We describe how the reweighting of events may allow this challenge to be met, as fully simulated Monte Carlo samples generated for arbitrary benchmark models can be effectively re-used. Specifically, we suggest procedures that allow more efficient collaboration between theorists andmore » experimentalists in exploring large theory parameter spaces in a rigorous way at the LHC.« less

Compiler-aided systematic construction of large-scale DNA strand displacement circuits using unpurified components

NASA Astrophysics Data System (ADS)

Thubagere, Anupama J.; Thachuk, Chris; Berleant, Joseph; Johnson, Robert F.; Ardelean, Diana A.; Cherry, Kevin M.; Qian, Lulu

2017-02-01

Biochemical circuits made of rationally designed DNA molecules are proofs of concept for embedding control within complex molecular environments. They hold promise for transforming the current technologies in chemistry, biology, medicine and material science by introducing programmable and responsive behaviour to diverse molecular systems. As the transformative power of a technology depends on its accessibility, two main challenges are an automated design process and simple experimental procedures. Here we demonstrate the use of circuit design software, combined with the use of unpurified strands and simplified experimental procedures, for creating a complex DNA strand displacement circuit that consists of 78 distinct species. We develop a systematic procedure for overcoming the challenges involved in using unpurified DNA strands. We also develop a model that takes synthesis errors into consideration and semi-quantitatively reproduces the experimental data. Our methods now enable even novice researchers to successfully design and construct complex DNA strand displacement circuits.

Extended solvent-contact model approach to blind SAMPL5 prediction challenge for the distribution coefficients of drug-like molecules

NASA Astrophysics Data System (ADS)

Chung, Kee-Choo; Park, Hwangseo

2016-11-01

The performance of the extended solvent-contact model has been addressed in the SAMPL5 blind prediction challenge for distribution coefficient (LogD) of drug-like molecules with respect to the cyclohexane/water partitioning system. All the atomic parameters defined for 41 atom types in the solvation free energy function were optimized by operating a standard genetic algorithm with respect to water and cyclohexane solvents. In the parameterizations for cyclohexane, the experimental solvation free energy (Δ G sol ) data of 15 molecules for 1-octanol were combined with those of 77 molecules for cyclohexane to construct a training set because Δ G sol values of the former were unavailable for cyclohexane in publicly accessible databases. Using this hybrid training set, we established the LogD prediction model with the correlation coefficient ( R), average error (AE), and root mean square error (RMSE) of 0.55, 1.53, and 3.03, respectively, for the comparison of experimental and computational results for 53 SAMPL5 molecules. The modest accuracy in LogD prediction could be attributed to the incomplete optimization of atomic solvation parameters for cyclohexane. With respect to 31 SAMPL5 molecules containing the atom types for which experimental reference data for Δ G sol were available for both water and cyclohexane, the accuracy in LogD prediction increased remarkably with the R, AE, and RMSE values of 0.82, 0.89, and 1.60, respectively. This significant enhancement in performance stemmed from the better optimization of atomic solvation parameters by limiting the element of training set to the molecules with experimental Δ G sol data for cyclohexane. Due to the simplicity in model building and to low computational cost for parameterizations, the extended solvent-contact model is anticipated to serve as a valuable computational tool for LogD prediction upon the enrichment of experimental Δ G sol data for organic solvents.

CURRENT CHALLENGES ON ENDOCRINE DISRUPTORS

EPA Science Inventory

For over ten years, major international efforts have been aimed at understanding the mechanism and extent of endocrine disruption in experimental models, wildlife, and people; the occurrence of this in the real world and in developing tools for screening and prediction of risk. ...

Computational Biochemistry-Enzyme Mechanisms Explored.

PubMed

Culka, Martin; Gisdon, Florian J; Ullmann, G Matthias

2017-01-01

Understanding enzyme mechanisms is a major task to achieve in order to comprehend how living cells work. Recent advances in biomolecular research provide huge amount of data on enzyme kinetics and structure. The analysis of diverse experimental results and their combination into an overall picture is, however, often challenging. Microscopic details of the enzymatic processes are often anticipated based on several hints from macroscopic experimental data. Computational biochemistry aims at creation of a computational model of an enzyme in order to explain microscopic details of the catalytic process and reproduce or predict macroscopic experimental findings. Results of such computations are in part complementary to experimental data and provide an explanation of a biochemical process at the microscopic level. In order to evaluate the mechanism of an enzyme, a structural model is constructed which can be analyzed by several theoretical approaches. Several simulation methods can and should be combined to get a reliable picture of the process of interest. Furthermore, abstract models of biological systems can be constructed combining computational and experimental data. In this review, we discuss structural computational models of enzymatic systems. We first discuss various models to simulate enzyme catalysis. Furthermore, we review various approaches how to characterize the enzyme mechanism both qualitatively and quantitatively using different modeling approaches. © 2017 Elsevier Inc. All rights reserved.

Virtual optical network mapping and core allocation in elastic optical networks using multi-core fibers

NASA Astrophysics Data System (ADS)

Xuan, Hejun; Wang, Yuping; Xu, Zhanqi; Hao, Shanshan; Wang, Xiaoli

2017-11-01

Virtualization technology can greatly improve the efficiency of the networks by allowing the virtual optical networks to share the resources of the physical networks. However, it will face some challenges, such as finding the efficient strategies for virtual nodes mapping, virtual links mapping and spectrum assignment. It is even more complex and challenging when the physical elastic optical networks using multi-core fibers. To tackle these challenges, we establish a constrained optimization model to determine the optimal schemes of optical network mapping, core allocation and spectrum assignment. To solve the model efficiently, tailor-made encoding scheme, crossover and mutation operators are designed. Based on these, an efficient genetic algorithm is proposed to obtain the optimal schemes of the virtual nodes mapping, virtual links mapping, core allocation. The simulation experiments are conducted on three widely used networks, and the experimental results show the effectiveness of the proposed model and algorithm.

MFIX simulation of NETL/PSRI challenge problem of circulating fluidized bed

DOE PAGES

Li, Tingwen; Dietiker, Jean-François; Shahnam, Mehrdad

2012-12-01

In this paper, numerical simulations of NETL/PSRI challenge problem of circulating fluidized bed (CFB) using the open-source code Multiphase Flow with Interphase eXchange (MFIX) are reported. Two rounds of simulation results are reported including the first-round blind test and the second-round modeling refinement. Three-dimensional high fidelity simulations are conducted to model a 12-inch diameter pilot-scale CFB riser. Detailed comparisons between numerical results and experimental data are made with respect to axial pressure gradient profile, radial profiles of solids velocity and solids mass flux along different radial directions at various elevations for operating conditions covering different fluidization regimes. Overall, the numericalmore » results show that CFD can predict the complex gas–solids flow behavior in the CFB riser reasonably well. In addition, lessons learnt from modeling this challenge problem are presented.« less

Molecular simulations of carbohydrates and protein-carbohydrate interactions: motivation, issues and prospects.

PubMed

Fadda, Elisa; Woods, Robert J

2010-08-01

The characterization of the 3D structure of oligosaccharides, their conjugates and analogs is particularly challenging for traditional experimental methods. Molecular simulation methods provide a basis for interpreting sparse experimental data and for independently predicting conformational and dynamic properties of glycans. Here, we summarize and analyze the issues associated with modeling carbohydrates, with a detailed discussion of four of the most recently developed carbohydrate force fields, reviewed in terms of applicability to natural glycans, carbohydrate-protein complexes and the emerging area of glycomimetic drugs. In addition, we discuss prospectives and new applications of carbohydrate modeling in drug discovery.

A decision support model for investment on P2P lending platform.

PubMed

Zeng, Xiangxiang; Liu, Li; Leung, Stephen; Du, Jiangze; Wang, Xun; Li, Tao

2017-01-01

Peer-to-peer (P2P) lending, as a novel economic lending model, has triggered new challenges on making effective investment decisions. In a P2P lending platform, one lender can invest N loans and a loan may be accepted by M investors, thus forming a bipartite graph. Basing on the bipartite graph model, we built an iteration computation model to evaluate the unknown loans. To validate the proposed model, we perform extensive experiments on real-world data from the largest American P2P lending marketplace-Prosper. By comparing our experimental results with those obtained by Bayes and Logistic Regression, we show that our computation model can help borrowers select good loans and help lenders make good investment decisions. Experimental results also show that the Logistic classification model is a good complement to our iterative computation model, which motivates us to integrate the two classification models. The experimental results of the hybrid classification model demonstrate that the logistic classification model and our iteration computation model are complementary to each other. We conclude that the hybrid model (i.e., the integration of iterative computation model and Logistic classification model) is more efficient and stable than the individual model alone.

A decision support model for investment on P2P lending platform

PubMed Central

Liu, Li; Leung, Stephen; Du, Jiangze; Wang, Xun; Li, Tao

2017-01-01

Peer-to-peer (P2P) lending, as a novel economic lending model, has triggered new challenges on making effective investment decisions. In a P2P lending platform, one lender can invest N loans and a loan may be accepted by M investors, thus forming a bipartite graph. Basing on the bipartite graph model, we built an iteration computation model to evaluate the unknown loans. To validate the proposed model, we perform extensive experiments on real-world data from the largest American P2P lending marketplace—Prosper. By comparing our experimental results with those obtained by Bayes and Logistic Regression, we show that our computation model can help borrowers select good loans and help lenders make good investment decisions. Experimental results also show that the Logistic classification model is a good complement to our iterative computation model, which motivates us to integrate the two classification models. The experimental results of the hybrid classification model demonstrate that the logistic classification model and our iteration computation model are complementary to each other. We conclude that the hybrid model (i.e., the integration of iterative computation model and Logistic classification model) is more efficient and stable than the individual model alone. PMID:28877234

Scale Adaptive Simulation Model for the Darrieus Wind Turbine

NASA Astrophysics Data System (ADS)

Rogowski, K.; Hansen, M. O. L.; Maroński, R.; Lichota, P.

2016-09-01

Accurate prediction of aerodynamic loads for the Darrieus wind turbine using more or less complex aerodynamic models is still a challenge. One of the problems is the small amount of experimental data available to validate the numerical codes. The major objective of the present study is to examine the scale adaptive simulation (SAS) approach for performance analysis of a one-bladed Darrieus wind turbine working at a tip speed ratio of 5 and at a blade Reynolds number of 40 000. The three-dimensional incompressible unsteady Navier-Stokes equations are used. Numerical results of aerodynamic loads and wake velocity profiles behind the rotor are compared with experimental data taken from literature. The level of agreement between CFD and experimental results is reasonable.

Effects of a Body Image Challenge on Smoking Motivation Among College Females

PubMed Central

Lopez, Elena N.; Drobes, David J.; Thompson, J. Kevin; Brandon, Thomas H.

2014-01-01

Objective Previous correlational and quasi-experimental research has established that weight concerns and negative body image are associated with tobacco smoking, cessation, and relapse, particularly among young women. This study examined the causal influence of body image upon smoking motivation by merging methodologies from the addiction and body image literatures. Design Using a cue-reactivity paradigm, the study tested whether an experimental manipulation designed to challenge women’s body image—specifically, their weight dissatisfaction—influenced their motivation to smoke. Female college smokers (N = 62) were included in a 2 × 2 factorial, within-subjects design (body image cues X smoking cues). Main Outcome Measures Self-reported urge to smoke was the primary dependent measure, with skin conductance as a secondary measure. Results As hypothesized, the presentation of smoking images and thin model images produced greater urges to smoke than control images. Additionally, trait weight concerns moderated the effect of the body image manipulation such that those women with greater weight concerns produced greater craving to the thin model image (when smoking cues were not present). Conclusion These findings provide initial evidence that situational challenges to body image are causally related to smoking motivation. PMID:18979977

Aeroelasticity Benchmark Assessment: Subsonic Fixed Wing Program

NASA Technical Reports Server (NTRS)

Florance, Jennifer P.; Chwalowski, Pawel; Wieseman, Carol D.

2010-01-01

The fundamental technical challenge in computational aeroelasticity is the accurate prediction of unsteady aerodynamic phenomena and the effect on the aeroelastic response of a vehicle. Currently, a benchmarking standard for use in validating the accuracy of computational aeroelasticity codes does not exist. Many aeroelastic data sets have been obtained in wind-tunnel and flight testing throughout the world; however, none have been globally presented or accepted as an ideal data set. There are numerous reasons for this. One reason is that often, such aeroelastic data sets focus on the aeroelastic phenomena alone (flutter, for example) and do not contain associated information such as unsteady pressures and time-correlated structural dynamic deflections. Other available data sets focus solely on the unsteady pressures and do not address the aeroelastic phenomena. Other discrepancies can include omission of relevant data, such as flutter frequency and / or the acquisition of only qualitative deflection data. In addition to these content deficiencies, all of the available data sets present both experimental and computational technical challenges. Experimental issues include facility influences, nonlinearities beyond those being modeled, and data processing. From the computational perspective, technical challenges include modeling geometric complexities, coupling between the flow and the structure, grid issues, and boundary conditions. The Aeroelasticity Benchmark Assessment task seeks to examine the existing potential experimental data sets and ultimately choose the one that is viewed as the most suitable for computational benchmarking. An initial computational evaluation of that configuration will then be performed using the Langley-developed computational fluid dynamics (CFD) software FUN3D1 as part of its code validation process. In addition to the benchmarking activity, this task also includes an examination of future research directions. Researchers within the Aeroelasticity Branch will examine other experimental efforts within the Subsonic Fixed Wing (SFW) program (such as testing of the NASA Common Research Model (CRM)) and other NASA programs and assess aeroelasticity issues and research topics.

Population-reaction model and microbial experimental ecosystems for understanding hierarchical dynamics of ecosystems.

PubMed

Hosoda, Kazufumi; Tsuda, Soichiro; Kadowaki, Kohmei; Nakamura, Yutaka; Nakano, Tadashi; Ishii, Kojiro

2016-02-01

Understanding ecosystem dynamics is crucial as contemporary human societies face ecosystem degradation. One of the challenges that needs to be recognized is the complex hierarchical dynamics. Conventional dynamic models in ecology often represent only the population level and have yet to include the dynamics of the sub-organism level, which makes an ecosystem a complex adaptive system that shows characteristic behaviors such as resilience and regime shifts. The neglect of the sub-organism level in the conventional dynamic models would be because integrating multiple hierarchical levels makes the models unnecessarily complex unless supporting experimental data are present. Now that large amounts of molecular and ecological data are increasingly accessible in microbial experimental ecosystems, it is worthwhile to tackle the questions of their complex hierarchical dynamics. Here, we propose an approach that combines microbial experimental ecosystems and a hierarchical dynamic model named population-reaction model. We present a simple microbial experimental ecosystem as an example and show how the system can be analyzed by a population-reaction model. We also show that population-reaction models can be applied to various ecological concepts, such as predator-prey interactions, climate change, evolution, and stability of diversity. Our approach will reveal a path to the general understanding of various ecosystems and organisms. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Clinic expert information extraction based on domain model and block importance model.

PubMed

Zhang, Yuanpeng; Wang, Li; Qian, Danmin; Geng, Xingyun; Yao, Dengfu; Dong, Jiancheng

2015-11-01

To extract expert clinic information from the Deep Web, there are two challenges to face. The first one is to make a judgment on forms. A novel method based on a domain model, which is a tree structure constructed by the attributes of query interfaces is proposed. With this model, query interfaces can be classified to a domain and filled in with domain keywords. Another challenge is to extract information from response Web pages indexed by query interfaces. To filter the noisy information on a Web page, a block importance model is proposed, both content and spatial features are taken into account in this model. The experimental results indicate that the domain model yields a precision 4.89% higher than that of the rule-based method, whereas the block importance model yields an F1 measure 10.5% higher than that of the XPath method. Copyright © 2015 Elsevier Ltd. All rights reserved.

WaterTransport in PEM Fuel Cells: Advanced Modeling, Material Selection, Testing and Design Optimization

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

J. Vernon Cole; Abhra Roy; Ashok Damle

2012-10-02

Water management in Proton Exchange Membrane, PEM, Fuel Cells is challenging because of the inherent conflicts between the requirements for efficient low and high power operation. Particularly at low powers, adequate water must be supplied to sufficiently humidify the membrane or protons will not move through it adequately and resistance losses will decrease the cell efficiency. At high power density operation, more water is produced at the cathode than is necessary for membrane hydration. This excess water must be removed effectively or it will accumulate in the Gas Diffusion Layers, GDLs, between the gas channels and catalysts, blocking diffusion pathsmore » for reactants to reach the catalysts and potentially flooding the electrode. As power density of the cells is increased, the challenges arising from water management are expected to become more difficult to overcome simply due to the increased rate of liquid water generation relative to fuel cell volume. Thus, effectively addressing water management based issues is a key challenge in successful application of PEMFC systems. In this project, CFDRC and our partners used a combination of experimental characterization, controlled experimental studies of important processes governing how water moves through the fuel cell materials, and detailed models and simulations to improve understanding of water management in operating hydrogen PEM fuel cells. The characterization studies provided key data that is used as inputs to all state-of-the-art models for commercially important GDL materials. Experimental studies and microscopic scale models of how water moves through the GDLs showed that the water follows preferential paths, not branching like a river, as it moves toward the surface of the material. Experimental studies and detailed models of water and airflow in fuel cells channels demonstrated that such models can be used as an effective design tool to reduce operating pressure drop in the channels and the associated costs and weight of blowers and pumps to force air and hydrogen gas through the fuel cell. Promising improvements to materials structure and surface treatments that can potentially aid in managing the distribution and removal of liquid water were developed; and improved steady-state and freeze-thaw performance was demonstrated for a fuel cell stack under the self-humidified operating conditions that are promising for stationary power generation with reduced operating costs.« less

Constitutive equations for the cyclic behaviour of short carbon fibre-reinforced thermoplastics and identification on a uniaxial database

NASA Astrophysics Data System (ADS)

Leveuf, Louis; Navrátil, Libor; Le Saux, Vincent; Marco, Yann; Olhagaray, Jérôme; Leclercq, Sylvain

2018-01-01

A constitutive model for the cyclic behaviour of short carbon fibre-reinforced thermoplastics for aeronautical applications is proposed. First, an extended experimental database is generated in order to highlight the specificities of the studied material. This database is composed of complex tests and is used to design a relevant constitutive model able to capture the cyclic behaviour of the material. A general 3D formulation of the model is then proposed, and an identification strategy is defined to identify its parameters. Finally, a validation of the identification is performed by challenging the prediction of the model to the tests that were not used for the identification. An excellent agreement between the numerical results and the experimental data is observed revealing the capabilities of the model.

A potential method for lift evaluation from velocity field data

NASA Astrophysics Data System (ADS)

de Guyon-Crozier, Guillaume; Mulleners, Karen

2017-11-01

Computing forces from velocity field measurements is one of the challenges in experimental aerodynamics. This work focuses on low Reynolds flows, where the dynamics of the leading and trailing edge vortices play a major role in lift production. Recent developments in 2D potential flow theory, using discrete vortex models, have shown good results for unsteady wing motions. A method is presented to calculate lift from experimental velocity field data using a discrete vortex potential flow model. The model continuously adds new point vortices at leading and trailing edges whose circulations are set directly from vorticity measurements. Forces are computed using the unsteady Blasius equation and compared with measured loads.

Comparison of Plasmodium berghei challenge models for the evaluation of pre-erythrocytic malaria vaccines and their effect on perceived vaccine efficacy.

PubMed

Leitner, Wolfgang W; Bergmann-Leitner, Elke S; Angov, Evelina

2010-05-27

The immunological mechanisms responsible for protection against malaria infection vary among Plasmodium species, host species and the developmental stage of parasite, and are poorly understood. A challenge with live parasites is the most relevant approach to testing the efficacy of experimental malaria vaccines. Nevertheless, in the mouse models of Plasmodium berghei and Plasmodium yoelii, parasites are usually delivered by intravenous injection. This route is highly artificial and particularly in the P. berghei model produces inconsistent challenge results. The initial objective of this study was to compare an optimized intravenous (IV) delivery challenge model with an optimized single infectious mosquito bite challenge model. Finding shortcomings of both approaches, an alternative approach was explored, i.e., the subcutaneous challenge. Mice were infected with P. berghei sporozoites by intravenous (tail vein) injection, single mosquito bite, or subcutaneous injection of isolated parasites into the subcutaneous pouch at the base of the hind leg. Infection was determined in blood smears 7 and 14 days later. To determine the usefulness of challenge models for vaccine testing, mice were immunized with circumsporozoite-based DNA vaccines by gene gun. Despite modifications that allowed infection with a much smaller than reported number of parasites, the IV challenge remained insufficiently reliable and reproducible. Variations in the virulence of the inoculum, if not properly monitored by the rigorous inclusion of sporozoite titration curves in each experiment, can lead to unacceptable variations in reported vaccine efficacies. In contrast, mice with different genetic backgrounds were consistently infected by a single mosquito bite, without overwhelming vaccine-induced protective immune responses. Because of the logistical challenges associated with the mosquito bite model, the subcutaneous challenge route was optimized. This approach, too, yields reliable challenge results, albeit requiring a relatively large inoculum. Although a single bite by P. berghei infected Anopheles mosquitoes was superior to the IV challenge route, it is laborious. However, any conclusive evaluation of a pre-erythrocytic malaria vaccine candidate should require challenge through the natural anatomic target site of the parasite, the skin. The subcutaneous injection of isolated parasites represents an attractive compromise. Similar to the mosquito bite model, it allows vaccine-induced antibodies to exert their effect and is, therefore not as prone to the artifacts of the IV challenge.

A Combined Experimental and Computational Approach to Subject-Specific Analysis of Knee Joint Laxity

PubMed Central

Harris, Michael D.; Cyr, Adam J.; Ali, Azhar A.; Fitzpatrick, Clare K.; Rullkoetter, Paul J.; Maletsky, Lorin P.; Shelburne, Kevin B.

2016-01-01

Modeling complex knee biomechanics is a continual challenge, which has resulted in many models of varying levels of quality, complexity, and validation. Beyond modeling healthy knees, accurately mimicking pathologic knee mechanics, such as after cruciate rupture or meniscectomy, is difficult. Experimental tests of knee laxity can provide important information about ligament engagement and overall contributions to knee stability for development of subject-specific models to accurately simulate knee motion and loading. Our objective was to provide combined experimental tests and finite-element (FE) models of natural knee laxity that are subject-specific, have one-to-one experiment to model calibration, simulate ligament engagement in agreement with literature, and are adaptable for a variety of biomechanical investigations (e.g., cartilage contact, ligament strain, in vivo kinematics). Calibration involved perturbing ligament stiffness, initial ligament strain, and attachment location until model-predicted kinematics and ligament engagement matched experimental reports. Errors between model-predicted and experimental kinematics averaged <2 deg during varus–valgus (VV) rotations, <6 deg during internal–external (IE) rotations, and <3 mm of translation during anterior–posterior (AP) displacements. Engagement of the individual ligaments agreed with literature descriptions. These results demonstrate the ability of our constraint models to be customized for multiple individuals and simultaneously call attention to the need to verify that ligament engagement is in good general agreement with literature. To facilitate further investigations of subject-specific or population based knee joint biomechanics, data collected during the experimental and modeling phases of this study are available for download by the research community. PMID:27306137

Stereochemical analysis of (+)-limonene using theoretical and experimental NMR and chiroptical data

NASA Astrophysics Data System (ADS)

Reinscheid, F.; Reinscheid, U. M.

2016-02-01

Using limonene as test molecule, the success and the limitations of three chiroptical methods (optical rotatory dispersion (ORD), electronic and vibrational circular dichroism, ECD and VCD) could be demonstrated. At quite low levels of theory (mpw1pw91/cc-pvdz, IEFPCM (integral equation formalism polarizable continuum model)) the experimental ORD values differ by less than 10 units from the calculated values. The modelling in the condensed phase still represents a challenge so that experimental NMR data were used to test for aggregation and solvent-solute interactions. After establishing a reasonable structural model, only the ECD spectra prediction showed a decisive dependence on the basis set: only augmented (in the case of Dunning's basis sets) or diffuse (in the case of Pople's basis sets) basis sets predicted the position and shape of the ECD bands correctly. Based on these result we propose a procedure to assign the absolute configuration (AC) of an unknown compound using the comparison between experimental and calculated chiroptical data.

Incorporating neurophysiological concepts in mathematical thermoregulation models

NASA Astrophysics Data System (ADS)

Kingma, Boris R. M.; Vosselman, M. J.; Frijns, A. J. H.; van Steenhoven, A. A.; van Marken Lichtenbelt, W. D.

2014-01-01

Skin blood flow (SBF) is a key player in human thermoregulation during mild thermal challenges. Various numerical models of SBF regulation exist. However, none explicitly incorporates the neurophysiology of thermal reception. This study tested a new SBF model that is in line with experimental data on thermal reception and the neurophysiological pathways involved in thermoregulatory SBF control. Additionally, a numerical thermoregulation model was used as a platform to test the function of the neurophysiological SBF model for skin temperature simulation. The prediction-error of the SBF-model was quantified by root-mean-squared-residual (RMSR) between simulations and experimental measurement data. Measurement data consisted of SBF (abdomen, forearm, hand), core and skin temperature recordings of young males during three transient thermal challenges (1 development and 2 validation). Additionally, ThermoSEM, a thermoregulation model, was used to simulate body temperatures using the new neurophysiological SBF-model. The RMSR between simulated and measured mean skin temperature was used to validate the model. The neurophysiological model predicted SBF with an accuracy of RMSR < 0.27. Tskin simulation results were within 0.37 °C of the measured mean skin temperature. This study shows that (1) thermal reception and neurophysiological pathways involved in thermoregulatory SBF control can be captured in a mathematical model, and (2) human thermoregulation models can be equipped with SBF control functions that are based on neurophysiology without loss of performance. The neurophysiological approach in modelling thermoregulation is favourable over engineering approaches because it is more in line with the underlying physiology.

From Numerical Problem Solving to Model-Based Experimentation Incorporating Computer-Based Tools of Various Scales into the ChE Curriculum

ERIC Educational Resources Information Center

Shacham, Mordechai; Cutlip, Michael B.; Brauner, Neima

2009-01-01

A continuing challenge to the undergraduate chemical engineering curriculum is the time-effective incorporation and use of computer-based tools throughout the educational program. Computing skills in academia and industry require some proficiency in programming and effective use of software packages for solving 1) single-model, single-algorithm…

Experimental liver fibrosis research: update on animal models, legal issues and translational aspects

PubMed Central

2013-01-01

Liver fibrosis is defined as excessive extracellular matrix deposition and is based on complex interactions between matrix-producing hepatic stellate cells and an abundance of liver-resident and infiltrating cells. Investigation of these processes requires in vitro and in vivo experimental work in animals. However, the use of animals in translational research will be increasingly challenged, at least in countries of the European Union, because of the adoption of new animal welfare rules in 2013. These rules will create an urgent need for optimized standard operating procedures regarding animal experimentation and improved international communication in the liver fibrosis community. This review gives an update on current animal models, techniques and underlying pathomechanisms with the aim of fostering a critical discussion of the limitations and potential of up-to-date animal experimentation. We discuss potential complications in experimental liver fibrosis and provide examples of how the findings of studies in which these models are used can be translated to human disease and therapy. In this review, we want to motivate the international community to design more standardized animal models which might help to address the legally requested replacement, refinement and reduction of animals in fibrosis research. PMID:24274743

Current Challenges in the First Principle Quantitative Modelling of the Lower Hybrid Current Drive in Tokamaks

NASA Astrophysics Data System (ADS)

Peysson, Y.; Bonoli, P. T.; Chen, J.; Garofalo, A.; Hillairet, J.; Li, M.; Qian, J.; Shiraiwa, S.; Decker, J.; Ding, B. J.; Ekedahl, A.; Goniche, M.; Zhai, X.

2017-10-01

The Lower Hybrid (LH) wave is widely used in existing tokamaks for tailoring current density profile or extending pulse duration to steady-state regimes. Its high efficiency makes it particularly attractive for a fusion reactor, leading to consider it for this purpose in ITER tokamak. Nevertheless, if basics of the LH wave in tokamak plasma are well known, quantitative modeling of experimental observations based on first principles remains a highly challenging exercise, despite considerable numerical efforts achieved so far. In this context, a rigorous methodology must be carried out in the simulations to identify the minimum number of physical mechanisms that must be considered to reproduce experimental shot to shot observations and also scalings (density, power spectrum). Based on recent simulations carried out for EAST, Alcator C-Mod and Tore Supra tokamaks, the state of the art in LH modeling is reviewed. The capability of fast electron bremsstrahlung, internal inductance li and LH driven current at zero loop voltage to constrain all together LH simulations is discussed, as well as the needs of further improvements (diagnostics, codes, LH model), for robust interpretative and predictive simulations.

Recovery of microbial communities and carbon cycling processes following drought manipulation in southern California

NASA Astrophysics Data System (ADS)

Allison, S. D.; Martiny, J. B. H.; Martiny, A.; Berlemont, R.; Treseder, K. K.; Goulden, M.; Brodie, E.

2016-12-01

Predicting the functioning of microbial communities under changing environmental conditions remains a key challenge in Earth system science. Metagenomics and other high-throughput molecular approaches can help address this challenge by revealing the functional potential of microbial communities. We coupled metagenomics with models and experimental manipulations to address microbial responses to drought in a California grassland ecosystem along with the consequences for carbon cycling. We developed an approach for extracting trait information from metagenomic data and asked: 1) What is the phylogenetic structure of drought response traits? 2) What is the relationship between these traits and those involved in carbohydrate degradation? 3) How do both classes of traits vary seasonally and with precipitation manipulation? 4) How resilient are these traits in the face of perturbation? We found that drought response traits are phylogenetically conserved at an equivalent of 5-8% ribosomal RNA gene sequence dissimilarity. Experimental drought treatment selected for the genetic potential to degrade starch, xylan, and mixed polysaccharides, suggesting a link between drought response and carbon cycling traits. In addition, microbial communities exposed to experimental drought showed a reduced potential to degrade plant biomass. Particularly among bacteria, seasonal drought had a larger impact on microbial composition, abundance, and carbohydrate-degrading genes compared to experimental drought. Bacterial communities were also more resilient to drought perturbation than fungal communities, which showed legacies of drought perturbation for up to three years. Altogether, these findings imply that microbial communities exhibit trait diversity that facilitates resilience but with substantial time lags and consequences for carbon turnover. This information is being used to inform new trait-based models that address the challenge of predicting microbial functioning under precipitation change.

Particle bed reactor modeling

NASA Technical Reports Server (NTRS)

Sapyta, Joe; Reid, Hank; Walton, Lew

1993-01-01

The topics are presented in viewgraph form and include the following: particle bed reactor (PBR) core cross section; PBR bleed cycle; fuel and moderator flow paths; PBR modeling requirements; characteristics of PBR and nuclear thermal propulsion (NTP) modeling; challenges for PBR and NTP modeling; thermal hydraulic computer codes; capabilities for PBR/reactor application; thermal/hydralic codes; limitations; physical correlations; comparison of predicted friction factor and experimental data; frit pressure drop testing; cold frit mask factor; decay heat flow rate; startup transient simulation; and philosophy of systems modeling.

Extreme-Scale Bayesian Inference for Uncertainty Quantification of Complex Simulations

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

Biros, George

Uncertainty quantification (UQ)—that is, quantifying uncertainties in complex mathematical models and their large-scale computational implementations—is widely viewed as one of the outstanding challenges facing the field of CS&E over the coming decade. The EUREKA project set to address the most difficult class of UQ problems: those for which both the underlying PDE model as well as the uncertain parameters are of extreme scale. In the project we worked on these extreme-scale challenges in the following four areas: 1. Scalable parallel algorithms for sampling and characterizing the posterior distribution that exploit the structure of the underlying PDEs and parameter-to-observable map. Thesemore » include structure-exploiting versions of the randomized maximum likelihood method, which aims to overcome the intractability of employing conventional MCMC methods for solving extreme-scale Bayesian inversion problems by appealing to and adapting ideas from large-scale PDE-constrained optimization, which have been very successful at exploring high-dimensional spaces. 2. Scalable parallel algorithms for construction of prior and likelihood functions based on learning methods and non-parametric density estimation. Constructing problem-specific priors remains a critical challenge in Bayesian inference, and more so in high dimensions. Another challenge is construction of likelihood functions that capture unmodeled couplings between observations and parameters. We will create parallel algorithms for non-parametric density estimation using high dimensional N-body methods and combine them with supervised learning techniques for the construction of priors and likelihood functions. 3. Bayesian inadequacy models, which augment physics models with stochastic models that represent their imperfections. The success of the Bayesian inference framework depends on the ability to represent the uncertainty due to imperfections of the mathematical model of the phenomena of interest. This is a central challenge in UQ, especially for large-scale models. We propose to develop the mathematical tools to address these challenges in the context of extreme-scale problems. 4. Parallel scalable algorithms for Bayesian optimal experimental design (OED). Bayesian inversion yields quantified uncertainties in the model parameters, which can be propagated forward through the model to yield uncertainty in outputs of interest. This opens the way for designing new experiments to reduce the uncertainties in the model parameters and model predictions. Such experimental design problems have been intractable for large-scale problems using conventional methods; we will create OED algorithms that exploit the structure of the PDE model and the parameter-to-output map to overcome these challenges. Parallel algorithms for these four problems were created, analyzed, prototyped, implemented, tuned, and scaled up for leading-edge supercomputers, including UT-Austin’s own 10 petaflops Stampede system, ANL’s Mira system, and ORNL’s Titan system. While our focus is on fundamental mathematical/computational methods and algorithms, we will assess our methods on model problems derived from several DOE mission applications, including multiscale mechanics and ice sheet dynamics.« less

Estimation and uncertainty analysis of dose response in an inter-laboratory experiment

NASA Astrophysics Data System (ADS)

Toman, Blaza; Rösslein, Matthias; Elliott, John T.; Petersen, Elijah J.

2016-02-01

An inter-laboratory experiment for the evaluation of toxic effects of NH2-polystyrene nanoparticles on living human cancer cells was performed with five participating laboratories. Previously published results from nanocytoxicity assays are often contradictory, mostly due to challenges related to producing a reliable cytotoxicity assay protocol for use with nanomaterials. Specific challenges include reproducibility preparing nanoparticle dispersions, biological variability from testing living cell lines, and the potential for nano-related interference effects. In this experiment, such challenges were addressed by developing a detailed experimental protocol and using a specially designed 96-well plate layout which incorporated a range of control measurements to assess multiple factors such as nanomaterial interference, pipetting accuracy, cell seeding density, and instrument performance. Detailed data analysis of these control measurements showed that good control of the experiments was attained by all participants in most cases. The main measurement objective of the study was the estimation of a dose response relationship between concentration of the nanoparticles and metabolic activity of the living cells, under several experimental conditions. The dose curve estimation was achieved by imbedding a three parameter logistic curve in a three level Bayesian hierarchical model, accounting for uncertainty due to all known experimental conditions as well as between laboratory variability in a top-down manner. Computation was performed using Markov Chain Monte Carlo methods. The fit of the model was evaluated using Bayesian posterior predictive probabilities and found to be satisfactory.

A framework for testing and comparing binaural models.

PubMed

Dietz, Mathias; Lestang, Jean-Hugues; Majdak, Piotr; Stern, Richard M; Marquardt, Torsten; Ewert, Stephan D; Hartmann, William M; Goodman, Dan F M

2018-03-01

Auditory research has a rich history of combining experimental evidence with computational simulations of auditory processing in order to deepen our theoretical understanding of how sound is processed in the ears and in the brain. Despite significant progress in the amount of detail and breadth covered by auditory models, for many components of the auditory pathway there are still different model approaches that are often not equivalent but rather in conflict with each other. Similarly, some experimental studies yield conflicting results which has led to controversies. This can be best resolved by a systematic comparison of multiple experimental data sets and model approaches. Binaural processing is a prominent example of how the development of quantitative theories can advance our understanding of the phenomena, but there remain several unresolved questions for which competing model approaches exist. This article discusses a number of current unresolved or disputed issues in binaural modelling, as well as some of the significant challenges in comparing binaural models with each other and with the experimental data. We introduce an auditory model framework, which we believe can become a useful infrastructure for resolving some of the current controversies. It operates models over the same paradigms that are used experimentally. The core of the proposed framework is an interface that connects three components irrespective of their underlying programming language: The experiment software, an auditory pathway model, and task-dependent decision stages called artificial observers that provide the same output format as the test subject. Copyright © 2017 Elsevier B.V. All rights reserved.

Modeling and Simulation of Nanoindentation

NASA Astrophysics Data System (ADS)

Huang, Sixie; Zhou, Caizhi

2017-11-01

Nanoindentation is a hardness test method applied to small volumes of material which can provide some unique effects and spark many related research activities. To fully understand the phenomena observed during nanoindentation tests, modeling and simulation methods have been developed to predict the mechanical response of materials during nanoindentation. However, challenges remain with those computational approaches, because of their length scale, predictive capability, and accuracy. This article reviews recent progress and challenges for modeling and simulation of nanoindentation, including an overview of molecular dynamics, the quasicontinuum method, discrete dislocation dynamics, and the crystal plasticity finite element method, and discusses how to integrate multiscale modeling approaches seamlessly with experimental studies to understand the length-scale effects and microstructure evolution during nanoindentation tests, creating a unique opportunity to establish new calibration procedures for the nanoindentation technique.

Bayesian Models Leveraging Bioactivity and Cytotoxicity Information for Drug Discovery

PubMed Central

Ekins, Sean; Reynolds, Robert C.; Kim, Hiyun; Koo, Mi-Sun; Ekonomidis, Marilyn; Talaue, Meliza; Paget, Steve D.; Woolhiser, Lisa K.; Lenaerts, Anne J.; Bunin, Barry A.; Connell, Nancy; Freundlich, Joel S.

2013-01-01

SUMMARY Identification of unique leads represents a significant challenge in drug discovery. This hurdle is magnified in neglected diseases such as tuberculosis. We have leveraged public high-throughput screening (HTS) data, to experimentally validate virtual screening approach employing Bayesian models built with bioactivity information (single-event model) as well as bioactivity and cytotoxicity information (dual-event model). We virtually screen a commercial library and experimentally confirm actives with hit rates exceeding typical HTS results by 1-2 orders of magnitude. The first dual-event Bayesian model identified compounds with antitubercular whole-cell activity and low mammalian cell cytotoxicity from a published set of antimalarials. The most potent hit exhibits the in vitro activity and in vitro/in vivo safety profile of a drug lead. These Bayesian models offer significant economies in time and cost to drug discovery. PMID:23521795

Experimental porcine cysticercosis using infected beetles with Taenia solium eggs.

PubMed

Gomez-Puerta, Luis A; Garcia, Hector H; Gonzalez, Armando E

2018-07-01

Beetles are intermediate hosts for human and animal parasites, and several beetle species have been shown to carry Taenia eggs. An experimental porcine cysticercosis infection model was developed using beetles (Ammophorus rubripes) infected with Taenia solium eggs and then using these beetles for oral pig challenge. A total of 18 three months-old Landrace pigs were divided in four groups. Pigs from groups 1, 2, and 3 (n = 6 pigs per group) were challenged with one, three, and six beetles infected with T. solium eggs, containing approximately 52, 156 or 312 eggs respectively. Pigs were necropsied 12 weeks after infection to assess the presence of T. solium metacestode. Porcine cysticercosis by T. solium was produced in 17 out of 18 pigs (94.4%) challenged with infected beetles, all infected pigs had viable cysts. Only one pig from group 1 was negative to the presence of cysts. The median number of metacestodes per pig in groups 1, 2, and 3 were 2 (range 0-71), 26 (range 5-33) and 40 cysts (range 4-111), respectively. Experimental porcine cysticercosis infection is consistently obtained using beetles as mechanical vectors for T. solium eggs. Copyright © 2018 Elsevier B.V. All rights reserved.

Facilitating the Critique of Racism and Classism: An Experimental Model for Euro-American Middle-Class Students.

ERIC Educational Resources Information Center

Cohen, Lorraine

1995-01-01

Maintains that, during the 1980s, it was difficult to find classroom approaches that effectively challenged racial and class stereotypes. Describes a college community service project designed to teach students about racial, social, and gender discrimination. (CFR)

Computational micromechanics of fatigue of microstructures in the HCF–VHCF regimes

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

Castelluccio, Gustavo M.; Musinski, William D.; McDowell, David L.

Advances in higher resolution experimental techniques have shown that metallic materials can develop fatigue cracks under cyclic loading levels significantly below the yield stress. Indeed, the traditional notion of a fatigue limit can be recast in terms of limits associated with nucleation and arrest of fatigue cracks at the microstructural scale. Though fatigue damage characteristically emerges from irreversible dislocation processes at sub-grain scales, the specific microstructure attributes, environment, and loading conditions can strongly affect the apparent failure mode and surface to subsurface transitions. This paper discusses multiple mechanisms that occur during fatigue loading in the high cycle fatigue (HCF) tomore » very high cycle fatigue (VHCF) regimes. We compare these regimes, focusing on strategies to bridge experimental and modeling approaches exercised at multiple length scales and discussing particular challenges to modeling and simulation regarding microstructure-sensitive fatigue driving forces and thresholds. Finally, we discuss some of the challenges in predicting the transition of failure mechanisms at different stress and strain amplitudes.« less

Computational micromechanics of fatigue of microstructures in the HCF–VHCF regimes

DOE PAGES

Castelluccio, Gustavo M.; Musinski, William D.; McDowell, David L.

2016-05-19

Advances in higher resolution experimental techniques have shown that metallic materials can develop fatigue cracks under cyclic loading levels significantly below the yield stress. Indeed, the traditional notion of a fatigue limit can be recast in terms of limits associated with nucleation and arrest of fatigue cracks at the microstructural scale. Though fatigue damage characteristically emerges from irreversible dislocation processes at sub-grain scales, the specific microstructure attributes, environment, and loading conditions can strongly affect the apparent failure mode and surface to subsurface transitions. This paper discusses multiple mechanisms that occur during fatigue loading in the high cycle fatigue (HCF) tomore » very high cycle fatigue (VHCF) regimes. We compare these regimes, focusing on strategies to bridge experimental and modeling approaches exercised at multiple length scales and discussing particular challenges to modeling and simulation regarding microstructure-sensitive fatigue driving forces and thresholds. Finally, we discuss some of the challenges in predicting the transition of failure mechanisms at different stress and strain amplitudes.« less

Modeling and Characterization of Cyclic Shape Memory Behaviors of the Binary Ni49.9Ti50.1 Material System

NASA Astrophysics Data System (ADS)

Saleeb, A. F.; Natsheh, S. H.; Owusu-Danquah, J. S.; Dhakal, B.

2017-05-01

In this work, we address two of the main challenges encountered in constitutive modeling of the thermomechanical behaviors of actuation-based shape memory alloys. Firstly, the complexity of behavior under cyclic thermomechanical loading is properly handled, particularly with regard to assessing the long-term dimensional stability. Secondly, we consider the marked differences in behavior distinguishing virgin-versus-trained SMA material. To this end, we utilize a set of experimental data comprehensive in scope to cover all the anticipated operational conditions for one and same SMA alloy, having a specific chemical composition with fixed heat treatment. More specifically, this includes twenty-four different tests from the recent SMA experimental literature for the Ni49.9Ti50.1 material having austenite finish temperature above 100 °C. Under all the different conditions investigated, the model results were found to be in very good agreement with the experimental measurements.

Bioreactor Technologies to Support Liver Function In Vitro

PubMed Central

Ebrahimkhani, Mohammad R; Neiman, Jaclyn A Shepard; Raredon, Micah Sam B; Hughes, David J; Griffith, Linda G

2014-01-01

Liver is a central nexus integrating metabolic and immunologic homeostasis in the human body, and the direct or indirect target of most molecular therapeutics. A wide spectrum of therapeutic and technological needs drive efforts to capture liver physiology and pathophysiology in vitro, ranging from prediction of metabolism and toxicity of small molecule drugs, to understanding off-target effects of proteins, nucleic acid therapies, and targeted therapeutics, to serving as disease models for drug development. Here we provide perspective on the evolving landscape of bioreactor-based models to meet old and new challenges in drug discovery and development, emphasizing design challenges in maintaining long-term liver-specific function and how emerging technologies in biomaterials and microdevices are providing new experimental models. PMID:24607703

Multiscale Mechanics of Articular Cartilage: Potentials and Challenges of Coupling Musculoskeletal, Joint, and Microscale Computational Models

PubMed Central

Halloran, J. P.; Sibole, S.; van Donkelaar, C. C.; van Turnhout, M. C.; Oomens, C. W. J.; Weiss, J. A.; Guilak, F.; Erdemir, A.

2012-01-01

Articular cartilage experiences significant mechanical loads during daily activities. Healthy cartilage provides the capacity for load bearing and regulates the mechanobiological processes for tissue development, maintenance, and repair. Experimental studies at multiple scales have provided a fundamental understanding of macroscopic mechanical function, evaluation of the micromechanical environment of chondrocytes, and the foundations for mechanobiological response. In addition, computational models of cartilage have offered a concise description of experimental data at many spatial levels under healthy and diseased conditions, and have served to generate hypotheses for the mechanical and biological function. Further, modeling and simulation provides a platform for predictive risk assessment, management of dysfunction, as well as a means to relate multiple spatial scales. Simulation-based investigation of cartilage comes with many challenges including both the computational burden and often insufficient availability of data for model development and validation. This review outlines recent modeling and simulation approaches to understand cartilage function from a mechanical systems perspective, and illustrates pathways to associate mechanics with biological function. Computational representations at single scales are provided from the body down to the microstructure, along with attempts to explore multiscale mechanisms of load sharing that dictate the mechanical environment of the cartilage and chondrocytes. PMID:22648577

Predicting the performance uncertainty of a 1-MW pilot-scale carbon capture system after hierarchical laboratory-scale calibration and validation

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

Xu, Zhijie; Lai, Canhai; Marcy, Peter William

2017-05-01

A challenging problem in designing pilot-scale carbon capture systems is to predict, with uncertainty, the adsorber performance and capture efficiency under various operating conditions where no direct experimental data exist. Motivated by this challenge, we previously proposed a hierarchical framework in which relevant parameters of physical models were sequentially calibrated from different laboratory-scale carbon capture unit (C2U) experiments. Specifically, three models of increasing complexity were identified based on the fundamental physical and chemical processes of the sorbent-based carbon capture technology. Results from the corresponding laboratory experiments were used to statistically calibrate the physical model parameters while quantifying some of theirmore » inherent uncertainty. The parameter distributions obtained from laboratory-scale C2U calibration runs are used in this study to facilitate prediction at a larger scale where no corresponding experimental results are available. In this paper, we first describe the multiphase reactive flow model for a sorbent-based 1-MW carbon capture system then analyze results from an ensemble of simulations with the upscaled model. The simulation results are used to quantify uncertainty regarding the design’s predicted efficiency in carbon capture. In particular, we determine the minimum gas flow rate necessary to achieve 90% capture efficiency with 95% confidence.« less

Biophysics of cadherin adhesion.

PubMed

Leckband, Deborah; Sivasankar, Sanjeevi

2012-01-01

Since the identification of cadherins and the publication of the first crystal structures, the mechanism of cadherin adhesion, and the underlying structural basis have been studied with a number of different experimental techniques, different classical cadherin subtypes, and cadherin fragments. Earlier studies based on biophysical measurements and structure determinations resulted in seemingly contradictory findings regarding cadherin adhesion. However, recent experimental data increasingly reveal parallels between structures, solution binding data, and adhesion-based biophysical measurements that are beginning to both reconcile apparent differences and generate a more comprehensive model of cadherin-mediated cell adhesion. This chapter summarizes the functional, structural, and biophysical findings relevant to cadherin junction assembly and adhesion. We emphasize emerging parallels between findings obtained with different experimental approaches. Although none of the current models accounts for all of the available experimental and structural data, this chapter discusses possible origins of apparent discrepancies, highlights remaining gaps in current knowledge, and proposes challenges for further study.

Modelling the dynamics and hazards of explosive eruptions: Where we are now, and confronting the next challenges (Sergey Soloviev Medal Lecture)

NASA Astrophysics Data System (ADS)

Neri, Augusto

2017-04-01

Understanding of explosive eruption dynamics and assessment of their hazards continue to represent challenging issues to the present-day volcanology community. This is largely due to the complex and diverse nature of the phenomena, and the variability and unpredictability of volcanic processes. Nevertheless, important and continuing progress has been made in the last few decades in understanding fundamental processes and in forecasting the occurrences of these phenomena, thanks to significant advances in field, experimental and theoretical modeling investigations. For over four decades, for example, volcanologists have made major progress in the description of the nature of explosive eruptions, considerably aided by the development, improvement, and application of physical-mathematical models. Integral steady-state homogeneous flow models were first used to investigate the different controlling mechanisms and to infer the genesis and evolution of the phenomena. Through continuous improvements and quantum-leap developments, a variety of transient, 3D, multiphase flow models of volcanic phenomena now can implement state-of-the-art formulations of the underlying physics, new-generation analytical and experimental data, as well as high-performance computational techniques. These numerical models have proved to be able to provide key insights in the understanding of the dynamics of explosive eruptions (e.g. convective plumes, collapsing columns, pyroclastic density currents, short-lived explosions, etc.), as well as to represent a valuable tool in the quantification of potential eruptive scenarios and associated hazards. Simplified models based on a reduction of the system complexity have been also proved useful, combined with Monte Carlo and statistical methods, to generate quantitative probabilistic hazard maps at different space and time scales, some including the quantification of important sources of uncertainty. Nevertheless, the development of physical models able to accurately replicate, within acceptable statistical uncertainty, the evolution of explosive eruptions remains a challenging goal still to be achieved. Testing of the developed models versus large-scale experimental data and well-measured real events, real-time assimilation of observational data to forecast the process nature and evolution, as well as the quantification of the uncertainties affecting our system and modelling representations appear key next steps to further progress volcanological research and its essential contribution to the mitigation of volcanic risk.

Experimental calibration procedures for rotating Lorentz-force flowmeters

DOE PAGES

Hvasta, M. G.; Slighton, N. T.; Kolemen, E.; ...

2017-07-14

Rotating Lorentz-force flowmeters are a novel and useful technology with a range of applications in a variety of different industries. However, calibrating these flowmeters can be challenging, time-consuming, and expensive. In this paper, simple calibration procedures for rotating Lorentz-force flowmeters are presented. These procedures eliminate the need for expensive equipment, numerical modeling, redundant flowmeters, and system down-time. Finally, the calibration processes are explained in a step-by-step manner and compared to experimental results.

Experimental calibration procedures for rotating Lorentz-force flowmeters

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

Hvasta, M. G.; Slighton, N. T.; Kolemen, E.

Rotating Lorentz-force flowmeters are a novel and useful technology with a range of applications in a variety of different industries. However, calibrating these flowmeters can be challenging, time-consuming, and expensive. In this paper, simple calibration procedures for rotating Lorentz-force flowmeters are presented. These procedures eliminate the need for expensive equipment, numerical modeling, redundant flowmeters, and system down-time. Finally, the calibration processes are explained in a step-by-step manner and compared to experimental results.

Membrane proteins structures: A review on computational modeling tools.

PubMed

Almeida, Jose G; Preto, Antonio J; Koukos, Panagiotis I; Bonvin, Alexandre M J J; Moreira, Irina S

2017-10-01

Membrane proteins (MPs) play diverse and important functions in living organisms. They constitute 20% to 30% of the known bacterial, archaean and eukaryotic organisms' genomes. In humans, their importance is emphasized as they represent 50% of all known drug targets. Nevertheless, experimental determination of their three-dimensional (3D) structure has proven to be both time consuming and rather expensive, which has led to the development of computational algorithms to complement the available experimental methods and provide valuable insights. This review highlights the importance of membrane proteins and how computational methods are capable of overcoming challenges associated with their experimental characterization. It covers various MP structural aspects, such as lipid interactions, allostery, and structure prediction, based on methods such as Molecular Dynamics (MD) and Machine-Learning (ML). Recent developments in algorithms, tools and hybrid approaches, together with the increase in both computational resources and the amount of available data have resulted in increasingly powerful and trustworthy approaches to model MPs. Even though MPs are elementary and important in nature, the determination of their 3D structure has proven to be a challenging endeavor. Computational methods provide a reliable alternative to experimental methods. In this review, we focus on computational techniques to determine the 3D structure of MP and characterize their binding interfaces. We also summarize the most relevant databases and software programs available for the study of MPs. Copyright © 2017 Elsevier B.V. All rights reserved.

Proton exchange membrane fuel cell model for aging predictions: Simulated equivalent active surface area loss and comparisons with durability tests

NASA Astrophysics Data System (ADS)

Robin, C.; Gérard, M.; Quinaud, M.; d'Arbigny, J.; Bultel, Y.

2016-09-01

The prediction of Proton Exchange Membrane Fuel Cell (PEMFC) lifetime is one of the major challenges to optimize both material properties and dynamic control of the fuel cell system. In this study, by a multiscale modeling approach, a mechanistic catalyst dissolution model is coupled to a dynamic PEMFC cell model to predict the performance loss of the PEMFC. Results are compared to two 2000-h experimental aging tests. More precisely, an original approach is introduced to estimate the loss of an equivalent active surface area during an aging test. Indeed, when the computed Electrochemical Catalyst Surface Area profile is fitted on the experimental measures from Cyclic Voltammetry, the computed performance loss of the PEMFC is underestimated. To be able to predict the performance loss measured by polarization curves during the aging test, an equivalent active surface area is obtained by a model inversion. This methodology enables to successfully find back the experimental cell voltage decay during time. The model parameters are fitted from the polarization curves so that they include the global degradation. Moreover, the model captures the aging heterogeneities along the surface of the cell observed experimentally. Finally, a second 2000-h durability test in dynamic operating conditions validates the approach.

Fast flexible modeling of RNA structure using internal coordinates.

PubMed

Flores, Samuel Coulbourn; Sherman, Michael A; Bruns, Christopher M; Eastman, Peter; Altman, Russ Biagio

2011-01-01

Modeling the structure and dynamics of large macromolecules remains a critical challenge. Molecular dynamics (MD) simulations are expensive because they model every atom independently, and are difficult to combine with experimentally derived knowledge. Assembly of molecules using fragments from libraries relies on the database of known structures and thus may not work for novel motifs. Coarse-grained modeling methods have yielded good results on large molecules but can suffer from difficulties in creating more detailed full atomic realizations. There is therefore a need for molecular modeling algorithms that remain chemically accurate and economical for large molecules, do not rely on fragment libraries, and can incorporate experimental information. RNABuilder works in the internal coordinate space of dihedral angles and thus has time requirements proportional to the number of moving parts rather than the number of atoms. It provides accurate physics-based response to applied forces, but also allows user-specified forces for incorporating experimental information. A particular strength of RNABuilder is that all Leontis-Westhof basepairs can be specified as primitives by the user to be satisfied during model construction. We apply RNABuilder to predict the structure of an RNA molecule with 160 bases from its secondary structure, as well as experimental information. Our model matches the known structure to 10.2 Angstroms RMSD and has low computational expense.

Comparing the Effects of Particulate Matter on the Ocular Surfaces of Normal Eyes and a Dry Eye Rat Model.

PubMed

Han, Ji Yun; Kang, Boram; Eom, Youngsub; Kim, Hyo Myung; Song, Jong Suk

2017-05-01

To compare the effect of exposure to particulate matter on the ocular surface of normal and experimental dry eye (EDE) rat models. Titanium dioxide (TiO2) nanoparticles were used as the particulate matter. Rats were divided into 4 groups: normal control group, TiO2 challenge group of the normal model, EDE control group, and TiO2 challenge group of the EDE model. After 24 hours, corneal clarity was compared and tear samples were collected for quantification of lactate dehydrogenase, MUC5AC, and tumor necrosis factor-α concentrations. The periorbital tissues were used to evaluate the inflammatory cell infiltration and detect apoptotic cells. The corneal clarity score was greater in the EDE model than in the normal model. The score increased after TiO2 challenge in each group compared with each control group (normal control vs. TiO2 challenge group, 0.0 ± 0.0 vs. 0.8 ± 0.6, P = 0.024; EDE control vs. TiO2 challenge group, 2.2 ± 0.6 vs. 3.8 ± 0.4, P = 0.026). The tear lactate dehydrogenase level and inflammatory cell infiltration on the ocular surface were higher in the EDE model than in the normal model. These measurements increased significantly in both normal and EDE models after TiO2 challenge. The tumor necrosis factor-α levels and terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling-positive cells were also higher in the EDE model than in the normal model. TiO2 nanoparticle exposure on the ocular surface had a more prominent effect in the EDE model than it did in the normal model. The ocular surface of dry eyes seems to be more vulnerable to fine dust of air pollution than that of normal eyes.

Toward a therapy for mitochondrial disease

PubMed Central

Viscomi, Carlo

2016-01-01

Mitochondrial disorders are a group of genetic diseases affecting the energy-converting process of oxidative phosphorylation. The extreme variability of symptoms, organ involvement, and clinical course represent a challenge to the development of effective therapeutic interventions. However, new possibilities have recently been emerging from studies in model organisms and awaiting verification in humans. I will discuss here the most promising experimental approaches and the challenges we face to translate them into the clinics. The current clinical trials will also be briefly reviewed. PMID:27911730

Climate change and evolutionary adaptation.

PubMed

Hoffmann, Ary A; Sgrò, Carla M

2011-02-24

Evolutionary adaptation can be rapid and potentially help species counter stressful conditions or realize ecological opportunities arising from climate change. The challenges are to understand when evolution will occur and to identify potential evolutionary winners as well as losers, such as species lacking adaptive capacity living near physiological limits. Evolutionary processes also need to be incorporated into management programmes designed to minimize biodiversity loss under rapid climate change. These challenges can be met through realistic models of evolutionary change linked to experimental data across a range of taxa.

The Implementation of Clay Modeling and Rat Dissection into the Human Anatomy and Physiology Curriculum of a Large Urban Community College

ERIC Educational Resources Information Center

Haspel, Carol; Motoike, Howard K.; Lenchner, Erez

2014-01-01

After a considerable amount of research and experimentation, cat dissection was replaced with rat dissection and clay modeling in the human anatomy and physiology laboratory curricula at La Guardia Community College (LAGCC), a large urban community college of the City University of New York (CUNY). This article describes the challenges faculty…

Refuting Data Aggregation Arguments and How the Instance-Based Learning Model Stands Criticism: A Reply to Hills and Hertwig (2012)

ERIC Educational Resources Information Center

Gonzalez, Cleotilde; Dutt, Varun

2012-01-01

Hills and Hertwig (2012) challenge the proposed similarity of the exploration-exploitation transitions found in Gonzalez and Dutt (2011) between the 2 experimental paradigms of decisions from experience (sampling and repeated-choice), which was predicted by an instance-based learning (IBL) model. The heart of their argument is that in the sampling…

Preface to the special volume on the second Sandia Fracture Challenge

DOE PAGES

Kramer, Sharlotte Lorraine Bolyard; Boyce, Brad

2016-01-01

In this study, ductile failure of structural metals is a pervasive issue for applications such as automotive manufacturing, transportation infrastructures, munitions and armor, and energy generation. Experimental investigation of all relevant failure scenarios is intractable, requiring reliance on computation models. Our confidence in model predictions rests on unbiased assessments of the entire predictive capability, including the mathematical formulation, numerical implementation, calibration, and execution.

The Limitations of Model-Based Experimental Design and Parameter Estimation in Sloppy Systems.

PubMed

White, Andrew; Tolman, Malachi; Thames, Howard D; Withers, Hubert Rodney; Mason, Kathy A; Transtrum, Mark K

2016-12-01

We explore the relationship among experimental design, parameter estimation, and systematic error in sloppy models. We show that the approximate nature of mathematical models poses challenges for experimental design in sloppy models. In many models of complex biological processes it is unknown what are the relevant physical mechanisms that must be included to explain system behaviors. As a consequence, models are often overly complex, with many practically unidentifiable parameters. Furthermore, which mechanisms are relevant/irrelevant vary among experiments. By selecting complementary experiments, experimental design may inadvertently make details that were ommitted from the model become relevant. When this occurs, the model will have a large systematic error and fail to give a good fit to the data. We use a simple hyper-model of model error to quantify a model's discrepancy and apply it to two models of complex biological processes (EGFR signaling and DNA repair) with optimally selected experiments. We find that although parameters may be accurately estimated, the discrepancy in the model renders it less predictive than it was in the sloppy regime where systematic error is small. We introduce the concept of a sloppy system-a sequence of models of increasing complexity that become sloppy in the limit of microscopic accuracy. We explore the limits of accurate parameter estimation in sloppy systems and argue that identifying underlying mechanisms controlling system behavior is better approached by considering a hierarchy of models of varying detail rather than focusing on parameter estimation in a single model.

Challenges for Preclinical Investigations of Human Biofield Modalities

PubMed Central

Gronowicz, Gloria; Bengston, William

2015-01-01

Preclinical models for studying the effects of the human biofield have great potential to advance our understanding of human biofield modalities, which include external qigong, Johrei, Reiki, therapeutic touch, healing touch, polarity therapy, pranic healing, and other practices. A short history of Western biofield studies using preclinical models is presented and demonstrates numerous and consistent examples of human biofields significantly affecting biological systems both in vitro and in vivo. Methodological issues arising from these studies and practical solutions in experimental design are presented. Important questions still left unanswered with preclinical models include variable reproducibility, dosing, intentionality of the practitioner, best preclinical systems, and mechanisms. Input from the biofield practitioners in the experimental design is critical to improving experimental outcomes; however, the development of standard criteria for uniformity of practice and for inclusion of multiple practitioners is needed. Research in human biofield studies involving preclinical models promises a better understanding of the mechanisms underlying the efficacy of biofield therapies and will be important in guiding clinical protocols and integrating treatments with conventional medical therapies. PMID:26665042

Network news: prime time for systems biology of the plant circadian clock.

PubMed

McClung, C Robertson; Gutiérrez, Rodrigo A

2010-12-01

Whole-transcriptome analyses have established that the plant circadian clock regulates virtually every plant biological process and most prominently hormonal and stress response pathways. Systems biology efforts have successfully modeled the plant central clock machinery and an iterative process of model refinement and experimental validation has contributed significantly to the current view of the central clock machinery. The challenge now is to connect this central clock to the output pathways for understanding how the plant circadian clock contributes to plant growth and fitness in a changing environment. Undoubtedly, systems approaches will be needed to integrate and model the vastly increased volume of experimental data in order to extract meaningful biological information. Thus, we have entered an era of systems modeling, experimental testing, and refinement. This approach, coupled with advances from the genetic and biochemical analyses of clock function, is accelerating our progress towards a comprehensive understanding of the plant circadian clock network. Copyright © 2010 Elsevier Ltd. All rights reserved.

Modeling defect cluster evolution in irradiated structural materials: Focus on comparing to high-resolution experimental characterization studies

DOE PAGES

Wirth, Brian D.; Hu, Xunxiang; Kohnert, Aaron; ...

2015-03-02

Exposure of metallic structural materials to irradiation environments results in significant microstructural evolution, property changes, and performance degradation, which limits the extended operation of current generation light water reactors and restricts the design of advanced fission and fusion reactors. Further, it is well recognized that these irradiation effects are a classic example of inherently multiscale phenomena and that the mix of radiation-induced features formed and the corresponding property degradation depend on a wide range of material and irradiation variables. This inherently multiscale evolution emphasizes the importance of closely integrating models with high-resolution experimental characterization of the evolving radiation-damaged microstructure. Lastly,more » this article provides a review of recent models of the defect microstructure evolution in irradiated body-centered cubic materials, which provide good agreement with experimental measurements, and presents some outstanding challenges, which will require coordinated high-resolution characterization and modeling to resolve.« less

Current challenges in fundamental physics

NASA Astrophysics Data System (ADS)

Egana Ugrinovic, Daniel

The discovery of the Higgs boson at the Large Hadron Collider completed the Standard Model of particle physics. The Standard Model is a remarkably successful theory of fundamental physics, but it suffers from severe problems. It does not provide an explanation for the origin or stability of the electroweak scale nor for the origin and structure of flavor and CP violation. It predicts vanishing neutrino masses, in disagreement with experimental observations. It also fails to explain the matter-antimatter asymmetry of the universe, and it does not provide a particle candidate for dark matter. In this thesis we provide experimentally testable solutions for most of these problems and we study their phenomenology.

Molecular simulations of carbohydrates and protein-carbohydrate interactions: motivation, issues and prospects

PubMed Central

Fadda, Elisa; Woods, Robert J.

2014-01-01

The characterization of the 3D structure of oligosaccharides, their conjugates and analogs is particularly challenging for traditional experimental methods. Molecular simulation methods provide a basis for interpreting sparse experimental data and for independently predicting conformational and dynamic properties of glycans. Here, we summarize and analyze the issues associated with modeling carbohydrates, with a detailed discussion of four of the most recently developed carbohydrate force fields, reviewed in terms of applicability to natural glycans, carbohydrate–protein complexes and the emerging area of glycomimetic drugs. In addition, we discuss prospectives and new applications of carbohydrate modeling in drug discovery. PMID:20594934

Propensity Score Estimation With Boosted Regression for Evaluating Causal Effects in Observational Studies

ERIC Educational Resources Information Center

McCaffrey, Daniel F.; Ridgeway, Greg; Morral, Andrew R.

2004-01-01

Causal effect modeling with naturalistic rather than experimental data is challenging. In observational studies participants in different treatment conditions may also differ on pretreatment characteristics that influence outcomes. Propensity score methods can theoretically eliminate these confounds for all observed covariates, but accurate…

Pore-scale and continuum simulations of solute transport micromodel benchmark experiments

DOE PAGES

Oostrom, M.; Mehmani, Y.; Romero-Gomez, P.; ...

2014-06-18

Four sets of nonreactive solute transport experiments were conducted with micromodels. Three experiments with one variable, i.e., flow velocity, grain diameter, pore-aspect ratio, and flow-focusing heterogeneity were in each set. The data sets were offered to pore-scale modeling groups to test their numerical simulators. Each set consisted of two learning experiments, for which our results were made available, and one challenge experiment, for which only the experimental description and base input parameters were provided. The experimental results showed a nonlinear dependence of the transverse dispersion coefficient on the Peclet number, a negligible effect of the pore-aspect ratio on transverse mixing,more » and considerably enhanced mixing due to flow focusing. Five pore-scale models and one continuum-scale model were used to simulate the experiments. Of the pore-scale models, two used a pore-network (PN) method, two others are based on a lattice Boltzmann (LB) approach, and one used a computational fluid dynamics (CFD) technique. Furthermore, we used the learning experiments, by the PN models, to modify the standard perfect mixing approach in pore bodies into approaches to simulate the observed incomplete mixing. The LB and CFD models used the learning experiments to appropriately discretize the spatial grid representations. For the continuum modeling, the required dispersivity input values were estimated based on published nonlinear relations between transverse dispersion coefficients and Peclet number. Comparisons between experimental and numerical results for the four challenge experiments show that all pore-scale models were all able to satisfactorily simulate the experiments. The continuum model underestimated the required dispersivity values, resulting in reduced dispersion. The PN models were able to complete the simulations in a few minutes, whereas the direct models, which account for the micromodel geometry and underlying flow and transport physics, needed up to several days on supercomputers to resolve the more complex problems.« less

Toxcast and the Use of Human Relevant In Vitro Exposures ...

EPA Pesticide Factsheets

The path for incorporating new approach methods and technologies into quantitative chemical risk assessment poses a diverse set of scientific challenges. These challenges include sufficient coverage of toxicological mechanisms to meaningfully interpret negative test results, development of increasingly relevant test systems, computational modeling to integrate experimental data, putting results in a dose and exposure context, characterizing uncertainty, and efficient validation of the test systems and computational models. The presentation will cover progress at the U.S. EPA in systematically addressing each of these challenges and delivering more human-relevant risk-based assessments. This abstract does not necessarily reflect U.S. EPA policy. Presentation at the British Toxicological Society Annual Congress on ToxCast and the Use of Human Relevant In Vitro Exposures: Incorporating high-throughput exposure and toxicity testing data for 21st century risk assessments .

The Limitations of Model-Based Experimental Design and Parameter Estimation in Sloppy Systems

PubMed Central

Tolman, Malachi; Thames, Howard D.; Mason, Kathy A.

2016-01-01

We explore the relationship among experimental design, parameter estimation, and systematic error in sloppy models. We show that the approximate nature of mathematical models poses challenges for experimental design in sloppy models. In many models of complex biological processes it is unknown what are the relevant physical mechanisms that must be included to explain system behaviors. As a consequence, models are often overly complex, with many practically unidentifiable parameters. Furthermore, which mechanisms are relevant/irrelevant vary among experiments. By selecting complementary experiments, experimental design may inadvertently make details that were ommitted from the model become relevant. When this occurs, the model will have a large systematic error and fail to give a good fit to the data. We use a simple hyper-model of model error to quantify a model’s discrepancy and apply it to two models of complex biological processes (EGFR signaling and DNA repair) with optimally selected experiments. We find that although parameters may be accurately estimated, the discrepancy in the model renders it less predictive than it was in the sloppy regime where systematic error is small. We introduce the concept of a sloppy system–a sequence of models of increasing complexity that become sloppy in the limit of microscopic accuracy. We explore the limits of accurate parameter estimation in sloppy systems and argue that identifying underlying mechanisms controlling system behavior is better approached by considering a hierarchy of models of varying detail rather than focusing on parameter estimation in a single model. PMID:27923060

What do we learn about development from baby robots?

PubMed

Oudeyer, Pierre-Yves

2017-01-01

Understanding infant development is one of the great scientific challenges of contemporary science. In addressing this challenge, robots have proven useful as they allow experimenters to model the developing brain and body and understand the processes by which new patterns emerge in sensorimotor, cognitive, and social domains. Robotics also complements traditional experimental methods in psychology and neuroscience, where only a few variables can be studied at the same time. Moreover, work with robots has enabled researchers to systematically explore the role of the body in shaping the development of skill. All told, this work has shed new light on development as a complex dynamical system. WIREs Cogn Sci 2017, 8:e1395. doi: 10.1002/wcs.1395 For further resources related to this article, please visit the WIREs website. © 2016 Wiley Periodicals, Inc.

Structural Model Tuning Capability in an Object-Oriented Multidisciplinary Design, Analysis, and Optimization Tool

NASA Technical Reports Server (NTRS)

Lung, Shun-fat; Pak, Chan-gi

2008-01-01

Updating the finite element model using measured data is a challenging problem in the area of structural dynamics. The model updating process requires not only satisfactory correlations between analytical and experimental results, but also the retention of dynamic properties of structures. Accurate rigid body dynamics are important for flight control system design and aeroelastic trim analysis. Minimizing the difference between analytical and experimental results is a type of optimization problem. In this research, a multidisciplinary design, analysis, and optimization (MDAO) tool is introduced to optimize the objective function and constraints such that the mass properties, the natural frequencies, and the mode shapes are matched to the target data as well as the mass matrix being orthogonalized.

Structural Model Tuning Capability in an Object-Oriented Multidisciplinary Design, Analysis, and Optimization Tool

NASA Technical Reports Server (NTRS)

Lung, Shun-fat; Pak, Chan-gi

2008-01-01

Updating the finite element model using measured data is a challenging problem in the area of structural dynamics. The model updating process requires not only satisfactory correlations between analytical and experimental results, but also the retention of dynamic properties of structures. Accurate rigid body dynamics are important for flight control system design and aeroelastic trim analysis. Minimizing the difference between analytical and experimental results is a type of optimization problem. In this research, a multidisciplinary design, analysis, and optimization [MDAO] tool is introduced to optimize the objective function and constraints such that the mass properties, the natural frequencies, and the mode shapes are matched to the target data as well as the mass matrix being orthogonalized.

A strain-mediated corrosion model for bioabsorbable metallic stents.

PubMed

Galvin, E; O'Brien, D; Cummins, C; Mac Donald, B J; Lally, C

2017-06-01

This paper presents a strain-mediated phenomenological corrosion model, based on the discrete finite element modelling method which was developed for use with the ANSYS Implicit finite element code. The corrosion model was calibrated from experimental data and used to simulate the corrosion performance of a WE43 magnesium alloy stent. The model was found to be capable of predicting the experimentally observed plastic strain-mediated mass loss profile. The non-linear plastic strain model, extrapolated from the experimental data, was also found to adequately capture the corrosion-induced reduction in the radial stiffness of the stent over time. The model developed will help direct future design efforts towards the minimisation of plastic strain during device manufacture, deployment and in-service, in order to reduce corrosion rates and prolong the mechanical integrity of magnesium devices. The need for corrosion models that explore the interaction of strain with corrosion damage has been recognised as one of the current challenges in degradable material modelling (Gastaldi et al., 2011). A finite element based plastic strain-mediated phenomenological corrosion model was developed in this work and was calibrated based on the results of the corrosion experiments. It was found to be capable of predicting the experimentally observed plastic strain-mediated mass loss profile and the corrosion-induced reduction in the radial stiffness of the stent over time. To the author's knowledge, the results presented here represent the first experimental calibration of a plastic strain-mediated corrosion model of a corroding magnesium stent. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

An Improved Swarm Optimization for Parameter Estimation and Biological Model Selection

PubMed Central

Abdullah, Afnizanfaizal; Deris, Safaai; Mohamad, Mohd Saberi; Anwar, Sohail

2013-01-01

One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This study is hoped to provide a new insight in developing more accurate and reliable biological models based on limited and low quality experimental data. PMID:23593445

Modelling strategies to predict the multi-scale effects of rural land management change

NASA Astrophysics Data System (ADS)

Bulygina, N.; Ballard, C. E.; Jackson, B. M.; McIntyre, N.; Marshall, M.; Reynolds, B.; Wheater, H. S.

2011-12-01

Changes to the rural landscape due to agricultural land management are ubiquitous, yet predicting the multi-scale effects of land management change on hydrological response remains an important scientific challenge. Much empirical research has been of little generic value due to inadequate design and funding of monitoring programmes, while the modelling issues challenge the capability of data-based, conceptual and physics-based modelling approaches. In this paper we report on a major UK research programme, motivated by a national need to quantify effects of agricultural intensification on flood risk. Working with a consortium of farmers in upland Wales, a multi-scale experimental programme (from experimental plots to 2nd order catchments) was developed to address issues of upland agricultural intensification. This provided data support for a multi-scale modelling programme, in which highly detailed physics-based models were conditioned on the experimental data and used to explore effects of potential field-scale interventions. A meta-modelling strategy was developed to represent detailed modelling in a computationally-efficient manner for catchment-scale simulation; this allowed catchment-scale quantification of potential management options. For more general application to data-sparse areas, alternative approaches were needed. Physics-based models were developed for a range of upland management problems, including the restoration of drained peatlands, afforestation, and changing grazing practices. Their performance was explored using literature and surrogate data; although subject to high levels of uncertainty, important insights were obtained, of practical relevance to management decisions. In parallel, regionalised conceptual modelling was used to explore the potential of indices of catchment response, conditioned on readily-available catchment characteristics, to represent ungauged catchments subject to land management change. Although based in part on speculative relationships, significant predictive power was derived from this approach. Finally, using a formal Bayesian procedure, these different sources of information were combined with local flow data in a catchment-scale conceptual model application , i.e. using small-scale physical properties, regionalised signatures of flow and available flow measurements.

The Interaction of High-Speed Turbulence with Flames: Global Properties and Internal Flame Structure

DTIC Science & Technology

2009-09-28

S L, on all scales, including that of the laminar flame thickness, presents a number of both experimental and numerical challenges. Hereafter, we...fuel preconditioning, compression of the overall system, or propagation of large-scale shocks . Probing such regimes experimentally requires either...reactions are modeled using the first-order Arrhenius kinetics dY dt ≡ ẇ = −AρY exp ( − Q RT ) , (5) where A is the pre-exponential factor, Q is the

Biobehavioral Outcomes Following Psychological Interventions for Cancer Patients

PubMed Central

Andersen, Barbara L.

2007-01-01

Psychological interventions for adult cancer patients have primarily focused on reducing stress and enhancing quality of life. However, there has been expanded focus on biobehavioral outcomes—health behaviors, compliance, biologic responses, and disease outcomes—consistent with the Biobehavioral Model of cancer stress and disease course. The author reviewed this expanded focus in quasi-experimental and experimental studies of psychological interventions, provided methodologic detail, summarized findings, and highlighted novel contributions. A final section discussed methodologic issues, research directions, and challenges for the coming decade. PMID:12090371

OECD-NEA Expert Group on Multi-Physics Experimental Data, Benchmarks and Validation

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

Valentine, Timothy; Rohatgi, Upendra S.

High-fidelity, multi-physics modeling and simulation (M&S) tools are being developed and utilized for a variety of applications in nuclear science and technology and show great promise in their abilities to reproduce observed phenomena for many applications. Even with the increasing fidelity and sophistication of coupled multi-physics M&S tools, the underpinning models and data still need to be validated against experiments that may require a more complex array of validation data because of the great breadth of the time, energy and spatial domains of the physical phenomena that are being simulated. The Expert Group on Multi-Physics Experimental Data, Benchmarks and Validationmore » (MPEBV) of the Nuclear Energy Agency (NEA) of the Organization for Economic Cooperation and Development (OECD) was formed to address the challenges with the validation of such tools. The work of the MPEBV expert group is shared among three task forces to fulfill its mandate and specific exercises are being developed to demonstrate validation principles for common industrial challenges. This paper describes the overall mission of the group, the specific objectives of the task forces, the linkages among the task forces, and the development of a validation exercise that focuses on a specific reactor challenge problem.« less

Experimental Design for Stochastic Models of Nonlinear Signaling Pathways Using an Interval-Wise Linear Noise Approximation and State Estimation.

PubMed

Zimmer, Christoph

2016-01-01

Computational modeling is a key technique for analyzing models in systems biology. There are well established methods for the estimation of the kinetic parameters in models of ordinary differential equations (ODE). Experimental design techniques aim at devising experiments that maximize the information encoded in the data. For ODE models there are well established approaches for experimental design and even software tools. However, data from single cell experiments on signaling pathways in systems biology often shows intrinsic stochastic effects prompting the development of specialized methods. While simulation methods have been developed for decades and parameter estimation has been targeted for the last years, only very few articles focus on experimental design for stochastic models. The Fisher information matrix is the central measure for experimental design as it evaluates the information an experiment provides for parameter estimation. This article suggest an approach to calculate a Fisher information matrix for models containing intrinsic stochasticity and high nonlinearity. The approach makes use of a recently suggested multiple shooting for stochastic systems (MSS) objective function. The Fisher information matrix is calculated by evaluating pseudo data with the MSS technique. The performance of the approach is evaluated with simulation studies on an Immigration-Death, a Lotka-Volterra, and a Calcium oscillation model. The Calcium oscillation model is a particularly appropriate case study as it contains the challenges inherent to signaling pathways: high nonlinearity, intrinsic stochasticity, a qualitatively different behavior from an ODE solution, and partial observability. The computational speed of the MSS approach for the Fisher information matrix allows for an application in realistic size models.

Experimental infection of calves by two genetically-distinct strains of rift valley fever virus

USDA-ARS?s Scientific Manuscript database

Recent outbreaks of Rift Valley fever in ruminant livestock, characterized by mass abortion and high mortality rates in neonates, have raised international interest in improving vaccine control strategies. Previously we developed a reliable challenge model for sheep that improves the evaluation of ...

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

Animal models of protein allergenicity: potential benefits, pitfalls and challenges.

PubMed

Dearman, R J; Kimber, I

2009-04-01

Food allergy is an important health issue. With an increasing interest in novel foods derived from transgenic crop plants, there is a growing need for the development of approaches suitable for the characterization of the allergenic potential of proteins. There are methods available currently (such as homology searches and serological testing) that are very effective at identifying proteins that are likely to cross-react with known allergens. However, animal models may play a role in the identification of truly novel proteins, such as bacterial or fungal proteins, that have not been experienced previously in the diet. We consider here the potential benefits, pitfalls and challenges of the selection of various animal models, including the mouse, the rat, the dog and the neonatal swine. The advantages and disadvantages of various experimental end-points are discussed, including the measurement of specific IgE by ELISA, Western blotting or functional tests such as the passive cutaneous anaphylaxis assay, and the assessment of challenge-induced clinical symptoms in previously sensitized animals. The experimental variables of route of exposure to test proteins and the incorporation of adjuvant to increase the sensitivity of the responses are considered also. It is important to emphasize that currently none of these approaches has been validated for the purposes of hazard identification in the context of a safety assessment. However, the available evidence suggests that the judicious use of an accurate and robust animal model could provide important additional data that would contribute significantly to the assessment of the potential allergenicity of novel proteins.

High Speed Dynamics in Brittle Materials

NASA Astrophysics Data System (ADS)

Hiermaier, Stefan

2015-06-01

Brittle Materials under High Speed and Shock loading provide a continuous challenge in experimental physics, analysis and numerical modelling, and consequently for engineering design. The dependence of damage and fracture processes on material-inherent length and time scales, the influence of defects, rate-dependent material properties and inertia effects on different scales make their understanding a true multi-scale problem. In addition, it is not uncommon that materials show a transition from ductile to brittle behavior when the loading rate is increased. A particular case is spallation, a brittle tensile failure induced by the interaction of stress waves leading to a sudden change from compressive to tensile loading states that can be invoked in various materials. This contribution highlights typical phenomena occurring when brittle materials are exposed to high loading rates in applications such as blast and impact on protective structures, or meteorite impact on geological materials. A short review on experimental methods that are used for dynamic characterization of brittle materials will be given. A close interaction of experimental analysis and numerical simulation has turned out to be very helpful in analyzing experimental results. For this purpose, adequate numerical methods are required. Cohesive zone models are one possible method for the analysis of brittle failure as long as some degree of tension is present. Their recent successful application for meso-mechanical simulations of concrete in Hopkinson-type spallation tests provides new insight into the dynamic failure process. Failure under compressive loading is a particular challenge for numerical simulations as it involves crushing of material which in turn influences stress states in other parts of a structure. On a continuum scale, it can be modeled using more or less complex plasticity models combined with failure surfaces, as will be demonstrated for ceramics. Models which take microstructural cracking directly into account may provide a more physics-based approach for compressive failure in the future.

Modelling the complete operation of a free-piston shock tunnel for a low enthalpy condition

NASA Astrophysics Data System (ADS)

McGilvray, M.; Dann, A. G.; Jacobs, P. A.

2013-07-01

Only a limited number of free-stream flow properties can be measured in hypersonic impulse facilities at the nozzle exit. This poses challenges for experimenters when subsequently analysing experimental data obtained from these facilities. Typically in a reflected shock tunnel, a simple analysis that requires small amounts of computational resources is used to calculate quasi-steady gas properties. This simple analysis requires initial fill conditions and experimental measurements in analytical calculations of each major flow process, using forward coupling with minor corrections to include processes that are not directly modeled. However, this simplistic approach leads to an unknown level of discrepancy to the true flow properties. To explore the simple modelling techniques accuracy, this paper details the use of transient one and two-dimensional numerical simulations of a complete facility to obtain more refined free-stream flow properties from a free-piston reflected shock tunnel operating at low-enthalpy conditions. These calculations were verified by comparison to experimental data obtained from the facility. For the condition and facility investigated, the test conditions at nozzle exit produced with the simple modelling technique agree with the time and space averaged results from the complete facility calculations to within the accuracy of the experimental measurements.

Challenges in microbial ecology: building predictive understanding of community function and dynamics

PubMed Central

Widder, Stefanie; Allen, Rosalind J; Pfeiffer, Thomas; Curtis, Thomas P; Wiuf, Carsten; Sloan, William T; Cordero, Otto X; Brown, Sam P; Momeni, Babak; Shou, Wenying; Kettle, Helen; Flint, Harry J; Haas, Andreas F; Laroche, Béatrice; Kreft, Jan-Ulrich; Rainey, Paul B; Freilich, Shiri; Schuster, Stefan; Milferstedt, Kim; van der Meer, Jan R; Groβkopf, Tobias; Huisman, Jef; Free, Andrew; Picioreanu, Cristian; Quince, Christopher; Klapper, Isaac; Labarthe, Simon; Smets, Barth F; Wang, Harris; Soyer, Orkun S

2016-01-01

The importance of microbial communities (MCs) cannot be overstated. MCs underpin the biogeochemical cycles of the earth's soil, oceans and the atmosphere, and perform ecosystem functions that impact plants, animals and humans. Yet our ability to predict and manage the function of these highly complex, dynamically changing communities is limited. Building predictive models that link MC composition to function is a key emerging challenge in microbial ecology. Here, we argue that addressing this challenge requires close coordination of experimental data collection and method development with mathematical model building. We discuss specific examples where model–experiment integration has already resulted in important insights into MC function and structure. We also highlight key research questions that still demand better integration of experiments and models. We argue that such integration is needed to achieve significant progress in our understanding of MC dynamics and function, and we make specific practical suggestions as to how this could be achieved. PMID:27022995

Comparative safety, immunogenicity, and efficacy of several anti‐H5N1 influenza experimental vaccines in a mouse and chicken models (Testing of killed and live H5 vaccine)

PubMed Central

Gambaryan, Alexandra S.; Lomakina, Natalia F.; Boravleva, Elizaveta Y.; Kropotkina, Ekaterina A.; Mashin, Vadim V.; Krasilnikov, Igor V.; Klimov, Alexander I.; Rudenko, Larisa G.

2011-01-01

Please cite this paper as: Gambaryan et al. (2011) Comparative safety, immunogenicity, and efficacy of several anti‐H5N1 influenza experimental vaccines in a mouse and chicken models. Parallel testing of killed and live H5 vaccine. Influenza and Other Respiratory Viruses 6(3), 188–195. Objective  Parallel testing of inactivated (split and whole virion) and live vaccine was conducted to compare the immunogenicity and protective efficacy against homologous and heterosubtypic challenge by H5N1 highly pathogenic avian influenza virus. Method  Four experimental live vaccines based on two H5N1 influenza virus strains were tested; two of them had hemagglutinin (HA) of A/Vietnam/1203/04 strain lacking the polybasic HA cleavage site, and two others had hemagglutinins from attenuated H5N1 virus A/Chicken/Kurgan/3/05, with amino acid substitutions of Asp54/Asn and Lys222/Thr in HA1 and Val48/Ile and Lys131/Thr in HA2 while maintaining the polybasic HA cleavage site. The neuraminidase and non‐glycoprotein genes of the experimental live vaccines were from H2N2 cold‐adapted master strain A/Leningrad/134/17/57 (VN‐Len and Ku‐Len) or from the apathogenic H6N2 virus A/Gull/Moscow/3100/2006 (VN‐Gull and Ku‐Gull). Inactivated H5N1 and H1N1 and live H1N1 vaccine were used for comparison. All vaccines were applied in a single dose. Safety, immunogenicity, and protectivity against the challenge with HPAI H5N1 virus A/Chicken/Kurgan/3/05 were estimated. Results  All experimental live H5 vaccines tested were apathogenic as determined by weight loss and conferred more than 90% protection against lethal challenge with A/Chicken/Kurgan/3/05 infection. Inactivated H1N1 vaccine in mice offered no protection against challenge with H5N1 virus, while live cold‐adapted H1N1 vaccine reduced the mortality near to zero level. Conclusions  The high yield, safety, and protectivity of VN‐Len and Ku‐Len made them promising strains for the production of inactivated and live vaccines against H5N1 viruses. PMID:21951678

Tensor methods for parameter estimation and bifurcation analysis of stochastic reaction networks

PubMed Central

Liao, Shuohao; Vejchodský, Tomáš; Erban, Radek

2015-01-01

Stochastic modelling of gene regulatory networks provides an indispensable tool for understanding how random events at the molecular level influence cellular functions. A common challenge of stochastic models is to calibrate a large number of model parameters against the experimental data. Another difficulty is to study how the behaviour of a stochastic model depends on its parameters, i.e. whether a change in model parameters can lead to a significant qualitative change in model behaviour (bifurcation). In this paper, tensor-structured parametric analysis (TPA) is developed to address these computational challenges. It is based on recently proposed low-parametric tensor-structured representations of classical matrices and vectors. This approach enables simultaneous computation of the model properties for all parameter values within a parameter space. The TPA is illustrated by studying the parameter estimation, robustness, sensitivity and bifurcation structure in stochastic models of biochemical networks. A Matlab implementation of the TPA is available at http://www.stobifan.org. PMID:26063822

Tensor methods for parameter estimation and bifurcation analysis of stochastic reaction networks.

PubMed

Liao, Shuohao; Vejchodský, Tomáš; Erban, Radek

2015-07-06

Stochastic modelling of gene regulatory networks provides an indispensable tool for understanding how random events at the molecular level influence cellular functions. A common challenge of stochastic models is to calibrate a large number of model parameters against the experimental data. Another difficulty is to study how the behaviour of a stochastic model depends on its parameters, i.e. whether a change in model parameters can lead to a significant qualitative change in model behaviour (bifurcation). In this paper, tensor-structured parametric analysis (TPA) is developed to address these computational challenges. It is based on recently proposed low-parametric tensor-structured representations of classical matrices and vectors. This approach enables simultaneous computation of the model properties for all parameter values within a parameter space. The TPA is illustrated by studying the parameter estimation, robustness, sensitivity and bifurcation structure in stochastic models of biochemical networks. A Matlab implementation of the TPA is available at http://www.stobifan.org.

Comparison of Experimental Surface and Flow Field Measurements to Computational Results of the Juncture Flow Model

NASA Technical Reports Server (NTRS)

Roozeboom, Nettie H.; Lee, Henry C.; Simurda, Laura J.; Zilliac, Gregory G.; Pulliam, Thomas H.

2016-01-01

Wing-body juncture flow fields on commercial aircraft configurations are challenging to compute accurately. The NASA Advanced Air Vehicle Program's juncture flow committee is designing an experiment to provide data to improve Computational Fluid Dynamics (CFD) modeling in the juncture flow region. Preliminary design of the model was done using CFD, yet CFD tends to over-predict the separation in the juncture flow region. Risk reduction wind tunnel tests were requisitioned by the committee to obtain a better understanding of the flow characteristics of the designed models. NASA Ames Research Center's Fluid Mechanics Lab performed one of the risk reduction tests. The results of one case, accompanied by CFD simulations, are presented in this paper. Experimental results suggest the wall mounted wind tunnel model produces a thicker boundary layer on the fuselage than the CFD predictions, resulting in a larger wing horseshoe vortex suppressing the side of body separation in the juncture flow region. Compared to experimental results, CFD predicts a thinner boundary layer on the fuselage generates a weaker wing horseshoe vortex resulting in a larger side of body separation.

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

Smith, Jeremy C.; Cheng, Xiaolin; Nickels, Jonathan D.

Understanding of cell membrane organization has evolved significantly from the classic fluid mosaic model. It is now recognized that biological membranes are highly organized structures, with differences in lipid compositions between inner and outer leaflets and in lateral structures within the bilayer plane, known as lipid rafts. These organizing principles are important for protein localization and function as well as cellular signaling. However, the mechanisms and biophysical basis of lipid raft formation, structure, dynamics and function are not clearly understood. One key question, which we focus on in this review, is how lateral organization and leaflet compositional asymmetry are coupled.more » Detailed information elucidating this question has been sparse because of the small size and transient nature of rafts and the experimental challenges in constructing asymmetric bilayers. Resolving this mystery will require advances in both experimentation and modeling. We discuss here the preparation of model systems along with experimental and computational approaches that have been applied in efforts to address this key question in membrane biology. Furthermore, we seek to place recent and future advances in experimental and computational techniques in context, providing insight into in-plane and transverse organization of biological membranes.« less

The BCD of response time analysis in experimental economics.

PubMed

Spiliopoulos, Leonidas; Ortmann, Andreas

2018-01-01

For decisions in the wild, time is of the essence. Available decision time is often cut short through natural or artificial constraints, or is impinged upon by the opportunity cost of time. Experimental economists have only recently begun to conduct experiments with time constraints and to analyze response time (RT) data, in contrast to experimental psychologists. RT analysis has proven valuable for the identification of individual and strategic decision processes including identification of social preferences in the latter case, model comparison/selection, and the investigation of heuristics that combine speed and performance by exploiting environmental regularities. Here we focus on the benefits, challenges, and desiderata of RT analysis in strategic decision making. We argue that unlocking the potential of RT analysis requires the adoption of process-based models instead of outcome-based models, and discuss how RT in the wild can be captured by time-constrained experiments in the lab. We conclude that RT analysis holds considerable potential for experimental economics, deserves greater attention as a methodological tool, and promises important insights on strategic decision making in naturally occurring environments.

Experimental Phasing: Substructure Solution and Density Modification as Implemented in SHELX.

PubMed

Thorn, Andrea

2017-01-01

This chapter describes experimental phasing methods as implemented in SHELX. After introducing fundamental concepts underlying all experimental phasing approaches, the methods used by SHELXC/D/E are described in greater detail, such as dual-space direct methods, Patterson seeding and density modification with the sphere of influence algorithm. Intensity differences from data for experimental phasing can also be used for the generation and usage of difference maps with ANODE for validation and phasing purposes. A short section describes how molecular replacement can be combined with experimental phasing methods. The second half covers practical challenges, such as prerequisites for successful experimental phasing, evaluation of potential solutions, and what to do if substructure search or density modification fails. It is also shown how auto-tracing in SHELXE can improve automation and how it ties in with automatic model building after phasing.

Attenuation and Dispersion in Earth's Materials

NASA Astrophysics Data System (ADS)

Gueguen, Y.

2012-04-01

One of the last challenges of Pr. Luigi Burlini has been to set up an experimental apparatus that would measure elastic wave attenuation under high pressure conditions. This project has since been developed by his colleagues and students at ETH. As a tribute to Luigi Burlini, this presentation aims at recalling why such measurements are important , how challenging such a project is, and what the main issues ahead are. Most of our knowledge about either crustal layers (seismic exploration) or deeper layers (seismology) results from data related to elastic wave propagation inside the Earth. The large amount of available data as well as the huge capability of computers are such that descriptions in terms of isotropic homogeneous layers appear to be very crude today. Anisotropic, heterogeneous models are reported at various scales. In addition, accounting for wave attenuation (the Q factor) is potentially of great interest. The Q factor is highly sensitive to processes that involve some departure from perfect elasticity. Its knowledge may provide information on possible fluid content, temperature, etc. This is because various processes may dissipate energy (and thus lower Q value) as a result of fluid flow, solid flow, etc., depending on the precise P-T conditions at depth. This points immediately to the theoretical challenge of Q investigations: there are many possible ways for a rock to not behave as a perfect elastic body. To model these various mechanisms and identify in which conditions they can take place is a first major challenge. The second challenge is on the experimental ground. What is looked for is to get low frequencies (f close to seismic frequencies) Q data on crustal (or mantle) rocks at high pressure P-high temperature T. Experiments in such highT-high P-low f conditions are extremely difficult to perform. Only in Canberra (I. Jackson) and now in Zurich such conditions have been achieved. Attenuation and dispersion (frequency dependence) of elastic waves are related through Kramers-Kronig equations. Using simple viscoelastic models such as the Zener model, one can show that Q-1 is maximum at a critical frequency fc, and, correlatively, that the wavespeed increases from low to high f by an amount ?V/V = (Q-1)max. This means that another (equivalent) way to look at attenuation is to look at dispersion. Experimentally, this implies to measure high and low frequency wavespeeds or elastic moduli. High frequency measurements have been performed for a long time (including high P-high T conditions) but low frequency measurements remain a challenge. Such data are however of major importance: seismic velocities data (1 H-1 kHz range) are obtained at much lower frequencies than laboratory data (MHz range). A difference by up to 6 orders of magnitudes in frequency exist between both set of data. Yet it has been mainly assumed that the frequency dependence can be neglected. Several set of experimental data show that it is not true. The implications for the crust and for the mantle will be discussed.

Assessment and Challenges of Ligand Docking into Comparative Models of G-Protein Coupled Receptors

PubMed Central

Frimurer, Thomas M.; Meiler, Jens

2013-01-01

The rapidly increasing number of high-resolution X-ray structures of G-protein coupled receptors (GPCRs) creates a unique opportunity to employ comparative modeling and docking to provide valuable insight into the function and ligand binding determinants of novel receptors, to assist in virtual screening and to design and optimize drug candidates. However, low sequence identity between receptors, conformational flexibility, and chemical diversity of ligands present an enormous challenge to molecular modeling approaches. It is our hypothesis that rapid Monte-Carlo sampling of protein backbone and side-chain conformational space with Rosetta can be leveraged to meet this challenge. This study performs unbiased comparative modeling and docking methodologies using 14 distinct high-resolution GPCRs and proposes knowledge-based filtering methods for improvement of sampling performance and identification of correct ligand-receptor interactions. On average, top ranked receptor models built on template structures over 50% sequence identity are within 2.9 Å of the experimental structure, with an average root mean square deviation (RMSD) of 2.2 Å for the transmembrane region and 5 Å for the second extracellular loop. Furthermore, these models are consistently correlated with low Rosetta energy score. To predict their binding modes, ligand conformers of the 14 ligands co-crystalized with the GPCRs were docked against the top ranked comparative models. In contrast to the comparative models themselves, however, it remains difficult to unambiguously identify correct binding modes by score alone. On average, sampling performance was improved by 103 fold over random using knowledge-based and energy-based filters. In assessing the applicability of experimental constraints, we found that sampling performance is increased by one order of magnitude for every 10 residues known to contact the ligand. Additionally, in the case of DOR, knowledge of a single specific ligand-protein contact improved sampling efficiency 7 fold. These findings offer specific guidelines which may lead to increased success in determining receptor-ligand complexes. PMID:23844000

Experimental and theoretical assessment of the multi-domain flow behaviour in a waste body during leachate infiltration

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

Tinet, A-J., E-mail: tinet@ujf-grenoble.fr; Oxarango, L.; Centre for Research in Environmental, Coastal and Hydrological Engineering, School of Civil Engineering, Surveying and Construction, University of KwaZulu-Natal, Howard College Campus, Durban 4041

2011-08-15

The optimisation of landfill operation is a key challenge for the upcoming years. A promising solution to improve municipal solid waste (MSW) management is the bioreactor technology. A meso-scale (around 1 m{sup 3}) experimental set-up was performed to study the effect of moisture control in low density conditions with different leachate injection operations and bioreactor monitoring including the use of a neutron probe. The moisture content distribution evolution demonstrates a multi-domain flow behaviour. A classic van Genuchten-Mualem description of the connected porosity proved insufficient to correctly describe the observed phenomena. A bimodal description of the connected porosity is proposed asmore » solution and a connected/non-connected porosities numerical model was applied to the results. The model explains the experimental results reasonably well.« less

Snow Leopard Cloud: A Multi-national Education Training and Experimentation Cloud and Its Security Challenges

NASA Astrophysics Data System (ADS)

Cayirci, Erdal; Rong, Chunming; Huiskamp, Wim; Verkoelen, Cor

Military/civilian education training and experimentation networks (ETEN) are an important application area for the cloud computing concept. However, major security challenges have to be overcome to realize an ETEN. These challenges can be categorized as security challenges typical to any cloud and multi-level security challenges specific to an ETEN environment. The cloud approach for ETEN is introduced and its security challenges are explained in this paper.

Biofilm growth in porous media: Experiments, computational modeling at the porescale, and upscaling

NASA Astrophysics Data System (ADS)

Peszynska, Malgorzata; Trykozko, Anna; Iltis, Gabriel; Schlueter, Steffen; Wildenschild, Dorthe

2016-09-01

Biofilm growth changes many physical properties of porous media such as porosity, permeability and mass transport parameters. The growth depends on various environmental conditions, and in particular, on flow rates. Modeling the evolution of such properties is difficult both at the porescale where the phase morphology can be distinguished, as well as during upscaling to the corescale effective properties. Experimental data on biofilm growth is also limited because its collection can interfere with the growth, while imaging itself presents challenges. In this paper we combine insight from imaging, experiments, and numerical simulations and visualization. The experimental dataset is based on glass beads domain inoculated by biomass which is subjected to various flow conditions promoting the growth of biomass and the appearance of a biofilm phase. The domain is imaged and the imaging data is used directly by a computational model for flow and transport. The results of the computational flow model are upscaled to produce conductivities which compare well with the experimentally obtained hydraulic properties of the medium. The flow model is also coupled to a newly developed biomass-nutrient growth model, and the model reproduces morphologies qualitatively similar to those observed in the experiment.

The effect of a live vaccine on the horizontal transmission of Mycoplasma gallisepticum.

PubMed

Feberwee, A; Landman, W J M; von Banniseht-Wysmuller, Th; Klinkenberg, D; Vernooij, J C M; Gielkens, A L J; Stegeman, J A

2006-10-01

The effect of a live Mycoplasma gallisepticum vaccine on the horizontal transmission of this Mycoplasma species was quantified in an experimental animal transmission model in specific pathogen free White Layers. Two identical trials were performed, each consisting of two experimental groups and one control group. The experimental groups each consisted of 20 birds 21 weeks of age, which were housed following a pair-wise design. One group was vaccinated twice with a commercially available live attenuated M. gallisepticum vaccine, while the other group was not vaccinated. Each pair of the experimental group consisted of a challenged chicken (10(4) colony-forming units intratracheally) and a susceptible in-contact bird. The control group consisted of 10 twice-vaccinated birds housed in pairs and five individually housed non-vaccinated birds. The infection was monitored by serology, culture and quantitative polymerase chain reaction. The vaccine strain and the challenge strain were distinguished by a specific polymerase chain reaction and by random amplified polymorphic DNA analysis. In both experiments, all non-vaccinated challenged chickens and their in-contact 'partners' became infected with M. gallisepticum. In the vaccinated challenged and corresponding in-contact birds, a total of 19 and 13 chickens, respectively, became infected with M. gallisepticum. Analysis of the M. gallisepticum shedding patterns showed a significant effect of vaccination on the shedding levels of the vaccinated in-contact chickens. Moreover, the Cox Proportional Hazard analysis indicated that the rate of M. gallisepticum transmission from challenged to in-contact birds in the vaccinated group was 0.356 times that of the non-vaccinated group. In addition, the overall estimate of R (the average number of secondary cases infected by one typical infectious case) of the vaccinated group (R = 4.3, 95% confidence interval = 1.6 to 49.9) was significantly lower than that of the non-vaccinated group (R = infinity, 95% confidence interval = 9.9 to infinity). However, the overall estimate of R in the vaccinated group still exceeded 1, which indicates that the effect of the vaccination on the horizontal transmission M. gallisepticum is insufficient to stop its spread under these experimental conditions.

A combined-slip predictive control of vehicle stability with experimental verification

NASA Astrophysics Data System (ADS)

Jalali, Milad; Hashemi, Ehsan; Khajepour, Amir; Chen, Shih-ken; Litkouhi, Bakhtiar

2018-02-01

In this paper, a model predictive vehicle stability controller is designed based on a combined-slip LuGre tyre model. Variations in the lateral tyre forces due to changes in tyre slip ratios are considered in the prediction model of the controller. It is observed that the proposed combined-slip controller takes advantage of the more accurate tyre model and can adjust tyre slip ratios based on lateral forces of the front axle. This results in an interesting closed-loop response that challenges the notion of braking only the wheels on one side of the vehicle in differential braking. The performance of the proposed controller is evaluated in software simulations and is compared to a similar pure-slip controller. Furthermore, experimental tests are conducted on a rear-wheel drive electric Chevrolet Equinox equipped with differential brakes to evaluate the closed-loop response of the model predictive control controller.

Modeling Self-Heating Effects in Nanoscale Devices

NASA Astrophysics Data System (ADS)

Raleva, K.; Shaik, A. R.; Vasileska, D.; Goodnick, S. M.

2017-08-01

Accurate thermal modeling and the design of microelectronic devices and thin film structures at the micro- and nanoscales poses a challenge to electrical engineers who are less familiar with the basic concepts and ideas in sub-continuum heat transport. This book aims to bridge that gap. Efficient heat removal methods are necessary to increase device performance and device reliability. The authors provide readers with a combination of nanoscale experimental techniques and accurate modeling methods that must be employed in order to determine a device's temperature profile.

Natural and experimental Helicobacter mustelae reinfection following successful antimicrobial eradication in ferrets.

PubMed

Batchelder, M; Fox, J G; Hayward, A; Yan, L; Shames, B; Murphy, J C; Palley, L

1996-03-01

Recrudescence or reinfection may occur after eradication of Helicobacter pylori in humans. We used the ferret Helicobacter mustelae model to investigate the effect of prior infection and eradication on reinfection by experimental and natural routes. Two groups of ferrets with naturally acquired H. mustelae infection were treated with an eradication protocol using amoxicillin, metronidazole, and bismuth subsalicylate. The ferrets were monitored for recrudescence by repeated cultures of endoscopic gastric mucosal biopsies. The ferrets were challenged at 17 months (group I) and 6 months (group II) after eradication with a strain of H. mustelae having a distinctive restriction endonuclease analysis pattern. The eradication protocol was repeated to eliminate the infection produced by experimental challenge. The ferrets were then cohoused intermittently with naturally infected ferrets. The original H. mustelae infection was successfully eliminated by the eradication protocol. No recrudescence was observed in group I for 12 months nor for 3 months in group II after eradication. All ferrets became persistently reinfected with the challenge strain. The infection from the challenge strain was eradicated successfully. No ferrets in group I and all ferrets in group II became infected through cohousing. These results suggest that though prior infection with H. mustelae may confer some protection against reinfection, such protection is not universal in all circumstances; that susceptibility to reinfection by contact with infected animals varies between individuals; and that age may be a factor in this individual variability. These results are applicable to studies of reinfection after eradication of H. pylori in humans.

Consideration of the Aluminum Distribution in Zeolites in Theoretical and Experimental Catalysis Research

DOE PAGES

Knott, Brandon C.; Nimlos, Claire T.; Robichaud, David J.; ...

2017-12-11

Research efforts in zeolite catalysis have become increasingly cognizant of the diversity in structure and function resulting from the distribution of framework aluminum atoms, through emerging reports of catalytic phenomena that fall outside those recognizable as the shape-selective ones emblematic of its earlier history. Molecular-level descriptions of how active-site distributions affect catalysis are an aspirational goal articulated frequently in experimental and theoretical research, yet they are limited by imprecise knowledge of the structure and behavior of the zeolite materials under interrogation. In experimental research, higher precision can result from more reliable control of structure during synthesis and from more robustmore » and quantitative structural and kinetic characterization probes. In theoretical research, construction of models with specific aluminum locations and distributions seldom capture the heterogeneity inherent to the materials studied by experiment. In this Perspective, we discuss research findings that appropriately frame the challenges in developing more predictive synthesis-structure-function relations for zeolites, highlighting studies on ZSM-5 zeolites that are among the most structurally complex molecular sieve frameworks and the most widely studied because of their versatility in commercial applications. We discuss research directions to address these challenges and forge stronger connections between zeolite structure, composition, and active sites to catalytic function. Such connections promise to aid in bridging the findings of theoretical and experimental catalysis research, and transforming zeolite active site design from an empirical endeavor into a more predictable science founded on validated models.« less

Consideration of the Aluminum Distribution in Zeolites in Theoretical and Experimental Catalysis Research

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

Knott, Brandon C.; Nimlos, Claire T.; Robichaud, David J.

Research efforts in zeolite catalysis have become increasingly cognizant of the diversity in structure and function resulting from the distribution of framework aluminum atoms, through emerging reports of catalytic phenomena that fall outside those recognizable as the shape-selective ones emblematic of its earlier history. Molecular-level descriptions of how active-site distributions affect catalysis are an aspirational goal articulated frequently in experimental and theoretical research, yet they are limited by imprecise knowledge of the structure and behavior of the zeolite materials under interrogation. In experimental research, higher precision can result from more reliable control of structure during synthesis and from more robustmore » and quantitative structural and kinetic characterization probes. In theoretical research, construction of models with specific aluminum locations and distributions seldom capture the heterogeneity inherent to the materials studied by experiment. In this Perspective, we discuss research findings that appropriately frame the challenges in developing more predictive synthesis-structure-function relations for zeolites, highlighting studies on ZSM-5 zeolites that are among the most structurally complex molecular sieve frameworks and the most widely studied because of their versatility in commercial applications. We discuss research directions to address these challenges and forge stronger connections between zeolite structure, composition, and active sites to catalytic function. Such connections promise to aid in bridging the findings of theoretical and experimental catalysis research, and transforming zeolite active site design from an empirical endeavor into a more predictable science founded on validated models.« less

Addressing recent docking challenges: A hybrid strategy to integrate template-based and free protein-protein docking.

PubMed

Yan, Yumeng; Wen, Zeyu; Wang, Xinxiang; Huang, Sheng-You

2017-03-01

Protein-protein docking is an important computational tool for predicting protein-protein interactions. With the rapid development of proteomics projects, more and more experimental binding information ranging from mutagenesis data to three-dimensional structures of protein complexes are becoming available. Therefore, how to appropriately incorporate the biological information into traditional ab initio docking has been an important issue and challenge in the field of protein-protein docking. To address these challenges, we have developed a Hybrid DOCKing protocol of template-based and template-free approaches, referred to as HDOCK. The basic procedure of HDOCK is to model the structures of individual components based on the template complex by a template-based method if a template is available; otherwise, the component structures will be modeled based on monomer proteins by regular homology modeling. Then, the complex structure of the component models is predicted by traditional protein-protein docking. With the HDOCK protocol, we have participated in the CPARI experiment for rounds 28-35. Out of the 25 CASP-CAPRI targets for oligomer modeling, our HDOCK protocol predicted correct models for 16 targets, ranking one of the top algorithms in this challenge. Our docking method also made correct predictions on other CAPRI challenges such as protein-peptide binding for 6 out of 8 targets and water predictions for 2 out of 2 targets. The advantage of our hybrid docking approach over pure template-based docking was further confirmed by a comparative evaluation on 20 CASP-CAPRI targets. Proteins 2017; 85:497-512. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Protective effects of vaccines against experimental salmonellosis in racing pigeons.

PubMed

Uyttebroek, E; Devriese, L A; Gevaert, D; Ducatelle, R; Nelis, J; Haesebrouck, F

1991-02-16

Five inactivated and one attenuated vaccine produced for the prevention of salmonellosis in pigeons were compared in an experimental challenge model. The birds were vaccinated according to the recommendations of the manufacturers and they were infected by gavage with a Salmonella typhimurium (var copenhagen) pigeon strain. The challenged control animals showed severe weight loss, excessive water intake over a prolonged period, and excreted large numbers of salmonellae. None of the vaccines fully protected the pigeons, and only an inactivated oil adjuvant vaccine was able to reduce the severity of the clinical signs significantly. Mortality was low and tended to increase with the severity of the clinical signs. These results do not justify the preventive use of salmonella vaccination in pigeons. Nevertheless, the oil adjuvant vaccine may help in the effective cleaning of lofts after an outbreak of salmonellosis.

Three-dimensional organotypic culture: experimental models of mammalian biology and disease.

PubMed

Shamir, Eliah R; Ewald, Andrew J

2014-10-01

Mammalian organs are challenging to study as they are fairly inaccessible to experimental manipulation and optical observation. Recent advances in three-dimensional (3D) culture techniques, coupled with the ability to independently manipulate genetic and microenvironmental factors, have enabled the real-time study of mammalian tissues. These systems have been used to visualize the cellular basis of epithelial morphogenesis, to test the roles of specific genes in regulating cell behaviours within epithelial tissues and to elucidate the contribution of microenvironmental factors to normal and disease processes. Collectively, these novel models can be used to answer fundamental biological questions and generate replacement human tissues, and they enable testing of novel therapeutic approaches, often using patient-derived cells.

Recent mouse and rat methods for the study of experimental oral candidiasis.

PubMed

Costa, Anna C B P; Pereira, Cristiane A; Junqueira, Juliana C; Jorge, Antonio O C

2013-07-01

The Candida genus expresses virulence factors that, when combined with immunosuppression and other risk factors, can cause different manifestations of oral candidiasis. The treatment of mucosal infections caused by Candida and the elucidation of the disease process have proven challenging. Therefore, the study of experimentally induced oral candidiasis in rats and mice is useful to clarify the etiopathology of this condition, improve diagnosis, and search for new therapeutic options because the disease process in these animals is similar to that of human candidiasis lesions. Here, we describe and discuss new studies involving rat and mouse models of oral candidiasis with respect to methods for inducing experimental infection, methods for evaluating the development of experimental candidiasis, and new treatment strategies for oral candidiasis.

Set statistics in conductive bridge random access memory device with Cu/HfO{sub 2}/Pt structure

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

Zhang, Meiyun; Long, Shibing, E-mail: longshibing@ime.ac.cn; Wang, Guoming

2014-11-10

The switching parameter variation of resistive switching memory is one of the most important challenges in its application. In this letter, we have studied the set statistics of conductive bridge random access memory with a Cu/HfO{sub 2}/Pt structure. The experimental distributions of the set parameters in several off resistance ranges are shown to nicely fit a Weibull model. The Weibull slopes of the set voltage and current increase and decrease logarithmically with off resistance, respectively. This experimental behavior is perfectly captured by a Monte Carlo simulator based on the cell-based set voltage statistics model and the Quantum Point Contact electronmore » transport model. Our work provides indications for the improvement of the switching uniformity.« less

Multiscale mechanobiology: computational models for integrating molecules to multicellular systems

PubMed Central

Mak, Michael; Kim, Taeyoon

2015-01-01

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

Editorial

NASA Astrophysics Data System (ADS)

Bijeljic, Branko; Icardi, Matteo; Prodanović, Maša

2018-05-01

Substantial progress has been made over last few decades on understanding the physics of multiphase flow and reactive transport phenomena in subsurface porous media. Confluence of advances in experimental techniques (including micromodels, X-ray microtomography, Nuclear Magnetic Resonance (NMR)) as well as computational power have made it possible to observe static and dynamic multi-scale flow, transport and reactive processes, thus stimulating development of new generation of modelling tools from pore to field scale. One of the key challenges is to make experiment and models as complementary as possible, with continuously improving experimental methods in order to increase predictive capabilities of theoretical models across scales. This creates need to establish rigorous benchmark studies of flow, transport and reaction in porous media which can then serve as the basis for introducing more complex phenomena in future developments.

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

PubMed Central

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

2009-01-01

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

Evolving Non-Dominated Parameter Sets for Computational Models from Multiple Experiments

NASA Astrophysics Data System (ADS)

Lane, Peter C. R.; Gobet, Fernand

2013-03-01

Creating robust, reproducible and optimal computational models is a key challenge for theorists in many sciences. Psychology and cognitive science face particular challenges as large amounts of data are collected and many models are not amenable to analytical techniques for calculating parameter sets. Particular problems are to locate the full range of acceptable model parameters for a given dataset, and to confirm the consistency of model parameters across different datasets. Resolving these problems will provide a better understanding of the behaviour of computational models, and so support the development of general and robust models. In this article, we address these problems using evolutionary algorithms to develop parameters for computational models against multiple sets of experimental data; in particular, we propose the `speciated non-dominated sorting genetic algorithm' for evolving models in several theories. We discuss the problem of developing a model of categorisation using twenty-nine sets of data and models drawn from four different theories. We find that the evolutionary algorithms generate high quality models, adapted to provide a good fit to all available data.

Exemplar for simulation challenges: Large-deformation micromechanics of Sylgard 184/glass microballoon syntactic foams.

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

Brown, Judith Alice; Long, Kevin Nicholas

2018-05-01

Sylgard® 184/Glass Microballoon (GMB) potting material is currently used in many NW systems. Analysts need a macroscale constitutive model that can predict material behavior under complex loading and damage evolution. To address this need, ongoing modeling and experimental efforts have focused on study of damage evolution in these materials. Micromechanical finite element simulations that resolve individual GMB and matrix components promote discovery and better understanding of the material behavior. With these simulations, we can study the role of the GMB volume fraction, time-dependent damage, behavior under confined vs. unconfined compression, and the effects of partial damage. These simulations are challengingmore » and push the boundaries of capability even with the high performance computing tools available at Sandia. We summarize the major challenges and the current state of this modeling effort, as an exemplar of micromechanical modeling needs that can motivate advances in future computing efforts.« less

[A New Challenge of Working Together: Psychiatry and Heraing Voices].

PubMed

Laval, Christian

Recovery model, as the hearing voices movement, promotes the users discourse among the health workers. This interference of users in the expertise considering the meaning of their voices is faced with the vision of advocating health workers, particularly the psychiatrists supporting the psychiatric users movement. On the field, this association seems challenging. On the experimental site in Marseille, professionals through various tensions and practical difficulties tend to reconsider their power / knowledge. This new challenge of working together leads them to adopt both a more humble position towards their clinical expertise and a more ambitious position regarding their participation in the construction of public controversies highlighted by the speaking experience of the hearing voices movement.

New Challenges for Intervertebral Disc Treatment Using Regenerative Medicine

PubMed Central

Masuda, Koichi

2010-01-01

The development of tissue engineering therapies for the intervertebral disc is challenging due to ambiguities of disease and pain mechanisms in patients, and lack of consensus on preclinical models for safety and efficacy testing. Although the issues associated with model selection for studying orthopedic diseases or treatments have been discussed often, the multifaceted challenges associated with developing intervertebral disc tissue engineering therapies require special discussion. This review covers topics relevant to the clinical translation of tissue-engineered technologies: (1) the unmet clinical need, (2) appropriate models for safety and efficacy testing, (3) the need for standardized model systems, and (4) the translational pathways leading to a clinical trial. For preclinical evaluation of new therapies, we recommend establishing biologic plausibility of efficacy and safety using models of increasing complexity, starting with cell culture, small animals (rats and rabbits), and then large animals (goat and minipig) that more closely mimic nutritional, biomechanical, and surgical realities of human application. The use of standardized and reproducible experimental procedures and outcome measures is critical for judging relative efficacy. Finally, success will hinge on carefully designed clinical trials with well-defined patient selection criteria, gold-standard controls, and objective outcome metrics to assess performance in the early postoperative period. PMID:19903086

Methods in Enzymology: “Flexible backbone sampling methods to model and design protein alternative conformations”

PubMed Central

Ollikainen, Noah; Smith, Colin A.; Fraser, James S.; Kortemme, Tanja

2013-01-01

Sampling alternative conformations is key to understanding how proteins work and engineering them for new functions. However, accurately characterizing and modeling protein conformational ensembles remains experimentally and computationally challenging. These challenges must be met before protein conformational heterogeneity can be exploited in protein engineering and design. Here, as a stepping stone, we describe methods to detect alternative conformations in proteins and strategies to model these near-native conformational changes based on backrub-type Monte Carlo moves in Rosetta. We illustrate how Rosetta simulations that apply backrub moves improve modeling of point mutant side chain conformations, native side chain conformational heterogeneity, functional conformational changes, tolerated sequence space, protein interaction specificity, and amino acid co-variation across protein-protein interfaces. We include relevant Rosetta command lines and RosettaScripts to encourage the application of these types of simulations to other systems. Our work highlights that critical scoring and sampling improvements will be necessary to approximate conformational landscapes. Challenges for the future development of these methods include modeling conformational changes that propagate away from designed mutation sites and modulating backbone flexibility to predictively design functionally important conformational heterogeneity. PMID:23422426

Quantitative analysis of Porcine Reproductive and Respiratory Syndrome (PRRS) viremia profiles from experimental infection: a statistical modelling approach

USDA-ARS?s Scientific Manuscript database

Porcine reproductive and respiratory syndrome (PRRS) is the most economically significant viral disease facing the global swine industry. Viremia profiles of PRRS virus challenged pigs reflect the severity and progression of the infection within the host and provide crucial information for subsequen...

Pathways, Networks, and Systems: Theory and Experiments

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

Joseph H. Nadeau; John D. Lambris

2004-10-30

The international conference provided a unique opportunity for theoreticians and experimenters to exchange ideas, strategies, problems, challenges, language and opportunities in both formal and informal settings. This dialog is an important step towards developing a deep and effective integration of theory and experiments in studies of systems biology in humans and model organisms.

Challenging the Knowledge-Transfer Orthodoxy: Knowledge Co-construction in Technology-Enhanced Learning for Children with Autism

ERIC Educational Resources Information Center

Guldberg, Karen; Parsons, Sarah; Porayska-Pomsta, Kaska; Keay-Bright, Wendy

2017-01-01

Experimental intervention studies constitute the current dominant research designs in the autism education field. Such designs are based on a "knowledge-transfer" model of evidence-based practice in which research is conducted by researchers, and is then "transferred" to practitioners to enable them to implement evidence-based…

Gravitational decoherence

NASA Astrophysics Data System (ADS)

Bassi, Angelo; Großardt, André; Ulbricht, Hendrik

2017-10-01

We discuss effects of loss of coherence in low energy quantum systems caused by or related to gravitation, referred to as gravitational decoherence. These effects, resulting from random metric fluctuations, for instance, promise to be accessible by relatively inexpensive table-top experiments, way before the scales where true quantum gravity effects become important. Therefore, they can provide a first experimental view on gravity in the quantum regime. We will survey models of decoherence induced both by classical and quantum gravitational fluctuations; it will be manifest that a clear understanding of gravitational decoherence is still lacking. Next we will review models where quantum theory is modified, under the assumption that gravity causes the collapse of the wave functions, when systems are large enough. These models challenge the quantum-gravity interplay, and can be tested experimentally. In the last part we have a look at the state of the art of experimental research. We will review efforts aiming at more and more accurate measurements of gravity (G and g) and ideas for measuring conventional and unconventional gravity effects on nonrelativistic quantum systems.

Studying light-harvesting models with superconducting circuits.

PubMed

Potočnik, Anton; Bargerbos, Arno; Schröder, Florian A Y N; Khan, Saeed A; Collodo, Michele C; Gasparinetti, Simone; Salathé, Yves; Creatore, Celestino; Eichler, Christopher; Türeci, Hakan E; Chin, Alex W; Wallraff, Andreas

2018-03-02

The process of photosynthesis, the main source of energy in the living world, converts sunlight into chemical energy. The high efficiency of this process is believed to be enabled by an interplay between the quantum nature of molecular structures in photosynthetic complexes and their interaction with the environment. Investigating these effects in biological samples is challenging due to their complex and disordered structure. Here we experimentally demonstrate a technique for studying photosynthetic models based on superconducting quantum circuits, which complements existing experimental, theoretical, and computational approaches. We demonstrate a high degree of freedom in design and experimental control of our approach based on a simplified three-site model of a pigment protein complex with realistic parameters scaled down in energy by a factor of 10 5 . We show that the excitation transport between quantum-coherent sites disordered in energy can be enabled through the interaction with environmental noise. We also show that the efficiency of the process is maximized for structured noise resembling intramolecular phononic environments found in photosynthetic complexes.

Computational-experimental approach to drug-target interaction mapping: A case study on kinase inhibitors

PubMed Central

Ravikumar, Balaguru; Parri, Elina; Timonen, Sanna; Airola, Antti; Wennerberg, Krister

2017-01-01

Due to relatively high costs and labor required for experimental profiling of the full target space of chemical compounds, various machine learning models have been proposed as cost-effective means to advance this process in terms of predicting the most potent compound-target interactions for subsequent verification. However, most of the model predictions lack direct experimental validation in the laboratory, making their practical benefits for drug discovery or repurposing applications largely unknown. Here, we therefore introduce and carefully test a systematic computational-experimental framework for the prediction and pre-clinical verification of drug-target interactions using a well-established kernel-based regression algorithm as the prediction model. To evaluate its performance, we first predicted unmeasured binding affinities in a large-scale kinase inhibitor profiling study, and then experimentally tested 100 compound-kinase pairs. The relatively high correlation of 0.77 (p < 0.0001) between the predicted and measured bioactivities supports the potential of the model for filling the experimental gaps in existing compound-target interaction maps. Further, we subjected the model to a more challenging task of predicting target interactions for such a new candidate drug compound that lacks prior binding profile information. As a specific case study, we used tivozanib, an investigational VEGF receptor inhibitor with currently unknown off-target profile. Among 7 kinases with high predicted affinity, we experimentally validated 4 new off-targets of tivozanib, namely the Src-family kinases FRK and FYN A, the non-receptor tyrosine kinase ABL1, and the serine/threonine kinase SLK. Our sub-sequent experimental validation protocol effectively avoids any possible information leakage between the training and validation data, and therefore enables rigorous model validation for practical applications. These results demonstrate that the kernel-based modeling approach offers practical benefits for probing novel insights into the mode of action of investigational compounds, and for the identification of new target selectivities for drug repurposing applications. PMID:28787438

Development and validation of quasi-steady-state heat pump water heater model having stratified water tank and wrapped-tank condenser

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

Shen, Bo; Nawaz, Kashif; Baxter, Van D.

Heat pump water heater systems (HPWH) introduce new challenges for design and modeling tools, because they require vapor compression system balanced with a water storage tank. In addition, a wrapped-tank condenser coil has strong coupling with a stratified water tank, which leads HPWH simulation to a transient process. To tackle these challenges and deliver an effective, hardware-based HPWH equipment design tool, a quasi-steady-state HPWH model was developed based on the DOE/ORNL Heat Pump Design Model (HPDM). Two new component models were added via this study. One is a one-dimensional stratified water tank model, an improvement to the open-source EnergyPlus watermore » tank model, by introducing a calibration factor to account for bulk mixing effect due to water draws, circulations, etc. The other is a wrapped-tank condenser coil model, using a segment-to-segment modeling approach. In conclusion, the HPWH system model was validated against available experimental data. After that, the model was used for parametric simulations to determine the effects of various design factors.« less

Development and validation of quasi-steady-state heat pump water heater model having stratified water tank and wrapped-tank condenser

DOE PAGES

Shen, Bo; Nawaz, Kashif; Baxter, Van D.; ...

2017-10-31

Heat pump water heater systems (HPWH) introduce new challenges for design and modeling tools, because they require vapor compression system balanced with a water storage tank. In addition, a wrapped-tank condenser coil has strong coupling with a stratified water tank, which leads HPWH simulation to a transient process. To tackle these challenges and deliver an effective, hardware-based HPWH equipment design tool, a quasi-steady-state HPWH model was developed based on the DOE/ORNL Heat Pump Design Model (HPDM). Two new component models were added via this study. One is a one-dimensional stratified water tank model, an improvement to the open-source EnergyPlus watermore » tank model, by introducing a calibration factor to account for bulk mixing effect due to water draws, circulations, etc. The other is a wrapped-tank condenser coil model, using a segment-to-segment modeling approach. In conclusion, the HPWH system model was validated against available experimental data. After that, the model was used for parametric simulations to determine the effects of various design factors.« less

Atomic Calculations and Laboratory Measurements Relevant to X-ray Warm Absorbers

NASA Technical Reports Server (NTRS)

Kallman, Tim; Bautista, M.; Palmeri, P.

2007-01-01

This viewgraph document reviews the atomic calculations and the measurements from the laboratory that are relevant to our understanding of X-Ray Warm Absorbers. Included is a brief discussion of the theoretical and the experimental tools. Also included is a discussion of the challenges, and calculations relevant to dielectronic recombination, photoionization cross sections, and collisional ionization. A review of the models is included, and the sequence that the models were applied.

Comments on PDF methods

NASA Technical Reports Server (NTRS)

Chen, J.-Y.

1992-01-01

Viewgraphs are presented on the following topics: the grand challenge of combustion engineering; research of probability density function (PDF) methods at Sandia; experiments of turbulent jet flames (Masri and Dibble, 1988); departures from chemical equilibrium; modeling turbulent reacting flows; superequilibrium OH radical; pdf modeling of turbulent jet flames; scatter plot for CH4 (methane) and O2 (oxygen); methanol turbulent jet flames; comparisons between predictions and experimental data; and turbulent C2H4 jet flames.

Fluid–Structure Interaction Analysis of Papillary Muscle Forces Using a Comprehensive Mitral Valve Model with 3D Chordal Structure

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

Toma, Milan; Jensen, Morten Ø.; Einstein, Daniel R.

2015-07-17

Numerical models of native heart valves are being used to study valve biomechanics to aid design and development of repair procedures and replacement devices. These models have evolved from simple two-dimensional approximations to complex three-dimensional, fully coupled fluid-structure interaction (FSI) systems. Such simulations are useful for predicting the mechanical and hemodynamic loading on implanted valve devices. A current challenge for improving the accuracy of these predictions is choosing and implementing modeling boundary conditions. In order to address this challenge, we are utilizing an advanced in-vitro system to validate FSI conditions for the mitral valve system. Explanted ovine mitral valves weremore » mounted in an in vitro setup, and structural data for the mitral valve was acquired with *CT. Experimental data from the in-vitro ovine mitral valve system were used to validate the computational model. As the valve closes, the hemodynamic data, high speed lea et dynamics, and force vectors from the in-vitro system were compared to the results of the FSI simulation computational model. The total force of 2.6 N per papillary muscle is matched by the computational model. In vitro and in vivo force measurements are important in validating and adjusting material parameters in computational models. The simulations can then be used to answer questions that are otherwise not possible to investigate experimentally. This work is important to maximize the validity of computational models of not just the mitral valve, but any biomechanical aspect using computational simulation in designing medical devices.« less

Fluid-Structure Interaction Analysis of Papillary Muscle Forces Using a Comprehensive Mitral Valve Model with 3D Chordal Structure.

PubMed

Toma, Milan; Jensen, Morten Ø; Einstein, Daniel R; Yoganathan, Ajit P; Cochran, Richard P; Kunzelman, Karyn S

2016-04-01

Numerical models of native heart valves are being used to study valve biomechanics to aid design and development of repair procedures and replacement devices. These models have evolved from simple two-dimensional approximations to complex three-dimensional, fully coupled fluid-structure interaction (FSI) systems. Such simulations are useful for predicting the mechanical and hemodynamic loading on implanted valve devices. A current challenge for improving the accuracy of these predictions is choosing and implementing modeling boundary conditions. In order to address this challenge, we are utilizing an advanced in vitro system to validate FSI conditions for the mitral valve system. Explanted ovine mitral valves were mounted in an in vitro setup, and structural data for the mitral valve was acquired with [Formula: see text]CT. Experimental data from the in vitro ovine mitral valve system were used to validate the computational model. As the valve closes, the hemodynamic data, high speed leaflet dynamics, and force vectors from the in vitro system were compared to the results of the FSI simulation computational model. The total force of 2.6 N per papillary muscle is matched by the computational model. In vitro and in vivo force measurements enable validating and adjusting material parameters to improve the accuracy of computational models. The simulations can then be used to answer questions that are otherwise not possible to investigate experimentally. This work is important to maximize the validity of computational models of not just the mitral valve, but any biomechanical aspect using computational simulation in designing medical devices.

The Mechanics of Embodiment: A Dialog on Embodiment and Computational Modeling

PubMed Central

Pezzulo, Giovanni; Barsalou, Lawrence W.; Cangelosi, Angelo; Fischer, Martin H.; McRae, Ken; Spivey, Michael J.

2011-01-01

Embodied theories are increasingly challenging traditional views of cognition by arguing that conceptual representations that constitute our knowledge are grounded in sensory and motor experiences, and processed at this sensorimotor level, rather than being represented and processed abstractly in an amodal conceptual system. Given the established empirical foundation, and the relatively underspecified theories to date, many researchers are extremely interested in embodied cognition but are clamoring for more mechanistic implementations. What is needed at this stage is a push toward explicit computational models that implement sensorimotor grounding as intrinsic to cognitive processes. In this article, six authors from varying backgrounds and approaches address issues concerning the construction of embodied computational models, and illustrate what they view as the critical current and next steps toward mechanistic theories of embodiment. The first part has the form of a dialog between two fictional characters: Ernest, the “experimenter,” and Mary, the “computational modeler.” The dialog consists of an interactive sequence of questions, requests for clarification, challenges, and (tentative) answers, and touches the most important aspects of grounded theories that should inform computational modeling and, conversely, the impact that computational modeling could have on embodied theories. The second part of the article discusses the most important open challenges for embodied computational modeling. PMID:21713184

A Review of the Combination of Experimental Measurements and Fibril-Reinforced Modeling for Investigation of Articular Cartilage and Chondrocyte Response to Loading

PubMed Central

Wilson, Wouter; Isaksson, Hanna; Jurvelin, Jukka S.; Herzog, Walter; Korhonen, Rami K.

2013-01-01

The function of articular cartilage depends on its structure and composition, sensitively impaired in disease (e.g. osteoarthritis, OA). Responses of chondrocytes to tissue loading are modulated by the structure. Altered cell responses as an effect of OA may regulate cartilage mechanotransduction and cell biosynthesis. To be able to evaluate cell responses and factors affecting the onset and progression of OA, local tissue and cell stresses and strains in cartilage need to be characterized. This is extremely challenging with the presently available experimental techniques and therefore computational modeling is required. Modern models of articular cartilage are inhomogeneous and anisotropic, and they include many aspects of the real tissue structure and composition. In this paper, we provide an overview of the computational applications that have been developed for modeling the mechanics of articular cartilage at the tissue and cellular level. We concentrate on the use of fibril-reinforced models of cartilage. Furthermore, we introduce practical considerations for modeling applications, including also experimental tests that can be combined with the modeling approach. At the end, we discuss the prospects for patient-specific models when aiming to use finite element modeling analysis and evaluation of articular cartilage function, cellular responses, failure points, OA progression, and rehabilitation. PMID:23653665

Experimental Design for Stochastic Models of Nonlinear Signaling Pathways Using an Interval-Wise Linear Noise Approximation and State Estimation

PubMed Central

Zimmer, Christoph

2016-01-01

Background Computational modeling is a key technique for analyzing models in systems biology. There are well established methods for the estimation of the kinetic parameters in models of ordinary differential equations (ODE). Experimental design techniques aim at devising experiments that maximize the information encoded in the data. For ODE models there are well established approaches for experimental design and even software tools. However, data from single cell experiments on signaling pathways in systems biology often shows intrinsic stochastic effects prompting the development of specialized methods. While simulation methods have been developed for decades and parameter estimation has been targeted for the last years, only very few articles focus on experimental design for stochastic models. Methods The Fisher information matrix is the central measure for experimental design as it evaluates the information an experiment provides for parameter estimation. This article suggest an approach to calculate a Fisher information matrix for models containing intrinsic stochasticity and high nonlinearity. The approach makes use of a recently suggested multiple shooting for stochastic systems (MSS) objective function. The Fisher information matrix is calculated by evaluating pseudo data with the MSS technique. Results The performance of the approach is evaluated with simulation studies on an Immigration-Death, a Lotka-Volterra, and a Calcium oscillation model. The Calcium oscillation model is a particularly appropriate case study as it contains the challenges inherent to signaling pathways: high nonlinearity, intrinsic stochasticity, a qualitatively different behavior from an ODE solution, and partial observability. The computational speed of the MSS approach for the Fisher information matrix allows for an application in realistic size models. PMID:27583802

Building macromolecular assemblies by information-driven docking: introducing the HADDOCK multibody docking server.

PubMed

Karaca, Ezgi; Melquiond, Adrien S J; de Vries, Sjoerd J; Kastritis, Panagiotis L; Bonvin, Alexandre M J J

2010-08-01

Over the last years, large scale proteomics studies have generated a wealth of information of biomolecular complexes. Adding the structural dimension to the resulting interactomes represents a major challenge that classical structural experimental methods alone will have difficulties to confront. To meet this challenge, complementary modeling techniques such as docking are thus needed. Among the current docking methods, HADDOCK (High Ambiguity-Driven DOCKing) distinguishes itself from others by the use of experimental and/or bioinformatics data to drive the modeling process and has shown a strong performance in the critical assessment of prediction of interactions (CAPRI), a blind experiment for the prediction of interactions. Although most docking programs are limited to binary complexes, HADDOCK can deal with multiple molecules (up to six), a capability that will be required to build large macromolecular assemblies. We present here a novel web interface of HADDOCK that allows the user to dock up to six biomolecules simultaneously. This interface allows the inclusion of a large variety of both experimental and/or bioinformatics data and supports several types of cyclic and dihedral symmetries in the docking of multibody assemblies. The server was tested on a benchmark of six cases, containing five symmetric homo-oligomeric protein complexes and one symmetric protein-DNA complex. Our results reveal that, in the presence of either bioinformatics and/or experimental data, HADDOCK shows an excellent performance: in all cases, HADDOCK was able to generate good to high quality solutions and ranked them at the top, demonstrating its ability to model symmetric multicomponent assemblies. Docking methods can thus play an important role in adding the structural dimension to interactomes. However, although the current docking methodologies were successful for a vast range of cases, considering the variety and complexity of macromolecular assemblies, inclusion of some kind of experimental information (e.g. from mass spectrometry, nuclear magnetic resonance, cryoelectron microscopy, etc.) will remain highly desirable to obtain reliable results.

Model-Based Estimation of Knee Stiffness

PubMed Central

Pfeifer, Serge; Vallery, Heike; Hardegger, Michael; Riener, Robert; Perreault, Eric J.

2013-01-01

During natural locomotion, the stiffness of the human knee is modulated continuously and subconsciously according to the demands of activity and terrain. Given modern actuator technology, powered transfemoral prostheses could theoretically provide a similar degree of sophistication and function. However, experimentally quantifying knee stiffness modulation during natural gait is challenging. Alternatively, joint stiffness could be estimated in a less disruptive manner using electromyography (EMG) combined with kinetic and kinematic measurements to estimate muscle force, together with models that relate muscle force to stiffness. Here we present the first step in that process, where we develop such an approach and evaluate it in isometric conditions, where experimental measurements are more feasible. Our EMG-guided modeling approach allows us to consider conditions with antagonistic muscle activation, a phenomenon commonly observed in physiological gait. Our validation shows that model-based estimates of knee joint stiffness coincide well with experimental data obtained using conventional perturbation techniques. We conclude that knee stiffness can be accurately estimated in isometric conditions without applying perturbations, which presents an important step towards our ultimate goal of quantifying knee stiffness during gait. PMID:22801482

Open challenges in structure-based virtual screening: Receptor modeling, target flexibility consideration and active site water molecules description.

PubMed

Spyrakis, Francesca; Cavasotto, Claudio N

2015-10-01

Structure-based virtual screening is currently an established tool in drug lead discovery projects. Although in the last years the field saw an impressive progress in terms of algorithm development, computational performance, and retrospective and prospective applications in ligand identification, there are still long-standing challenges where further improvement is needed. In this review, we consider the conceptual frame, state-of-the-art and recent developments of three critical "structural" issues in structure-based drug lead discovery: the use of homology modeling to accurately model the binding site when no experimental structures are available, the necessity of accounting for the dynamics of intrinsically flexible systems as proteins, and the importance of considering active site water molecules in lead identification and optimization campaigns. Copyright © 2015 Elsevier Inc. All rights reserved.

BioPreDyn-bench: a suite of benchmark problems for dynamic modelling in systems biology.

PubMed

Villaverde, Alejandro F; Henriques, David; Smallbone, Kieran; Bongard, Sophia; Schmid, Joachim; Cicin-Sain, Damjan; Crombach, Anton; Saez-Rodriguez, Julio; Mauch, Klaus; Balsa-Canto, Eva; Mendes, Pedro; Jaeger, Johannes; Banga, Julio R

2015-02-20

Dynamic modelling is one of the cornerstones of systems biology. Many research efforts are currently being invested in the development and exploitation of large-scale kinetic models. The associated problems of parameter estimation (model calibration) and optimal experimental design are particularly challenging. The community has already developed many methods and software packages which aim to facilitate these tasks. However, there is a lack of suitable benchmark problems which allow a fair and systematic evaluation and comparison of these contributions. Here we present BioPreDyn-bench, a set of challenging parameter estimation problems which aspire to serve as reference test cases in this area. This set comprises six problems including medium and large-scale kinetic models of the bacterium E. coli, baker's yeast S. cerevisiae, the vinegar fly D. melanogaster, Chinese Hamster Ovary cells, and a generic signal transduction network. The level of description includes metabolism, transcription, signal transduction, and development. For each problem we provide (i) a basic description and formulation, (ii) implementations ready-to-run in several formats, (iii) computational results obtained with specific solvers, (iv) a basic analysis and interpretation. This suite of benchmark problems can be readily used to evaluate and compare parameter estimation methods. Further, it can also be used to build test problems for sensitivity and identifiability analysis, model reduction and optimal experimental design methods. The suite, including codes and documentation, can be freely downloaded from the BioPreDyn-bench website, https://sites.google.com/site/biopredynbenchmarks/ .

Skin hydration analysis by experiment and computer simulations and its implications for diapered skin.

PubMed

Saadatmand, M; Stone, K J; Vega, V N; Felter, S; Ventura, S; Kasting, G; Jaworska, J

2017-11-01

Experimental work on skin hydration is technologically challenging, and mostly limited to observations where environmental conditions are constant. In some cases, like diapered baby skin, such work is practically unfeasible, yet it is important to understand potential effects of diapering on skin condition. To overcome this challenge, in part, we developed a computer simulation model of reversible transient skin hydration effects. Skin hydration model by Li et al. (Chem Eng Sci, 138, 2015, 164) was further developed to simulate transient exposure conditions where relative humidity (RH), wind velocity, air, and skin temperature can be any function of time. Computer simulations of evaporative water loss (EWL) decay after different occlusion times were compared with experimental data to calibrate the model. Next, we used the model to investigate EWL and SC thickness in different diapering scenarios. Key results from the experimental work were: (1) For occlusions by RH=100% and free water longer than 30 minutes the absorbed amount of water is almost the same; (2) Longer occlusion times result in higher water absorption by the SC. The EWL decay and skin water content predictions were in agreement with experimental data. Simulations also revealed that skin under occlusion hydrates mainly because the outflux is blocked, not because it absorbs water from the environment. Further, simulations demonstrated that hydration level is sensitive to time, RH and/or free water on skin. In simulated diapering scenarios, skin maintained hydration content very close to the baseline conditions without a diaper for the entire duration of a 24 hours period. Different diapers/diaper technologies are known to have different profiles in terms of their ability to provide wetness protection, which can result in consumer-noticeable differences in wetness. Simulation results based on published literature using data from a number of different diapers suggest that diapered skin hydrates within ranges considered reversible. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The trials and tribulations of a practitioner-researcher: challenges and lessons learned through testing a feminist-cognitive-relational social work model of practice.

PubMed

Dombo, Eileen A; Bass, Ami P

2014-01-01

In practice with adult women who survived childhood sexual abuse, the field of social work currently lacks an evidence-based intervention. The current interventions, from the 1990s, come primarily from psychologists. The hypothesis that the Feminist-Cognitive-Relational Social Work Model and Intervention will be more effective in decreasing cognitive distortions, and increasing intimacy and relational health when compared to the standard agency intervention was tested in a quasi-experimental study. The challenges in carrying out the study in small, non-profit organizations are explored to highlight the difficulties in developing evidence-based interventions. Changes to implementation that resulted from the research findings are discussed.

Evaluation of cross-protection by immunization with an experimental trivalent companion animal periodontitis vaccine in the mouse periodontitis model.

PubMed

Hardham, John; Sfintescu, Cornelia; Evans, Richard T

2008-03-01

Companion animal periodontal disease is one of the most prevalent diseases seen by veterinarians. The goal of this study was to evaluate the vaccine performance of a trivalent canine periodontitis vaccine in the mouse oral challenge model of periodontitis. Mice vaccinated subcutaneously with an inactivated, whole-cell vaccine preparation of Porphyromonas denticanis, Porphyromonas gulae, and Porphyromonas salivosa displayed significantly reduced alveolar bone loss in response to heterologous and cross-species challenges as compared to sham vaccinated animals. Based on the results of these studies, a periodontitis vaccine may be a useful tool in preventing the initiation and progression of periodontitis caused by the most commonly isolated pigmenting anaerobic bacteria in animals.

Batch settling curve registration via image data modeling.

PubMed

Derlon, Nicolas; Thürlimann, Christian; Dürrenmatt, David; Villez, Kris

2017-05-01

To this day, obtaining reliable characterization of sludge settling properties remains a challenging and time-consuming task. Without such assessments however, optimal design and operation of secondary settling tanks is challenging and conservative approaches will remain necessary. With this study, we show that automated sludge blanket height registration and zone settling velocity estimation is possible thanks to analysis of images taken during batch settling experiments. The experimental setup is particularly interesting for practical applications as it consists of off-the-shelf components only, no moving parts are required, and the software is released publicly. Furthermore, the proposed multivariate shape constrained spline model for image analysis appears to be a promising method for reliable sludge blanket height profile registration. Copyright © 2017 Elsevier Ltd. All rights reserved.

Traumatic Neuroma in Continuity Injury Model in Rodents

PubMed Central

Kemp, Stephen William Peter; Khu, Kathleen Joy Ong Lopez; Kumar, Ranjan; Webb, Aubrey A.; Midha, Rajiv

2012-01-01

Abstract Traumatic neuroma in continuity (NIC) results in profound neurological deficits, and its management poses the most challenging problem to peripheral nerve surgeons today. The absence of a clinically relevant experimental model continues to handicap our ability to investigate ways of better diagnosis and treatment for these disabling injuries. Various injury techniques were tested on Lewis rat sciatic nerves. Optimal experimental injuries that consistently resulted in NIC combined both intense focal compression and traction forces. Nerves were harvested at 0, 5, 13, 21, and 65 days for histological examination. Skilled locomotion and ground reaction force (GRF) analysis were performed up to 9 weeks on the experimental (n=6) and crush-control injuries (n=5). Focal widening, disruption of endoneurium and perineurium with aberrant intra- and extrafascicular axonal regeneration and progressive fibrosis was consistently demonstrated in 14 of 14 nerves with refined experimental injuries. At 8 weeks, experimental animals displayed a significantly greater slip ratio in both skilled locomotor assessments, compared to nerve crush animals (p<0.01). GRFs of the crush- injured animals showed earlier improvement compared to the experimental animals, whose overall GRF patterns failed to recover as well as the crush group. We have demonstrated histological features and poor functional recovery consistent with NIC formation in a rat model. The injury mechanism employed combines traction and compression forces akin to the physical forces at play in clinical nerve injuries. This model may serve as a tool to help diagnose this injury earlier and to develop intervention strategies to improve patient outcomes. PMID:22011082

Genetics of hypertension: discoveries from the bench to human populations

PubMed Central

Franceschini, Nora

2013-01-01

Hypertension is a complex trait that is influenced by both heritable and environmental factors. The search for genes accounting for the susceptibility to hypertension has driven parallel efforts in human research and in research using experimental animals in controlled environmental settings. Evidence from rodent models of genetic hypertension and human Mendelian forms of hypertension and hypotension have yielded mechanistic insights into the pathways that are perturbed in blood pressure homeostasis, most of which converge at the level of renal sodium reabsorption. However, the bridging of evidence from these very diverse approaches to identify mechanisms underlying hypertension susceptibility and the translation of these findings to human populations and public health remain a challenge. Furthermore, findings from genome-wide association studies still require functional validation in experimental models. In this review, we highlight results and implications from key studies in experimental and clinical hypertension to date. PMID:24133117

Budding yeast for budding geneticists: a primer on the Saccharomyces cerevisiae model system.

PubMed

Duina, Andrea A; Miller, Mary E; Keeney, Jill B

2014-05-01

The budding yeast Saccharomyces cerevisiae is a powerful model organism for studying fundamental aspects of eukaryotic cell biology. This Primer article presents a brief historical perspective on the emergence of this organism as a premier experimental system over the course of the past century. An overview of the central features of the S. cerevisiae genome, including the nature of its genetic elements and general organization, is also provided. Some of the most common experimental tools and resources available to yeast geneticists are presented in a way designed to engage and challenge undergraduate and graduate students eager to learn more about the experimental amenability of budding yeast. Finally, a discussion of several major discoveries derived from yeast studies highlights the far-reaching impact that the yeast system has had and will continue to have on our understanding of a variety of cellular processes relevant to all eukaryotes, including humans.

Budding Yeast for Budding Geneticists: A Primer on the Saccharomyces cerevisiae Model System

PubMed Central

Duina, Andrea A.; Miller, Mary E.; Keeney, Jill B.

2014-01-01

The budding yeast Saccharomyces cerevisiae is a powerful model organism for studying fundamental aspects of eukaryotic cell biology. This Primer article presents a brief historical perspective on the emergence of this organism as a premier experimental system over the course of the past century. An overview of the central features of the S. cerevisiae genome, including the nature of its genetic elements and general organization, is also provided. Some of the most common experimental tools and resources available to yeast geneticists are presented in a way designed to engage and challenge undergraduate and graduate students eager to learn more about the experimental amenability of budding yeast. Finally, a discussion of several major discoveries derived from yeast studies highlights the far-reaching impact that the yeast system has had and will continue to have on our understanding of a variety of cellular processes relevant to all eukaryotes, including humans. PMID:24807111

Interpreting plasmonic response of epitaxial Ag/Si(100) island ensembles

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

Kong, Dexin; Jiang, Liying; Drucker, Jeff

Associating features in the experimentally measured optical response of epitaxial Ag islands grown on Si(100) with the localized surface plasmon resonances (LSPRs) hosted by the Ag islands is challenging due to the variation of the Si dielectric function over the energy range under consideration. However, it is possible to conclusively identify features in the experimental spectra with LSPR modes oscillating both parallel and perpendicular to the epitaxial interface by simulating the optical response. The Abeles matrix method is used to describe the composite layered system and the Ag islands are modeled using the thin island film model developed by Bedeauxmore » and Vlieger. By incorporating island morphology parameters determined by quantitative analysis of electron micrographs, the simulation faithfully reproduces the main features of the experimental spectra. Individually zeroing the dipoles associated with the LSPR modes enables conclusive identification of their contribution to the optical response of the composite system.« less

Unravelling the electrochemical double layer by direct probing of the solid/liquid interface

PubMed Central

Favaro, Marco; Jeong, Beomgyun; Ross, Philip N.; Yano, Junko; Hussain, Zahid; Liu, Zhi; Crumlin, Ethan J.

2016-01-01

The electrochemical double layer plays a critical role in electrochemical processes. Whilst there have been many theoretical models predicting structural and electrical organization of the electrochemical double layer, the experimental verification of these models has been challenging due to the limitations of available experimental techniques. The induced potential drop in the electrolyte has never been directly observed and verified experimentally, to the best of our knowledge. In this study, we report the direct probing of the potential drop as well as the potential of zero charge by means of ambient pressure X-ray photoelectron spectroscopy performed under polarization conditions. By analyzing the spectra of the solvent (water) and a spectator neutral molecule with numerical simulations of the electric field, we discern the shape of the electrochemical double layer profile. In addition, we determine how the electrochemical double layer changes as a function of both the electrolyte concentration and applied potential. PMID:27576762

Recent Progress on Labfit: a Multispectrum Analysis Program for Fitting Lineshapes Including the Htp Model and Temperature Dependence

NASA Astrophysics Data System (ADS)

Cich, Matthew J.; Guillaume, Alexandre; Drouin, Brian; Benner, D. Chris

2017-06-01

Multispectrum analysis can be a challenge for a variety of reasons. It can be computationally intensive to fit a proper line shape model especially for high resolution experimental data. Band-wide analyses including many transitions along with interactions, across many pressures and temperatures are essential to accurately model, for example, atmospherically relevant systems. Labfit is a fast multispectrum analysis program originally developed by D. Chris Benner with a text-based interface. More recently at JPL a graphical user interface was developed with the goal of increasing the ease of use but also the number of potential users. The HTP lineshape model has been added to Labfit keeping it up-to-date with community standards. Recent analyses using labfit will be shown to demonstrate its ability to competently handle large experimental datasets, including high order lineshape effects, that are otherwise unmanageable.

Water permeability in hydrate-bearing sediments: A pore-scale study

NASA Astrophysics Data System (ADS)

Dai, Sheng; Seol, Yongkoo

2014-06-01

Permeability is a critical parameter governing methane flux and fluid flow in hydrate-bearing sediments; however, limited valid data are available due to experimental challenges. Here we investigate the relationship between apparent water permeability (k') and hydrate saturation (Sh), accounting for hydrate pore-scale growth habit and meso-scale heterogeneity. Results from capillary tube models rely on cross-sectional tube shapes and hydrate pore habits, thus are appropriate only for sediments with uniform hydrate distribution and known hydrate pore character. Given our pore network modeling results showing that accumulating hydrate in sediments decreases sediment porosity and increases hydraulic tortuosity, we propose a modified Kozeny-Carman model to characterize water permeability in hydrate-bearing sediments. This model agrees well with experimental results and can be easily implemented in reservoir simulators with no empirical variables other than Sh. Results are also relevant to flow through other natural sediments that undergo diagenesis, salt precipitation, or bio-clogging.

Protein Modelling: What Happened to the “Protein Structure Gap”?

PubMed Central

Schwede, Torsten

2013-01-01

Computational modeling and prediction of three-dimensional macromolecular structures and complexes from their sequence has been a long standing vision in structural biology as it holds the promise to bypass part of the laborious process of experimental structure solution. Over the last two decades, a paradigm shift has occurred: starting from a situation where the “structure knowledge gap” between the huge number of protein sequences and small number of known structures has hampered the widespread use of structure-based approaches in life science research, today some form of structural information – either experimental or computational – is available for the majority of amino acids encoded by common model organism genomes. Template based homology modeling techniques have matured to a point where they are now routinely used to complement experimental techniques. With the scientific focus of interest moving towards larger macromolecular complexes and dynamic networks of interactions, the integration of computational modeling methods with low-resolution experimental techniques allows studying large and complex molecular machines. Computational modeling and prediction techniques are still facing a number of challenges which hamper the more widespread use by the non-expert scientist. For example, it is often difficult to convey the underlying assumptions of a computational technique, as well as the expected accuracy and structural variability of a specific model. However, these aspects are crucial to understand the limitations of a model, and to decide which interpretations and conclusions can be supported. PMID:24010712

Mastitomics, the integrated omics of bovine milk in an experimental model of Streptococcus uberis mastitis: 3. Untargeted metabolomics.

PubMed

Thomas, Funmilola Clara; Mudaliar, Manikhandan; Tassi, Riccardo; McNeilly, Tom N; Burchmore, Richard; Burgess, Karl; Herzyk, Pawel; Zadoks, Ruth N; Eckersall, P David

2016-08-16

Intramammary infection leading to bovine mastitis is the leading disease problem affecting dairy cows and has marked effects on the milk produced by infected udder quarters. An experimental model of Streptococcus uberis mastitis has previously been investigated for clinical, immunological and pathophysiological alteration in milk, and has been the subject of peptidomic and quantitative proteomic investigation. The same sample set has now been investigated with a metabolomics approach using liquid chromatography and mass spectrometry. The analysis revealed over 3000 chromatographic peaks, of which 690 were putatively annotated with a metabolite. Hierarchical clustering analysis and principal component analysis demonstrated that metabolite changes due to S. uberis infection were maximal at 81 hours post challenge with metabolites in the milk from the resolution phase at 312 hours post challenge being closest to the pre-challenge samples. Metabolic pathway analysis revealed that the majority of the metabolites mapped to carbohydrate and nucleotide metabolism show a decreasing trend in concentration up to 81 hours post-challenge whereas an increasing trend was found in lipid metabolites and di-, tri- and tetra-peptides up to the same time point. The increase in these peptides coincides with an increase in larger peptides found in the previous peptidomic analysis and is likely to be due to protease degradation of milk proteins. Components of bile acid metabolism, linked to the FXR pathway regulating inflammation, were also increased. Metabolomic analysis of the response in milk during mastitis provides an essential component to the full understanding of the mammary gland's response to infection.

TAP score: torsion angle propensity normalization applied to local protein structure evaluation

PubMed Central

Tosatto, Silvio CE; Battistutta, Roberto

2007-01-01

Background Experimentally determined protein structures may contain errors and require validation. Conformational criteria based on the Ramachandran plot are mainly used to distinguish between distorted and adequately refined models. While the readily available criteria are sufficient to detect totally wrong structures, establishing the more subtle differences between plausible structures remains more challenging. Results A new criterion, called TAP score, measuring local sequence to structure fitness based on torsion angle propensities normalized against the global minimum and maximum is introduced. It is shown to be more accurate than previous methods at estimating the validity of a protein model in terms of commonly used experimental quality parameters on two test sets representing the full PDB database and a subset of obsolete PDB structures. Highly selective TAP thresholds are derived to recognize over 90% of the top experimental structures in the absence of experimental information. Both a web server and an executable version of the TAP score are available at . Conclusion A novel procedure for energy normalization (TAP) has significantly improved the possibility to recognize the best experimental structures. It will allow the user to more reliably isolate problematic structures in the context of automated experimental structure determination. PMID:17504537

A recombinant vesicular stomatitis virus-based Lassa fever vaccine protects guinea pigs and macaques against challenge with geographically and genetically distinct Lassa viruses.

PubMed

Safronetz, David; Mire, Chad; Rosenke, Kyle; Feldmann, Friederike; Haddock, Elaine; Geisbert, Thomas; Feldmann, Heinz

2015-04-01

Lassa virus (LASV) is endemic in several West African countries and is the etiological agent of Lassa fever. Despite the high annual incidence and significant morbidity and mortality rates, currently there are no approved vaccines to prevent infection or disease in humans. Genetically, LASV demonstrates a high degree of diversity that correlates with geographic distribution. The genetic heterogeneity observed between geographically distinct viruses raises concerns over the potential efficacy of a "universal" LASV vaccine. To date, several experimental LASV vaccines have been developed; however, few have been evaluated against challenge with various genetically unique Lassa virus isolates in relevant animal models. Here we demonstrate that a single, prophylactic immunization with a recombinant vesicular stomatitis virus (VSV) expressing the glycoproteins of LASV strain Josiah from Sierra Leone protects strain 13 guinea pigs from infection / disease following challenge with LASV isolates originating from Liberia, Mali and Nigeria. Similarly, the VSV-based LASV vaccine yields complete protection against a lethal challenge with the Liberian LASV isolate in the gold-standard macaque model of Lassa fever. Our results demonstrate the VSV-based LASV vaccine is capable of preventing morbidity and mortality associated with non-homologous LASV challenge in two animal models of Lassa fever. Additionally, this work highlights the need for the further development of disease models for geographical distinct LASV strains, particularly those from Nigeria, in order to comprehensively evaluate potential vaccines and therapies against this prominent agent of viral hemorrhagic fever.

Advances and challenges in logical modeling of cell cycle regulation: perspective for multi-scale, integrative yeast cell models

PubMed Central

Todd, Robert G.; van der Zee, Lucas

2016-01-01

Abstract The eukaryotic cell cycle is robustly designed, with interacting molecules organized within a definite topology that ensures temporal precision of its phase transitions. Its underlying dynamics are regulated by molecular switches, for which remarkable insights have been provided by genetic and molecular biology efforts. In a number of cases, this information has been made predictive, through computational models. These models have allowed for the identification of novel molecular mechanisms, later validated experimentally. Logical modeling represents one of the youngest approaches to address cell cycle regulation. We summarize the advances that this type of modeling has achieved to reproduce and predict cell cycle dynamics. Furthermore, we present the challenge that this type of modeling is now ready to tackle: its integration with intracellular networks, and its formalisms, to understand crosstalks underlying systems level properties, ultimate aim of multi-scale models. Specifically, we discuss and illustrate how such an integration may be realized, by integrating a minimal logical model of the cell cycle with a metabolic network. PMID:27993914

Modelling High-temperature EBPR by Incorporating Glycogen and GAOs: Challenges from a Preliminary Study.

PubMed

Liau, Kee Fui; Yeoh, Hak Koon; Shoji, Tadashi; Chua, Adeline Seak May; Ho, Pei Yee

2017-01-01

  Recently reported kinetic and stoichiometric parameters of the Activated Sludge Model no. 2d (ASM2d) for high-temperature EBPR processes suggested that the absence of glycogen in the model contributed to underestimation of PHA accumulation at 32 °C. Here, two modified ASM2d models were used to further explore the contribution of glycogen in the process. The ASM2d-1G model incorporated glycogen metabolism by PAOs (polyphosphate-accumulating organisms), while the ASM2d-2G model further included processes by GAOs (glycogen-accumulating organisms). These models were calibrated and validated using experimental data at 32 °C. The ASM2d-1G model supported the hypothesis that the excess PHA was attributed to glycogen, but remained inadequate to capture the dynamics of glycogen without considering GAOs activities. The ASM2d-2G model performed better, but it was challenging to calibrate as it often led to wash-out of either PAOs or GAOs. Associated hurdles are highlighted and additional efforts in calibrating ASM2d-2G more effectively are proposed.

High salt intake does not exacerbate murine autoimmune thyroiditis

PubMed Central

Kolypetri, P; Randell, E; Van Vliet, B N; Carayanniotis, G

2014-01-01

Recent studies have shown that high salt (HS) intake exacerbates experimental autoimmune encephalomyelitis and have raised the possibility that a HS diet may comprise a risk factor for autoimmune diseases in general. In this report, we have examined whether a HS diet regimen could exacerbate murine autoimmune thyroiditis, including spontaneous autoimmune thyroiditis (SAT) in non-obese diabetic (NOD.H2h4) mice, experimental autoimmune thyroiditis (EAT) in C57BL/6J mice challenged with thyroglobulin (Tg) and EAT in CBA/J mice challenged with the Tg peptide (2549–2560). The physiological impact of HS intake was confirmed by enhanced water consumption and suppressed aldosterone levels in all strains. However, the HS treatment failed to significantly affect the incidence and severity of SAT or EAT or Tg-specific immunoglobulin (Ig)G levels, relative to control mice maintained on a normal salt diet. In three experimental models, these data demonstrate that HS intake does not exacerbate autoimmune thyroiditis, indicating that a HS diet is not a risk factor for all autoimmune diseases. PMID:24528002

Increasing drought and diminishing benefits of elevated carbon dioxide for soybean yields across the US Midwest.

PubMed

Jin, Zhenong; Ainsworth, Elizabeth A; Leakey, Andrew D B; Lobell, David B

2018-02-01

Elevated atmospheric CO 2 concentrations ([CO 2 ]) are expected to increase C3 crop yield through the CO 2 fertilization effect (CFE) by stimulating photosynthesis and by reducing stomatal conductance and transpiration. The latter effect is widely believed to lead to greater benefits in dry rather than wet conditions, although some recent experimental evidence challenges this view. Here we used a process-based crop model, the Agricultural Production Systems sIMulator (APSIM), to quantify the contemporary and future CFE on soybean in one of its primary production area of the US Midwest. APSIM accurately reproduced experimental data from the Soybean Free-Air CO 2 Enrichment site showing that the CFE declined with increasing drought stress. This resulted from greater radiation use efficiency (RUE) and above-ground biomass production at elevated [CO 2 ] that outpaced gains in transpiration efficiency (TE). Using an ensemble of eight climate model projections, we found that drought frequency in the US Midwest is projected to increase from once every 5 years currently to once every other year by 2050. In addition to directly driving yield loss, greater drought also significantly limited the benefit from rising [CO 2 ]. This study provides a link between localized experiments and regional-scale modeling to highlight that increased drought frequency and severity pose a formidable challenge to maintaining soybean yield progress that is not offset by rising [CO 2 ] as previously anticipated. Evaluating the relative sensitivity of RUE and TE to elevated [CO 2 ] will be an important target for future modeling and experimental studies of climate change impacts and adaptation in C3 crops. © 2017 John Wiley & Sons Ltd.

Neuro-immune interactions of neural stem cell transplants: From animal disease models to human trials

PubMed Central

Cossetti, Chiara; Pluchino, Stefano

2014-01-01

Stem cell technology is a promising branch of regenerative medicine that is aimed at developing new approaches for the treatment of severely debilitating human diseases, including those affecting the central nervous system (CNS). Despite the increasing understanding of the mechanisms governing their biology, the application of stem cell therapeutics remains challenging. The initial idea that stem cell transplants work in vivo via the replacement of endogenous cells lost or damaged owing to disease has been challenged by accumulating evidence of their therapeutic plasticity. This new concept covers the remarkable immune regulatory and tissue trophic effects that transplanted stem cells exert at the level of the neural microenvironment to promote tissue healing via combination of immune modulatory and tissue protective actions, while retaining predominantly undifferentiated features. Among a number of promising candidate stem cell sources, neural stem/precursor cells (NPCs) are under extensive investigation with regard to their therapeutic plasticity after transplantation. The significant impact in vivo of experimental NPC therapies in animal models of inflammatory CNS diseases has raised great expectations that these stem cells, or the manipulation of the mechanisms behind their therapeutic impact, could soon be translated to human studies. This review aims to provide an update on the most recent evidence of therapeutically-relevant neuroimmune interactions following NPC transplants in animal models of multiple sclerosis, cerebral stroke and traumas of the spinal cord, and consideration of the forthcoming challenges related to the early translation of some of these exciting experimental outcomes into clinical medicines. PMID:23507035

Neuro-immune interactions of neural stem cell transplants: from animal disease models to human trials.

PubMed

Giusto, Elena; Donegà, Matteo; Cossetti, Chiara; Pluchino, Stefano

2014-10-01

Stem cell technology is a promising branch of regenerative medicine that is aimed at developing new approaches for the treatment of severely debilitating human diseases, including those affecting the central nervous system (CNS). Despite the increasing understanding of the mechanisms governing their biology, the application of stem cell therapeutics remains challenging. The initial idea that stem cell transplants work in vivo via the replacement of endogenous cells lost or damaged owing to disease has been challenged by accumulating evidence of their therapeutic plasticity. This new concept covers the remarkable immune regulatory and tissue trophic effects that transplanted stem cells exert at the level of the neural microenvironment to promote tissue healing via combination of immune modulatory and tissue protective actions, while retaining predominantly undifferentiated features. Among a number of promising candidate stem cell sources, neural stem/precursor cells (NPCs) are under extensive investigation with regard to their therapeutic plasticity after transplantation. The significant impact in vivo of experimental NPC therapies in animal models of inflammatory CNS diseases has raised great expectations that these stem cells, or the manipulation of the mechanisms behind their therapeutic impact, could soon be translated to human studies. This review aims to provide an update on the most recent evidence of therapeutically-relevant neuro-immune interactions following NPC transplants in animal models of multiple sclerosis, cerebral stroke and traumas of the spinal cord, and consideration of the forthcoming challenges related to the early translation of some of these exciting experimental outcomes into clinical medicines. Copyright © 2013 Elsevier Inc. All rights reserved.

Anti-Ebola therapies based on monoclonal antibodies: Current state and challenges ahead

PubMed Central

González-González, E; Alvarez, MM; Márquez-Ipiña, AR; Santiago, G Trujillo-de; Rodríguez-Martínez, LM; Annabi, N; Khademhosseini, A

2017-01-01

The 2014 Ebola outbreak, the largest recorded, took us largely unprepared, with no available vaccine or specific treatment. In this context, the World Health Organization (WHO) declared that the humanitarian use of experimental therapies against Ebola Virus (EBOV) is ethical. In particular, an experimental treatment consisting of a cocktail of three monoclonal antibodies (mAbs) produced in tobacco plants and specifically directed to the Ebola virus glycoprotein (GP) was tested in humans, apparently with good results. Several mAbs with high affinity to the GP have been described. This review discusses our current knowledge on this topic. Particular emphasis is devoted to those mAbs that have been assayed in animal models or humans as possible therapies against Ebola. Engineering aspects and challenges for the production of anti-Ebola mAbs are also briefly discussed; current platforms for the design and production of full-length mAbs are cumbersome and costly. PMID:26611830

The Challenge of Reproducibility and Accuracy in Nutrition Research: Resources and Pitfalls1234

PubMed Central

Kuszak, Adam J; Williamson, John S; Hopp, D Craig; Betz, Joseph M

2016-01-01

Inconsistent and contradictory results from nutrition studies conducted by different investigators continue to emerge, in part because of the inherent variability of natural products, as well as the unknown and therefore uncontrolled variables in study populations and experimental designs. Given these challenges inherent in nutrition research, it is critical for the progress of the field that researchers strive to minimize variability within studies and enhance comparability between studies by optimizing the characterization, control, and reporting of products, reagents, and model systems used, as well as the rigor and reporting of experimental designs, protocols, and data analysis. Here we describe some recent developments relevant to research on plant-derived products used in nutrition research, highlight some resources for optimizing the characterization and reporting of research using these products, and describe some of the pitfalls that may be avoided by adherence to these recommendations. PMID:26980822

Creation and manipulation of topological states in chiral nematic microspheres

PubMed Central

Orlova, Tetiana; Aßhoff, Sarah Jane; Yamaguchi, Tadatsugu; Katsonis, Nathalie; Brasselet, Etienne

2015-01-01

Topology is a universal concept that is encountered in daily life and is known to determine many static and dynamical properties of matter. Taming and controlling the topology of materials therefore constitutes a contemporary interdisciplinary challenge. Building on the controllable spatial properties of soft matter appears as a relevant strategy to address the challenge, in particular, because it may lead to paradigmatic model systems that allow checking theories experimentally. Here we report experimentally on a wealth of complex free-standing metastable topological architectures at the micron scale, in frustrated chiral nematic droplets. These results support recent works predicting the formation of free-standing knotted and linked disclination structures in confined chiral nematic fluids. We also demonstrate that various kinds of external fields (thermal, electrical and optical) can be used to achieve topological remote control. All this may foster the development of new devices based on topologically structured soft media. PMID:26145716

Reaction Mechanisms on Multiwell Potential Energy Surfaces in Combustion (and Atmospheric) Chemistry

DOE PAGES

Osborn, David L.

2017-03-15

Chemical reactions occurring on a potential energy surface with multiple wells are ubiquitous in low temperature combustion and the oxidation of volatile organic compounds in earth’s atmosphere. The rich variety of structural isomerizations that compete with collisional stabilization make characterizing such complex-forming reactions challenging. This review describes recent experimental and theoretical advances that deliver increasingly complete views of their reaction mechanisms. New methods for creating reactive intermediates coupled with multiplexed measurements provide many experimental observables simultaneously. Automated methods to explore potential energy surfaces can uncover hidden reactive pathways, while master equation methods enable a holistic treatment of both sequential andmore » well-skipping pathways. Our ability to probe and understand nonequilibrium effects and reaction sequences is increasing. These advances provide the fundamental science base for predictive models of combustion and the atmosphere that are crucial to address global challenges.« less

Anti-Ebola therapies based on monoclonal antibodies: current state and challenges ahead.

PubMed

González-González, Everardo; Alvarez, Mario Moisés; Márquez-Ipiña, Alan Roberto; Trujillo-de Santiago, Grissel; Rodríguez-Martínez, Luis Mario; Annabi, Nasim; Khademhosseini, Ali

2017-02-01

The 2014 Ebola outbreak, the largest recorded, took us largely unprepared, with no available vaccine or specific treatment. In this context, the World Health Organization declared that the humanitarian use of experimental therapies against Ebola Virus (EBOV) is ethical. In particular, an experimental treatment consisting of a cocktail of three monoclonal antibodies (mAbs) produced in tobacco plants and specifically directed to the EBOV glycoprotein (GP) was tested in humans, apparently with good results. Several mAbs with high affinity to the GP have been described. This review discusses our current knowledge on this topic. Particular emphasis is devoted to those mAbs that have been assayed in animal models or humans as possible therapies against Ebola. Engineering aspects and challenges for the production of anti-Ebola mAbs are also briefly discussed; current platforms for the design and production of full-length mAbs are cumbersome and costly.

Creation and manipulation of topological states in chiral nematic microspheres

NASA Astrophysics Data System (ADS)

Orlova, Tetiana; Aßhoff, Sarah Jane; Yamaguchi, Tadatsugu; Katsonis, Nathalie; Brasselet, Etienne

2015-07-01

Topology is a universal concept that is encountered in daily life and is known to determine many static and dynamical properties of matter. Taming and controlling the topology of materials therefore constitutes a contemporary interdisciplinary challenge. Building on the controllable spatial properties of soft matter appears as a relevant strategy to address the challenge, in particular, because it may lead to paradigmatic model systems that allow checking theories experimentally. Here we report experimentally on a wealth of complex free-standing metastable topological architectures at the micron scale, in frustrated chiral nematic droplets. These results support recent works predicting the formation of free-standing knotted and linked disclination structures in confined chiral nematic fluids. We also demonstrate that various kinds of external fields (thermal, electrical and optical) can be used to achieve topological remote control. All this may foster the development of new devices based on topologically structured soft media.

Reaction Mechanisms on Multiwell Potential Energy Surfaces in Combustion (and Atmospheric) Chemistry

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

Osborn, David L.

Chemical reactions occurring on a potential energy surface with multiple wells are ubiquitous in low temperature combustion and the oxidation of volatile organic compounds in earth’s atmosphere. The rich variety of structural isomerizations that compete with collisional stabilization make characterizing such complex-forming reactions challenging. This review describes recent experimental and theoretical advances that deliver increasingly complete views of their reaction mechanisms. New methods for creating reactive intermediates coupled with multiplexed measurements provide many experimental observables simultaneously. Automated methods to explore potential energy surfaces can uncover hidden reactive pathways, while master equation methods enable a holistic treatment of both sequential andmore » well-skipping pathways. Our ability to probe and understand nonequilibrium effects and reaction sequences is increasing. These advances provide the fundamental science base for predictive models of combustion and the atmosphere that are crucial to address global challenges.« less

Expanding a dynamic flux balance model of yeast fermentation to genome-scale

PubMed Central

2011-01-01

Background Yeast is considered to be a workhorse of the biotechnology industry for the production of many value-added chemicals, alcoholic beverages and biofuels. Optimization of the fermentation is a challenging task that greatly benefits from dynamic models able to accurately describe and predict the fermentation profile and resulting products under different genetic and environmental conditions. In this article, we developed and validated a genome-scale dynamic flux balance model, using experimentally determined kinetic constraints. Results Appropriate equations for maintenance, biomass composition, anaerobic metabolism and nutrient uptake are key to improve model performance, especially for predicting glycerol and ethanol synthesis. Prediction profiles of synthesis and consumption of the main metabolites involved in alcoholic fermentation closely agreed with experimental data obtained from numerous lab and industrial fermentations under different environmental conditions. Finally, fermentation simulations of genetically engineered yeasts closely reproduced previously reported experimental results regarding final concentrations of the main fermentation products such as ethanol and glycerol. Conclusion A useful tool to describe, understand and predict metabolite production in batch yeast cultures was developed. The resulting model, if used wisely, could help to search for new metabolic engineering strategies to manage ethanol content in batch fermentations. PMID:21595919

Transverse momentum spectra of hadrons in p + p collisions at CERN SPS energies from the UrQMD transport model

NASA Astrophysics Data System (ADS)

Ozvenchuk, V.; Rybicki, A.

2018-05-01

The UrQMD transport model, version 3.4, is used to study the new experimental data on transverse momentum spectra of π±, K±, p and p bar produced in inelastic p + p interactions at SPS energies, recently published by the NA61/SHINE Collaboration. The comparison of model predictions to these new measurements is presented as a function of collision energy for central and forward particle rapidity intervals. In addition, the inverse slope parameters characterizing the transverse momentum distributions are extracted from the predicted spectra and compared to the corresponding values obtained from NA61/SHINE distributions, as a function of particle rapidity and collision energy. A complex pattern of deviations between the experimental data and the UrQMD model emerges. For charged pions, the fair agreement visible at top SPS energies deteriorates with the decreasing energy. For charged K mesons, UrQMD significantly underpredicts positive kaon production at lower beam momenta. It also underpredicts the central rapidity proton yield at top collision energy and overpredicts antiproton production at all considered energies. We conclude that the new experimental data analyzed in this paper still constitute a challenge for the present version of the model.

Recent mouse and rat methods for the study of experimental oral candidiasis

PubMed Central

Costa, Anna CBP; Pereira, Cristiane A; Junqueira, Juliana C; Jorge, Antonio OC

2013-01-01

The Candida genus expresses virulence factors that, when combined with immunosuppression and other risk factors, can cause different manifestations of oral candidiasis. The treatment of mucosal infections caused by Candida and the elucidation of the disease process have proven challenging. Therefore, the study of experimentally induced oral candidiasis in rats and mice is useful to clarify the etiopathology of this condition, improve diagnosis, and search for new therapeutic options because the disease process in these animals is similar to that of human candidiasis lesions. Here, we describe and discuss new studies involving rat and mouse models of oral candidiasis with respect to methods for inducing experimental infection, methods for evaluating the development of experimental candidiasis, and new treatment strategies for oral candidiasis. PMID:23715031

Deriving habitat models for northern long-eared bats from historical detection data: a case study using the Fernow Experimental Forest

Treesearch

W. Mark Ford; Alexander Silvis; Jane L. Rodrigue; Andrew B. Kniowski; Joshua B. Johnson

2016-01-01

The listing of the northern long-eared bat (Myotis septentrionalis) as federally threatened under the Endangered Species Act following severe population declines from white-nose syndrome presents considerable challenges to natural resource managers. Because the northern long-eared bat is a forest habitat generalist, development of effective...

Hydrological Modeling in Alaska with WRF-Hydro

NASA Astrophysics Data System (ADS)

Elmer, N. J.; Zavodsky, B.; Molthan, A.

2017-12-01

The operational National Water Model (NWM), implemented in August 2016, is an instantiation of the Weather Research and Forecasting hydrological extension package (WRF-Hydro). Currently, the NWM only covers the contiguous United States, but will be expanded to include an Alaska domain in the future. It is well known that Alaska presents several hydrological modeling challenges, including unique arctic/sub-arctic hydrological processes not observed elsewhere in the United States and a severe lack of in-situ observations for model initialization. This project sets up an experimental version of WRF-Hydro in Alaska mimicking the NWM to gauge the ability of WRF-Hydro to represent hydrological processes in Alaska and identify model calibration challenges. Recent and upcoming launches of hydrology-focused NASA satellite missions such as the Soil Moisture Active Passive (SMAP) and Surface Water Ocean Topography (SWOT) expand the spatial and temporal coverage of observations in Alaska, so this study also lays the groundwork for assimilating these NASA datasets into WRF-Hydro in the future.

CHARACTERIZATION OF VIRULENCE OF Leptospira ISOLATES IN A HAMSTER MODEL

PubMed Central

Silva, Éverton F.; Santos, Cleiton S.; Athanazio, Daniel A.; Seyffert, Núbia; Seixas, Fabiana K.; Cerqueira, Gustavo M.; Fagundes, Michel Q.; Brod, Claudiomar S.; Reis, Mitermayer G.; Dellagostin, Odir A.; Ko, Albert I.

2008-01-01

Effort has been made to identify protective antigens in order to develop a recombinant vaccine against leptospirosis. Several attempts failed to conclusively demonstrate efficacy of vaccine candidates due to the lack of an appropriate model of lethal leptospirosis. The purposes of our study were: (i) to test the virulence of leptospiral isolates from Brazil, which are representative of important serogroups that cause disease in humans and animals; and (ii) to standardize the lethal dose 50% (LD50) for each of the virulent strains using a hamster (Mesocricetus auratus) model. Five of seven Brazilian isolates induced lethality in a hamster model, with inocula lower than 200 leptospires. Histopathological examination of infected animals showed typical lesions found in both natural and experimental leptospirosis. Results described here demonstrated the potential use of Brazilian isolates as highly virulent strains in challenge experiments using hamster as an appropriate animal model for leptospirosis. Furthermore these strains may be useful in heterologous challenge studies which aim to evaluate cross-protective responses induced by subunit vaccine candidates. PMID:18547690

The implementation of non-Voigt line profiles in the HITRAN database: H2 case study

NASA Astrophysics Data System (ADS)

Wcisło, P.; Gordon, I. E.; Tran, H.; Tan, Y.; Hu, S.-M.; Campargue, A.; Kassi, S.; Romanini, D.; Hill, C.; Kochanov, R. V.; Rothman, L. S.

2016-07-01

Experimental capabilities of molecular spectroscopy and its applications nowadays require a sub-percent or even sub-per mille accuracy of the representation of the shapes of molecular transitions. This implies the necessity of using more advanced line-shape models which are characterized by many more parameters than a simple Voigt profile. It is a great challenge for modern molecular spectral databases to store and maintain the extended set of line-shape parameters as well as their temperature dependences. It is even more challenging to reliably retrieve these parameters from experimental spectra over a large range of pressures and temperatures. In this paper we address this problem starting from the case of the H2 molecule for which the non-Voigt line-shape effects are exceptionally pronounced. For this purpose we reanalyzed the experimental data reported in the literature. In particular, we performed detailed line-shape analysis of high-quality spectra obtained with cavity-enhanced techniques. We also report the first high-quality cavity-enhanced measurement of the H2 fundamental vibrational mode. We develop a correction to the Hartmann-Tran profile (HTP) which adjusts the HTP to the particular model of the velocity-changing collisions. This allows the measured spectra to be better represented over a wide range of pressures. The problem of storing the HTP parameters in the HITRAN database together with their temperature dependences is also discussed.

A Combination of Hand-held Models and Computer Imaging Programs Helps Students Answer Oral Questions about Molecular Structure and Function: A Controlled Investigation of Student Learning

PubMed Central

Peck, Ronald F.; Colton, Shannon; Morris, Jennifer; Chaibub Neto, Elias; Kallio, Julie

2009-01-01

We conducted a controlled investigation to examine whether a combination of computer imagery and tactile tools helps introductory cell biology laboratory undergraduate students better learn about protein structure/function relationships as compared with computer imagery alone. In all five laboratory sections, students used the molecular imaging program, Protein Explorer (PE). In the three experimental sections, three-dimensional physical models were made available to the students, in addition to PE. Student learning was assessed via oral and written research summaries and videotaped interviews. Differences between the experimental and control group students were not found in our typical course assessments such as research papers, but rather were revealed during one-on-one interviews with students at the end of the semester. A subset of students in the experimental group produced superior answers to some higher-order interview questions as compared with students in the control group. During the interview, students in both groups preferred to use either the hand-held models alone or in combination with the PE imaging program. Students typically did not use any tools when answering knowledge (lower-level thinking) questions, but when challenged with higher-level thinking questions, students in both the control and experimental groups elected to use the models. PMID:19255134

Thermal-to-visible face recognition using partial least squares.

PubMed

Hu, Shuowen; Choi, Jonghyun; Chan, Alex L; Schwartz, William Robson

2015-03-01

Although visible face recognition has been an active area of research for several decades, cross-modal face recognition has only been explored by the biometrics community relatively recently. Thermal-to-visible face recognition is one of the most difficult cross-modal face recognition challenges, because of the difference in phenomenology between the thermal and visible imaging modalities. We address the cross-modal recognition problem using a partial least squares (PLS) regression-based approach consisting of preprocessing, feature extraction, and PLS model building. The preprocessing and feature extraction stages are designed to reduce the modality gap between the thermal and visible facial signatures, and facilitate the subsequent one-vs-all PLS-based model building. We incorporate multi-modal information into the PLS model building stage to enhance cross-modal recognition. The performance of the proposed recognition algorithm is evaluated on three challenging datasets containing visible and thermal imagery acquired under different experimental scenarios: time-lapse, physical tasks, mental tasks, and subject-to-camera range. These scenarios represent difficult challenges relevant to real-world applications. We demonstrate that the proposed method performs robustly for the examined scenarios.

Vaxar: A Web-Based Database of Laboratory Animal Responses to Vaccinations and Its Application in the Meta-Analysis of Different Animal Responses to Tuberculosis Vaccinations

PubMed Central

Todd, Thomas; Dunn, Natalie; Xiang, Zuoshuang; He, Yongqun

2016-01-01

Animal models are indispensable for vaccine research and development. However, choosing which species to use and designing a vaccine study that is optimized for that species is often challenging. Vaxar (http://www.violinet.org/vaxar/) is a web-based database and analysis system that stores manually curated data regarding vaccine-induced responses in animals. To date, Vaxar encompasses models from 35 animal species including rodents, rabbits, ferrets, primates, and birds. These 35 species have been used to study more than 1300 experimentally tested vaccines for 164 pathogens and diseases significant to humans and domestic animals. The responses to vaccines by animals in more than 1500 experimental studies are recorded in Vaxar; these data can be used for systematic meta-analysis of various animal responses to a particular vaccine. For example, several variables, including animal strain, animal age, and the dose or route of either vaccination or challenge, might affect host response outcomes. Vaxar can also be used to identify variables that affect responses to different vaccines in a specific animal model. All data stored in Vaxar are publically available for web-based queries and analyses. Overall Vaxar provides a unique systematic approach for understanding vaccine-induced host immunity. PMID:27053566

Three-dimensional organotypic culture: experimental models of mammalian biology and disease

PubMed Central

Shamir, Eliah R.; Ewald, Andrew J.

2015-01-01

Mammalian organs are challenging to study as they are fairly inaccessible to experimental manipulation and optical observation. Recent advances in three-dimensional (3D) culture techniques, coupled with the ability to independently manipulate genetic and microenvironmental factors, have enabled the real-time study of mammalian tissues. These systems have been used to visualize the cellular basis of epithelial morphogenesis, to test the roles of specific genes in regulating cell behaviours within epithelial tissues and to elucidate the contribution of microenvironmental factors to normal and disease processes. Collectively, these novel models can be used to answer fundamental biological questions and generate replacement human tissues, and they enable testing of novel therapeutic approaches, often using patient-derived cells. PMID:25237826

Lateral organization, bilayer asymmetry, and inter-leaflet coupling of biological membranes

DOE PAGES

Smith, Jeremy C.; Cheng, Xiaolin; Nickels, Jonathan D.

2015-07-29

Understanding of cell membrane organization has evolved significantly from the classic fluid mosaic model. It is now recognized that biological membranes are highly organized structures, with differences in lipid compositions between inner and outer leaflets and in lateral structures within the bilayer plane, known as lipid rafts. These organizing principles are important for protein localization and function as well as cellular signaling. However, the mechanisms and biophysical basis of lipid raft formation, structure, dynamics and function are not clearly understood. One key question, which we focus on in this review, is how lateral organization and leaflet compositional asymmetry are coupled.more » Detailed information elucidating this question has been sparse because of the small size and transient nature of rafts and the experimental challenges in constructing asymmetric bilayers. Resolving this mystery will require advances in both experimentation and modeling. We discuss here the preparation of model systems along with experimental and computational approaches that have been applied in efforts to address this key question in membrane biology. Furthermore, we seek to place recent and future advances in experimental and computational techniques in context, providing insight into in-plane and transverse organization of biological membranes.« less

Advances in modelling of condensation phenomena

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

Liu, W.S.; Zaltsgendler, E.; Hanna, B.

1997-07-01

The physical parameters in the modelling of condensation phenomena in the CANDU reactor system codes are discussed. The experimental programs used for thermal-hydraulic code validation in the Canadian nuclear industry are briefly described. The modelling of vapour generation and in particular condensation plays a key role in modelling of postulated reactor transients. The condensation models adopted in the current state-of-the-art two-fluid CANDU reactor thermal-hydraulic system codes (CATHENA and TUF) are described. As examples of the modelling challenges faced, the simulation of a cold water injection experiment by CATHENA and the simulation of a condensation induced water hammer experiment by TUFmore » are described.« less

Modeling Tumor Clonal Evolution for Drug Combinations Design.

PubMed

Zhao, Boyang; Hemann, Michael T; Lauffenburger, Douglas A

2016-03-01

Cancer is a clonal evolutionary process. This presents challenges for effective therapeutic intervention, given the constant selective pressure towards drug resistance. Mathematical modeling from population genetics, evolutionary dynamics, and engineering perspectives are being increasingly employed to study tumor progression, intratumoral heterogeneity, drug resistance, and rational drug scheduling and combinations design. In this review, we discuss promising opportunities these inter-disciplinary approaches hold for advances in cancer biology and treatment. We propose that quantitative modeling perspectives can complement emerging experimental technologies to facilitate enhanced understanding of disease progression and improved capabilities for therapeutic drug regimen designs.

Theoretical models for the regulation of DNA replication in fast-growing bacteria

NASA Astrophysics Data System (ADS)

Creutziger, Martin; Schmidt, Mischa; Lenz, Peter

2012-09-01

Growing in always changing environments, Escherichia coli cells are challenged by the task to coordinate growth and division. In particular, adaption of their growth program to the surrounding medium has to guarantee that the daughter cells obtain fully replicated chromosomes. Replication is therefore to be initiated at the right time, which is particularly challenging in media that support fast growth. Here, the mother cell initiates replication not only for the daughter but also for the granddaughter cells. This is possible only if replication occurs from several replication forks that all need to be correctly initiated. Despite considerable efforts during the last 40 years, regulation of this process is still unknown. Part of the difficulty arises from the fact that many details of the relevant molecular processes are not known. Here, we develop a novel theoretical strategy for dealing with this general problem: instead of analyzing a single model, we introduce a wide variety of 128 different models that make different assumptions about the unknown processes. By comparing the predictions of these models we are able to identify the key quantities that allow the experimental discrimination of the different models. Analysis of these quantities yields that out of the 128 models 94 are not consistent with available experimental data. From the remaining 34 models we are able to conclude that mass growth and DNA replication need either to be truly coupled, by coupling DNA replication initiation to the event of cell division, or to the amount of accumulated mass. Finally, we make suggestions for experiments to further reduce the number of possible regulation scenarios.

Simulating immersed particle collisions: the Devil's in the details

NASA Astrophysics Data System (ADS)

Biegert, Edward; Vowinckel, Bernhard; Meiburg, Eckart

2015-11-01

Simulating densely-packed particle-laden flows with any degree of confidence requires accurate modeling of particle-particle collisions. To this end, we investigate a few collision models from the fluids and granular flow communities using sphere-wall collisions, which have been studied by a number of experimental groups. These collisions involve enough complexities--gravity, particle-wall lubrication forces, particle-wall contact stresses, particle-wake interactions--to challenge any collision model. Evaluating the successes and shortcomings of the collision models, we seek improvements in order to obtain more consistent results. We will highlight several implementation details that are crucial for obtaining accurate results.

Pharmacotherapy in Generalized Anxiety Disorder: Novel Experimental Medicine Models and Emerging Drug Targets.

PubMed

Baldwin, David S; Hou, Ruihua; Gordon, Robert; Huneke, Nathan T M; Garner, Matthew

2017-04-01

Many pharmacological and psychological approaches have been found efficacious in patients with generalized anxiety disorder (GAD), but many treatment-seeking patients will not respond and others will relapse despite continuing with interventions that initially had beneficial effects. Other patients will respond but then stop treatment early because of untoward effects such as sexual dysfunction, drowsiness, and weight gain. There is much scope for the development of novel approaches that could have greater overall effectiveness or acceptability than currently available interventions or that have particular effectiveness in specific clinical subgroups. 'Experimental medicine' studies in healthy volunteers model disease states and represent a proof-of-concept approach for the development of novel therapeutic interventions: they determine whether to proceed to pivotal efficacy studies and so can reduce delays in translating innovations into clinical practice. Investigations in healthy volunteers challenged with the inhalation of air 'enriched' with 7.5% carbon dioxide (CO 2 ) indicate this technique provides a validated and robust experimental medicine model, mirroring the subjective, autonomic, and cognitive features of GAD. The anxiety response during CO 2 challenge probably involves both central noradrenergic neurotransmission and effects on acid-base sensitive receptors and so may stimulate development of novel agents targeted at central chemosensors. Increasing awareness of the potential role of altered cytokine balance in anxiety and the interplay of cytokines with monoaminergic mechanisms may also encourage the investigation of novel agents with modulating effects on immunological profiles. Although seemingly disparate, these two approaches to treatment development may pivot on a shared mechanism in exerting anxiolytic-like effects through pharmacological effects on acid-sensing ion channels.

In a bovine model of onchocerciasis, protective immunity exists naturally, is absent in drug-cured hosts, and is induced by vaccination

PubMed Central

Tchakouté, Virginia L.; Graham, Simon P.; Jensen, Siv Aina; Makepeace, Benjamin L.; Nfon, Charles K.; Njongmeta, Leo M.; Lustigman, Sara; Enyong, Peter A.; Tanya, Vincent N.; Bianco, Albert E.; Trees, Alexander J.

2006-01-01

Onchocerciasis (river blindness) is a major parasitic disease of humans in sub-Saharan Africa caused by the microfilarial stage of the nematode Onchocerca volvulus. Using Onchocerca ochengi, a closely related species which infects cattle and is transmitted by the same black fly vector (Simulium damnosum sensu lato) as O. volvulus, we have conducted longitudinal studies after either natural field exposure or experimental infection to determine whether, and under what circumstances, protective immunity exists in onchocerciasis. On the basis of the adult worm burdens (nodules) observed, we determined that cattle reared in endemic areas without detectable parasites (putatively immune) were significantly less susceptible to heavy field challenge than age-matched, naïve controls (P = 0.002), whereas patently infected cattle, cured of infection by adulticide treatment with melarsomine, were fully susceptible. Cattle immunized with irradiated third-stage larvae were significantly protected against experimental challenge (100% reduction in median nodule load, P = 0.003), and vaccination also conferred resistance to severe and prolonged field challenge (64% reduction in median nodule load, P = 0.053; and a significant reduction in microfilarial positivity rates and density, P < 0.05). These results constitute evidence of protective immunity in a naturally evolved host–Onchocerca sp. relationship and provide proof-of-principle for immunoprophylaxis under experimental and field conditions. PMID:16585501

Fusion power: a challenge for materials science.

PubMed

Duffy, D M

2010-07-28

The selection and design of materials that will withstand the extreme conditions of a fusion power plant has been described as one of the greatest materials science challenges in history. The high particle flux, high thermal load, thermal mechanical stress and the production of transmutation elements combine to produce a uniquely hostile environment. In this paper, the materials favoured for the diverse roles in a fusion power plant are discussed, along with the experimental and modelling techniques that are used to advance the understanding of radiation damage in materials. Areas where further research is necessary are highlighted.

The Shigella human challenge model.

PubMed

Porter, C K; Thura, N; Ranallo, R T; Riddle, M S

2013-02-01

Shigella is an important bacterial cause of infectious diarrhoea globally. The Shigella human challenge model has been used since 1946 for a variety of objectives including understanding disease pathogenesis, human immune responses and allowing for an early assessment of vaccine efficacy. A systematic review of the literature regarding experimental shigellosis in human subjects was conducted. Summative estimates were calculated by strain and dose. While a total of 19 studies evaluating nine strains at doses ranging from 10 to 1 × 1010 colony-forming units were identified, most studies utilized the S. sonnei strain 53G and the S. flexneri strain 2457T. Inoculum solution and pre-inoculation buffering has varied over time although diarrhoea attack rates do not appear to increase above 75-80%, and dysentery rates remain fairly constant, highlighting the need for additional dose-ranging studies. Expansion of the model to include additional strains from different serotypes will elucidate serotype and strain-specific outcome variability.

Optimal experimental designs for fMRI when the model matrix is uncertain.

PubMed

Kao, Ming-Hung; Zhou, Lin

2017-07-15

This study concerns optimal designs for functional magnetic resonance imaging (fMRI) experiments when the model matrix of the statistical model depends on both the selected stimulus sequence (fMRI design), and the subject's uncertain feedback (e.g. answer) to each mental stimulus (e.g. question) presented to her/him. While practically important, this design issue is challenging. This mainly is because that the information matrix cannot be fully determined at the design stage, making it difficult to evaluate the quality of the selected designs. To tackle this challenging issue, we propose an easy-to-use optimality criterion for evaluating the quality of designs, and an efficient approach for obtaining designs optimizing this criterion. Compared with a previously proposed method, our approach requires a much less computing time to achieve designs with high statistical efficiencies. Copyright © 2017 Elsevier Inc. All rights reserved.

A constitutive framework for modelling thin incompressible viscoelastic materials under plane stress in the finite strain regime

NASA Astrophysics Data System (ADS)

Kroon, M.

2011-11-01

Rubbers and soft biological tissues may undergo large deformations and are also viscoelastic. The formulation of constitutive models for these materials poses special challenges. In several applications, especially in biomechanics, these materials are also relatively thin, implying that in-plane stresses dominate and that plane stress may therefore be assumed. In the present paper, a constitutive model for viscoelastic materials in the finite strain regime and under the assumption of plane stress is proposed. It is assumed that the relaxation behaviour in the direction of plane stress can be treated separately, which makes it possible to formulate evolution laws for the plastic strains on explicit form at the same time as incompressibility is fulfilled. Experimental results from biomechanics (dynamic inflation of dog aorta) and rubber mechanics (biaxial stretching of rubber sheets) were used to assess the proposed model. The assessment clearly indicates that the model is fully able to predict the experimental outcome for these types of material.

The Osseus platform: a prototype for advanced web-based distributed simulation

NASA Astrophysics Data System (ADS)

Franceschini, Derrick; Riecken, Mark

2016-05-01

Recent technological advances in web-based distributed computing and database technology have made possible a deeper and more transparent integration of some modeling and simulation applications. Despite these advances towards true integration of capabilities, disparate systems, architectures, and protocols will remain in the inventory for some time to come. These disparities present interoperability challenges for distributed modeling and simulation whether the application is training, experimentation, or analysis. Traditional approaches call for building gateways to bridge between disparate protocols and retaining interoperability specialists. Challenges in reconciling data models also persist. These challenges and their traditional mitigation approaches directly contribute to higher costs, schedule delays, and frustration for the end users. Osseus is a prototype software platform originally funded as a research project by the Defense Modeling & Simulation Coordination Office (DMSCO) to examine interoperability alternatives using modern, web-based technology and taking inspiration from the commercial sector. Osseus provides tools and services for nonexpert users to connect simulations, targeting the time and skillset needed to successfully connect disparate systems. The Osseus platform presents a web services interface to allow simulation applications to exchange data using modern techniques efficiently over Local or Wide Area Networks. Further, it provides Service Oriented Architecture capabilities such that finer granularity components such as individual models can contribute to simulation with minimal effort.

The Diagnostic Challenge Competition: Probabilistic Techniques for Fault Diagnosis in Electrical Power Systems

NASA Technical Reports Server (NTRS)

Ricks, Brian W.; Mengshoel, Ole J.

2009-01-01

Reliable systems health management is an important research area of NASA. A health management system that can accurately and quickly diagnose faults in various on-board systems of a vehicle will play a key role in the success of current and future NASA missions. We introduce in this paper the ProDiagnose algorithm, a diagnostic algorithm that uses a probabilistic approach, accomplished with Bayesian Network models compiled to Arithmetic Circuits, to diagnose these systems. We describe the ProDiagnose algorithm, how it works, and the probabilistic models involved. We show by experimentation on two Electrical Power Systems based on the ADAPT testbed, used in the Diagnostic Challenge Competition (DX 09), that ProDiagnose can produce results with over 96% accuracy and less than 1 second mean diagnostic time.

Experimental challenge of pregnant cattle with the putative abortifacient Waddlia chondrophila.

PubMed

Wheelhouse, Nicholas; Flockhart, Allen; Aitchison, Kevin; Livingstone, Morag; Finlayson, Jeanie; Flachon, Virginie; Sellal, Eric; Dagleish, Mark P; Longbottom, David

2016-11-14

Waddlia chondrophila is a Gram-negative intracellular bacterial organism that is related to classical chlamydial species and has been implicated as a cause of abortion in cattle. Despite an increasing number of observational studies linking W. chondrophila infection to cattle abortion, little direct experimental evidence exists. Given this paucity of direct evidence the current study was carried out to investigate whether experimental challenge of pregnant cattle with W. chondrophila would result in infection and abortion. Nine pregnant Friesian-Holstein heifers received 2 × 10 8 inclusion forming units (IFU) W. chondrophila intravenously on day 105-110 of pregnancy, while four negative-control animals underwent mock challenge. Only one of the challenged animals showed pathogen-associated lesions, with the organism being detected in the diseased placenta. Importantly, the organism was re-isolated and its identity confirmed by whole genome sequencing, confirming Koch's third and fourth postulates. However, while infection of the placenta was observed, the experimental challenge in this study did not confirm the abortifacient potential of the organism.

Challenges in Reproducibility, Replicability, and Comparability of Computational Models and Tools for Neuronal and Glial Networks, Cells, and Subcellular Structures.

PubMed

Manninen, Tiina; Aćimović, Jugoslava; Havela, Riikka; Teppola, Heidi; Linne, Marja-Leena

2018-01-01

The possibility to replicate and reproduce published research results is one of the biggest challenges in all areas of science. In computational neuroscience, there are thousands of models available. However, it is rarely possible to reimplement the models based on the information in the original publication, let alone rerun the models just because the model implementations have not been made publicly available. We evaluate and discuss the comparability of a versatile choice of simulation tools: tools for biochemical reactions and spiking neuronal networks, and relatively new tools for growth in cell cultures. The replicability and reproducibility issues are considered for computational models that are equally diverse, including the models for intracellular signal transduction of neurons and glial cells, in addition to single glial cells, neuron-glia interactions, and selected examples of spiking neuronal networks. We also address the comparability of the simulation results with one another to comprehend if the studied models can be used to answer similar research questions. In addition to presenting the challenges in reproducibility and replicability of published results in computational neuroscience, we highlight the need for developing recommendations and good practices for publishing simulation tools and computational models. Model validation and flexible model description must be an integral part of the tool used to simulate and develop computational models. Constant improvement on experimental techniques and recording protocols leads to increasing knowledge about the biophysical mechanisms in neural systems. This poses new challenges for computational neuroscience: extended or completely new computational methods and models may be required. Careful evaluation and categorization of the existing models and tools provide a foundation for these future needs, for constructing multiscale models or extending the models to incorporate additional or more detailed biophysical mechanisms. Improving the quality of publications in computational neuroscience, enabling progressive building of advanced computational models and tools, can be achieved only through adopting publishing standards which underline replicability and reproducibility of research results.

Challenges in Reproducibility, Replicability, and Comparability of Computational Models and Tools for Neuronal and Glial Networks, Cells, and Subcellular Structures

PubMed Central

Manninen, Tiina; Aćimović, Jugoslava; Havela, Riikka; Teppola, Heidi; Linne, Marja-Leena

2018-01-01

The possibility to replicate and reproduce published research results is one of the biggest challenges in all areas of science. In computational neuroscience, there are thousands of models available. However, it is rarely possible to reimplement the models based on the information in the original publication, let alone rerun the models just because the model implementations have not been made publicly available. We evaluate and discuss the comparability of a versatile choice of simulation tools: tools for biochemical reactions and spiking neuronal networks, and relatively new tools for growth in cell cultures. The replicability and reproducibility issues are considered for computational models that are equally diverse, including the models for intracellular signal transduction of neurons and glial cells, in addition to single glial cells, neuron-glia interactions, and selected examples of spiking neuronal networks. We also address the comparability of the simulation results with one another to comprehend if the studied models can be used to answer similar research questions. In addition to presenting the challenges in reproducibility and replicability of published results in computational neuroscience, we highlight the need for developing recommendations and good practices for publishing simulation tools and computational models. Model validation and flexible model description must be an integral part of the tool used to simulate and develop computational models. Constant improvement on experimental techniques and recording protocols leads to increasing knowledge about the biophysical mechanisms in neural systems. This poses new challenges for computational neuroscience: extended or completely new computational methods and models may be required. Careful evaluation and categorization of the existing models and tools provide a foundation for these future needs, for constructing multiscale models or extending the models to incorporate additional or more detailed biophysical mechanisms. Improving the quality of publications in computational neuroscience, enabling progressive building of advanced computational models and tools, can be achieved only through adopting publishing standards which underline replicability and reproducibility of research results. PMID:29765315

Modeling the Effects of Turbulence in Rotating Detonation Engines

NASA Astrophysics Data System (ADS)

Towery, Colin; Smith, Katherine; Hamlington, Peter; van Schoor, Marthinus; TESLa Team; Midé Team

2014-03-01

Propulsion systems based on detonation waves, such as rotating and pulsed detonation engines, have the potential to substantially improve the efficiency and power density of gas turbine engines. Numerous technical challenges remain to be solved in such systems, however, including obtaining more efficient injection and mixing of air and fuels, more reliable detonation initiation, and better understanding of the flow in the ejection nozzle. These challenges can be addressed using numerical simulations. Such simulations are enormously challenging, however, since accurate descriptions of highly unsteady turbulent flow fields are required in the presence of combustion, shock waves, fluid-structure interactions, and other complex physical processes. In this study, we performed high-fidelity three dimensional simulations of a rotating detonation engine and examined turbulent flow effects on the operation, performance, and efficiency of the engine. Along with experimental data, these simulations were used to test the accuracy of commonly-used Reynolds averaged and subgrid-scale turbulence models when applied to detonation engines. The authors gratefully acknowledge the support of the Defense Advanced Research Projects Agency (DARPA).

A Novel Vaccine against Crimean-Congo Haemorrhagic Fever Protects 100% of Animals against Lethal Challenge in a Mouse Model

PubMed Central

Buttigieg, Karen R.; Dowall, Stuart D.; Findlay-Wilson, Stephen; Miloszewska, Aleksandra; Rayner, Emma; Hewson, Roger; Carroll, Miles W.

2014-01-01

Crimean-Congo Haemorrhagic Fever (CCHF) is a severe tick-borne disease, endemic in many countries in Africa, the Middle East, Eastern Europe and Asia. Between 15–70% of reported cases are fatal. There is no approved vaccine available, and preclinical protection in vivo by an experimental vaccine has not been demonstrated previously. In the present study, the attenuated poxvirus vector, Modified Vaccinia virus Ankara, was used to develop a recombinant candidate vaccine expressing the CCHF virus glycoproteins. Cellular and humoral immunogenicity was confirmed in two mouse strains, including type I interferon receptor knockout mice, which are susceptible to CCHF disease. This vaccine protected all recipient animals from lethal disease in a challenge model adapted to represent infection via a tick bite. Histopathology and viral load analysis of protected animals confirmed that they had been exposed to challenge virus, even though they did not exhibit clinical signs. This is the first demonstration of efficacy of a CCHF vaccine. PMID:24621656

A novel vaccine against Crimean-Congo Haemorrhagic Fever protects 100% of animals against lethal challenge in a mouse model.

PubMed

Buttigieg, Karen R; Dowall, Stuart D; Findlay-Wilson, Stephen; Miloszewska, Aleksandra; Rayner, Emma; Hewson, Roger; Carroll, Miles W

2014-01-01

Crimean-Congo Haemorrhagic Fever (CCHF) is a severe tick-borne disease, endemic in many countries in Africa, the Middle East, Eastern Europe and Asia. Between 15-70% of reported cases are fatal. There is no approved vaccine available, and preclinical protection in vivo by an experimental vaccine has not been demonstrated previously. In the present study, the attenuated poxvirus vector, Modified Vaccinia virus Ankara, was used to develop a recombinant candidate vaccine expressing the CCHF virus glycoproteins. Cellular and humoral immunogenicity was confirmed in two mouse strains, including type I interferon receptor knockout mice, which are susceptible to CCHF disease. This vaccine protected all recipient animals from lethal disease in a challenge model adapted to represent infection via a tick bite. Histopathology and viral load analysis of protected animals confirmed that they had been exposed to challenge virus, even though they did not exhibit clinical signs. This is the first demonstration of efficacy of a CCHF vaccine.

Noisy probability judgment, the conjunction fallacy, and rationality: Comment on Costello and Watts (2014).

PubMed

Crupi, Vincenzo; Tentori, Katya

2016-01-01

According to Costello and Watts (2014), probability theory can account for key findings in human judgment research provided that random noise is embedded in the model. We concur with a number of Costello and Watts's remarks, but challenge the empirical adequacy of their model in one of their key illustrations (the conjunction fallacy) on the basis of recent experimental findings. We also discuss how our argument bears on heuristic and rational thinking. (c) 2015 APA, all rights reserved).

Improving homology modeling of G-protein coupled receptors through multiple-template derived conserved inter-residue interactions

NASA Astrophysics Data System (ADS)

Chaudhari, Rajan; Heim, Andrew J.; Li, Zhijun

2015-05-01

Evidenced by the three-rounds of G-protein coupled receptors (GPCR) Dock competitions, improving homology modeling methods of helical transmembrane proteins including the GPCRs, based on templates of low sequence identity, remains an eminent challenge. Current approaches addressing this challenge adopt the philosophy of "modeling first, refinement next". In the present work, we developed an alternative modeling approach through the novel application of available multiple templates. First, conserved inter-residue interactions are derived from each additional template through conservation analysis of each template-target pairwise alignment. Then, these interactions are converted into distance restraints and incorporated in the homology modeling process. This approach was applied to modeling of the human β2 adrenergic receptor using the bovin rhodopsin and the human protease-activated receptor 1 as templates and improved model quality was demonstrated compared to the homology model generated by standard single-template and multiple-template methods. This method of "refined restraints first, modeling next", provides a fast and complementary way to the current modeling approaches. It allows rational identification and implementation of additional conserved distance restraints extracted from multiple templates and/or experimental data, and has the potential to be applicable to modeling of all helical transmembrane proteins.

Internal friction in enzyme reactions.

PubMed

Rauscher, Anna; Derényi, Imre; Gráf, László; Málnási-Csizmadia, András

2013-01-01

The empirical concept of internal friction was introduced 20 years ago. This review summarizes the results of experimental and theoretical studies that help to uncover the nature of internal friction. After the history of the concept, we describe the experimental challenges in measuring and interpreting internal friction based on the viscosity dependence of enzyme reactions. We also present speculations about the structural background of this viscosity dependence. Finally, some models about the relationship between the energy landscape and internal friction are outlined. Alternative concepts regarding the viscosity dependence of enzyme reactions are also discussed. Copyright © 2012 International Union of Biochemistry and Molecular Biology, Inc.

Sexual transmission of Lyme disease: challenging the tickborne disease paradigm.

PubMed

Stricker, Raphael B; Middelveen, Marianne J

2015-01-01

Lyme disease caused by the spirochete Borrelia burgdorferi has become a major worldwide epidemic. In this article, we explore the clinical, epidemiological and experimental evidence for sexual transmission of Lyme disease in animal models and humans. Although the likelihood of sexual transmission of the Lyme spirochete remains speculative, the possibility of Lyme disease transmission via intimate human contact merits further study.

Grand challenges in evolutionary and population genetics: The importance of integrating epigenetics, genomics, modeling, and experimentation

Treesearch

Samuel A. Cushman

2014-01-01

This is a time of explosive growth in the fields of evolutionary and population genetics, with whole genome sequencing and bioinformatics driving a transformative paradigm shift (Morozova and Marra, 2008). At the same time, advances in epigenetics are thoroughly transforming our understanding of evolutionary processes and their implications for populations, species and...

An Experimental Test of Differential Susceptibility to Parenting among Emotionally-Dysregulated Children in a Randomized Controlled Trial for Oppositional Behavior

ERIC Educational Resources Information Center

Scott, Stephen; O'Connor, Thomas G.

2012-01-01

Background: The concept of differential susceptibility has challenged the potential meaning of personal traits such as poor ability to regulate emotions. Under the traditional model of diathesis/stress, personal characteristics such as liability to angry outbursts are seen as essentially disadvantageous, emerging under duress in a way that is…

Phenotypic characterisation of cell populations in the brains of horses experimentally infected with West Nile virus.

PubMed

Delcambre, G H; Liu, J; Streit, W J; Shaw, G P J; Vallario, K; Herrington, J; Wenzlow, N; Barr, K L; Long, M T

2017-11-01

West Nile virus (WNV), a mosquito borne member of the Flaviviridae, is one of the most commonly diagnosed agents of viral encephalitis in horses and people worldwide. A cassette of markers for formalin-fixed paraffin-embedded tissue and an archive of tissues from experimental infections in the horse were used to investigate the equine neuroimmune response to WNV meningoencephalomyelitis to phenotype the early response to WNV infection in the horse. Quantitative analysis using archived tissue from experimentally infected horses. The thalamus and hindbrain from 2 groups of 6 horses were compared and consisted of a culture positive tissues from WNV experimentally horses, in the other, normal horses. Formalin-fixed paraffin-embedded tissue from the thalamus and hindbrain were immunolabeled for microglia, astrocytes, B cells, macrophages/neutrophils, CD3 + T cells. Fresh frozen tissues were immunolabeled for CD4 + and CD8 + T lymphocyte cell markers. Cell counts were obtained using a computer software program. Differences, after meeting assumptions of abnormality, were computed using a general linear model with a Tukey test (P<0.05) for pairwise comparisons. In WNV-challenged horses, Iba-1 + microglia, CD3 + T lymphocyte and MAC387 + macrophage staining were significantly increased. The T cell response for the WNV-challenged horses was mixed, composed of CD4 + and CD8 + T lymphocytes. A limited astrocyte response was also observed in WNV-challenged horses, and MAC387 + and B cells were the least abundant cell populations. The results of this study were limited by a single collection time post-infection. Furthermore, a comprehensive analysis of cellular phenotypes is needed for naturally infected horses. Unfortunately, in clinical horses, there is high variability of sampling in terms of days post-infection and tissue handling. The data show that WNV-challenged horses recruit a mixed T cell population at the onset of neurologic disease. © 2017 EVJ Ltd.

A White Paper on keV sterile neutrino Dark Matter

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

Adhikari, R.; Agostini, M.; Ky, N. Anh

We present a comprehensive review of keV-scale sterile neutrino Dark Matter, collecting views and insights from all disciplines involved—cosmology, astrophysics, nuclear, and particle physics—in each case viewed from both theoretical and experimental/observational perspectives. After reviewing the role of active neutrinos in particle physics, astrophysics, and cosmology, we focus on sterile neutrinos in the context of the Dark Matter puzzle. Here, we first review the physics motivation for sterile neutrino Dark Matter, based on challenges and tensions in purely cold Dark Matter scenarios. We then round out the discussion by critically summarizing all known constraints on sterile neutrino Dark Matter arisingmore » from astrophysical observations, laboratory experiments, and theoretical considerations. In this context, we provide a balanced discourse on the possibly positive signal from X-ray observations. Another focus of the paper concerns the construction of particle physics models, aiming to explain how sterile neutrinos of keV-scale masses could arise in concrete settings beyond the Standard Model of elementary particle physics. The paper ends with an extensive review of current and future astrophysical and laboratory searches, highlighting new ideas and their experimental challenges, as well as future perspectives for the discovery of sterile neutrinos.« less

A White Paper on keV sterile neutrino Dark Matter

DOE PAGES

Adhikari, R.

2017-01-13

Here, we present a comprehensive review of keV-scale sterile neutrino Dark Matter, collecting views and insights from all disciplines involved - cosmology, astrophysics, nuclear, and particle physics - in each case viewed from both theoretical and experimental/observational perspectives. After reviewing the role of active neutrinos in particle physics, astrophysics, and cosmology, we focus on sterile neutrinos in the context of the Dark Matter puzzle. First, we review the physics motivation for sterile neutrino Dark Matter, based on challenges and tensions in purely cold Dark Matter scenarios. We then round out the discussion by critically summarizing all known constraints on sterilemore » neutrino Dark Matter arising from astrophysical observations, laboratory experiments, and theoretical considerations. In this context, we provide a balanced discourse on the possibly positive signal from X-ray observations. Another focus of the paper concerns the construction of particle physics models, aiming to explain how sterile neutrinos of keV-scale masses could arise in concrete settings beyond the Standard Model of elementary particle physics. Our paper ends with an extensive review of current and future astrophysical and laboratory searches, highlighting new ideas and their experimental challenges, as well as future perspectives for the discovery of sterile neutrinos.« less

A White Paper on keV sterile neutrino Dark Matter

NASA Astrophysics Data System (ADS)

Adhikari, R.; Agostini, M.; Ky, N. Anh; Araki, T.; Archidiacono, M.; Bahr, M.; Baur, J.; Behrens, J.; Bezrukov, F.; Bhupal Dev, P. S.; Borah, D.; Boyarsky, A.; de Gouvea, A.; Pires, C. A. de S.; de Vega, H. J.; Dias, A. G.; Di Bari, P.; Djurcic, Z.; Dolde, K.; Dorrer, H.; Durero, M.; Dragoun, O.; Drewes, M.; Drexlin, G.; Düllmann, Ch. E.; Eberhardt, K.; Eliseev, S.; Enss, C.; Evans, N. W.; Faessler, A.; Filianin, P.; Fischer, V.; Fleischmann, A.; Formaggio, J. A.; Franse, J.; Fraenkle, F. M.; Frenk, C. S.; Fuller, G.; Gastaldo, L.; Garzilli, A.; Giunti, C.; Glück, F.; Goodman, M. C.; Gonzalez-Garcia, M. C.; Gorbunov, D.; Hamann, J.; Hannen, V.; Hannestad, S.; Hansen, S. H.; Hassel, C.; Heeck, J.; Hofmann, F.; Houdy, T.; Huber, A.; Iakubovskyi, D.; Ianni, A.; Ibarra, A.; Jacobsson, R.; Jeltema, T.; Jochum, J.; Kempf, S.; Kieck, T.; Korzeczek, M.; Kornoukhov, V.; Lachenmaier, T.; Laine, M.; Langacker, P.; Lasserre, T.; Lesgourgues, J.; Lhuillier, D.; Li, Y. F.; Liao, W.; Long, A. W.; Maltoni, M.; Mangano, G.; Mavromatos, N. E.; Menci, N.; Merle, A.; Mertens, S.; Mirizzi, A.; Monreal, B.; Nozik, A.; Neronov, A.; Niro, V.; Novikov, Y.; Oberauer, L.; Otten, E.; Palanque-Delabrouille, N.; Pallavicini, M.; Pantuev, V. S.; Papastergis, E.; Parke, S.; Pascoli, S.; Pastor, S.; Patwardhan, A.; Pilaftsis, A.; Radford, D. C.; Ranitzsch, P. C.-O.; Rest, O.; Robinson, D. J.; Rodrigues da Silva, P. S.; Ruchayskiy, O.; Sanchez, N. G.; Sasaki, M.; Saviano, N.; Schneider, A.; Schneider, F.; Schwetz, T.; Schönert, S.; Scholl, S.; Shankar, F.; Shrock, R.; Steinbrink, N.; Strigari, L.; Suekane, F.; Suerfu, B.; Takahashi, R.; Van, N. Thi Hong; Tkachev, I.; Totzauer, M.; Tsai, Y.; Tully, C. G.; Valerius, K.; Valle, J. W. F.; Venos, D.; Viel, M.; Vivier, M.; Wang, M. Y.; Weinheimer, C.; Wendt, K.; Winslow, L.; Wolf, J.; Wurm, M.; Xing, Z.; Zhou, S.; Zuber, K.

2017-01-01

We present a comprehensive review of keV-scale sterile neutrino Dark Matter, collecting views and insights from all disciplines involved—cosmology, astrophysics, nuclear, and particle physics—in each case viewed from both theoretical and experimental/observational perspectives. After reviewing the role of active neutrinos in particle physics, astrophysics, and cosmology, we focus on sterile neutrinos in the context of the Dark Matter puzzle. Here, we first review the physics motivation for sterile neutrino Dark Matter, based on challenges and tensions in purely cold Dark Matter scenarios. We then round out the discussion by critically summarizing all known constraints on sterile neutrino Dark Matter arising from astrophysical observations, laboratory experiments, and theoretical considerations. In this context, we provide a balanced discourse on the possibly positive signal from X-ray observations. Another focus of the paper concerns the construction of particle physics models, aiming to explain how sterile neutrinos of keV-scale masses could arise in concrete settings beyond the Standard Model of elementary particle physics. The paper ends with an extensive review of current and future astrophysical and laboratory searches, highlighting new ideas and their experimental challenges, as well as future perspectives for the discovery of sterile neutrinos.

A White Paper on keV sterile neutrino Dark Matter

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

Adhikari, R.

Here, we present a comprehensive review of keV-scale sterile neutrino Dark Matter, collecting views and insights from all disciplines involved - cosmology, astrophysics, nuclear, and particle physics - in each case viewed from both theoretical and experimental/observational perspectives. After reviewing the role of active neutrinos in particle physics, astrophysics, and cosmology, we focus on sterile neutrinos in the context of the Dark Matter puzzle. First, we review the physics motivation for sterile neutrino Dark Matter, based on challenges and tensions in purely cold Dark Matter scenarios. We then round out the discussion by critically summarizing all known constraints on sterilemore » neutrino Dark Matter arising from astrophysical observations, laboratory experiments, and theoretical considerations. In this context, we provide a balanced discourse on the possibly positive signal from X-ray observations. Another focus of the paper concerns the construction of particle physics models, aiming to explain how sterile neutrinos of keV-scale masses could arise in concrete settings beyond the Standard Model of elementary particle physics. Our paper ends with an extensive review of current and future astrophysical and laboratory searches, highlighting new ideas and their experimental challenges, as well as future perspectives for the discovery of sterile neutrinos.« less

Multisource data assimilation in a Richards equation-based integrated hydrological model: a real-world application to an experimental hillslope

NASA Astrophysics Data System (ADS)

Camporese, M.; Botto, A.

2017-12-01

Data assimilation is becoming increasingly popular in hydrological and earth system modeling, as it allows for direct integration of multisource observation data in modeling predictions and uncertainty reduction. For this reason, data assimilation has been recently the focus of much attention also for integrated surface-subsurface hydrological models, whereby multiple terrestrial compartments (e.g., snow cover, surface water, groundwater) are solved simultaneously, in an attempt to tackle environmental problems in a holistic approach. Recent examples include the joint assimilation of water table, soil moisture, and river discharge measurements in catchment models of coupled surface-subsurface flow using the ensemble Kalman filter (EnKF). Although the EnKF has been specifically developed to deal with nonlinear models, integrated hydrological models based on the Richards equation still represent a challenge, due to strong nonlinearities that may significantly affect the filter performance. Thus, more studies are needed to investigate the capabilities of EnKF to correct the system state and identify parameters in cases where the unsaturated zone dynamics are dominant. Here, the model CATHY (CATchment HYdrology) is applied to reproduce the hydrological dynamics observed in an experimental hillslope, equipped with tensiometers, water content reflectometer probes, and tipping bucket flow gages to monitor the hillslope response to a series of artificial rainfall events. We assimilate pressure head, soil moisture, and subsurface outflow with EnKF in a number of assimilation scenarios and discuss the challenges, issues, and tradeoffs arising from the assimilation of multisource data in a real-world test case, with particular focus on the capability of DA to update the subsurface parameters.

Gaussian process based modeling and experimental design for sensor calibration in drifting environments

PubMed Central

Geng, Zongyu; Yang, Feng; Chen, Xi; Wu, Nianqiang

2016-01-01

It remains a challenge to accurately calibrate a sensor subject to environmental drift. The calibration task for such a sensor is to quantify the relationship between the sensor’s response and its exposure condition, which is specified by not only the analyte concentration but also the environmental factors such as temperature and humidity. This work developed a Gaussian Process (GP)-based procedure for the efficient calibration of sensors in drifting environments. Adopted as the calibration model, GP is not only able to capture the possibly nonlinear relationship between the sensor responses and the various exposure-condition factors, but also able to provide valid statistical inference for uncertainty quantification of the target estimates (e.g., the estimated analyte concentration of an unknown environment). Built on GP’s inference ability, an experimental design method was developed to achieve efficient sampling of calibration data in a batch sequential manner. The resulting calibration procedure, which integrates the GP-based modeling and experimental design, was applied on a simulated chemiresistor sensor to demonstrate its effectiveness and its efficiency over the traditional method. PMID:26924894

A competitive complex formation mechanism underlies trichome patterning on Arabidopsis leaves

PubMed Central

Digiuni, Simona; Schellmann, Swen; Geier, Florian; Greese, Bettina; Pesch, Martina; Wester, Katja; Dartan, Burcu; Mach, Valerie; Srinivas, Bhylahalli Purushottam; Timmer, Jens; Fleck, Christian; Hulskamp, Martin

2008-01-01

Trichome patterning in Arabidopsis serves as a model system for de novo pattern formation in plants. It is thought to typify the theoretical activator–inhibitor mechanism, although this hypothesis has never been challenged by a combined experimental and theoretical approach. By integrating the key genetic and molecular data of the trichome patterning system, we developed a new theoretical model that allows the direct testing of the effect of experimental interventions and in the prediction of patterning phenotypes. We show experimentally that the trichome inhibitor TRIPTYCHON is transcriptionally activated by the known positive regulators GLABRA1 and GLABRA3. Further, we demonstrate by particle bombardment of protein fusions with GFP that TRIPTYCHON and CAPRICE but not GLABRA1 and GLABRA3 can move between cells. Finally, theoretical considerations suggest promoter swapping and basal overexpression experiments by means of which we are able to discriminate three biologically meaningful variants of the trichome patterning model. Our study demonstrates that the mutual interplay between theory and experiment can reveal a new level of understanding of how biochemical mechanisms can drive biological patterning processes. PMID:18766177

A Recombinant Vesicular Stomatitis Virus-Based Lassa Fever Vaccine Protects Guinea Pigs and Macaques against Challenge with Geographically and Genetically Distinct Lassa Viruses

PubMed Central

Safronetz, David; Mire, Chad; Rosenke, Kyle; Feldmann, Friederike; Haddock, Elaine; Geisbert, Thomas; Feldmann, Heinz

2015-01-01

Background Lassa virus (LASV) is endemic in several West African countries and is the etiological agent of Lassa fever. Despite the high annual incidence and significant morbidity and mortality rates, currently there are no approved vaccines to prevent infection or disease in humans. Genetically, LASV demonstrates a high degree of diversity that correlates with geographic distribution. The genetic heterogeneity observed between geographically distinct viruses raises concerns over the potential efficacy of a “universal” LASV vaccine. To date, several experimental LASV vaccines have been developed; however, few have been evaluated against challenge with various genetically unique Lassa virus isolates in relevant animal models. Methodologies/principle findings Here we demonstrate that a single, prophylactic immunization with a recombinant vesicular stomatitis virus (VSV) expressing the glycoproteins of LASV strain Josiah from Sierra Leone protects strain 13 guinea pigs from infection / disease following challenge with LASV isolates originating from Liberia, Mali and Nigeria. Similarly, the VSV-based LASV vaccine yields complete protection against a lethal challenge with the Liberian LASV isolate in the gold-standard macaque model of Lassa fever. Conclusions/significance Our results demonstrate the VSV-based LASV vaccine is capable of preventing morbidity and mortality associated with non-homologous LASV challenge in two animal models of Lassa fever. Additionally, this work highlights the need for the further development of disease models for geographical distinct LASV strains, particularly those from Nigeria, in order to comprehensively evaluate potential vaccines and therapies against this prominent agent of viral hemorrhagic fever. PMID:25884628

Best practices for germ-free derivation and gnotobiotic zebrafish husbandry

PubMed Central

Melancon, E.; De La Torre Canny, S. Gomez; Sichel, S.; Kelly, M.; Wiles, T.J.; Rawls, J.F.; Eisen, J.S.; Guillemin, K.

2017-01-01

All animals are ecosystems with resident microbial communities, referred to as microbiota, which play profound roles in host development, physiology, and evolution. Enabled by new DNA sequencing technologies, there is a burgeoning interest in animal–microbiota interactions, but dissecting the specific impacts of microbes on their hosts is experimentally challenging. Gnotobiology, the study of biological systems in which all members are known, enables precise experimental analysis of the necessity and sufficiency of microbes in animal biology by deriving animals germ-free (GF) and inoculating them with defined microbial lineages. Mammalian host models have long dominated gnotobiology, but we have recently adapted gnotobiotic approaches to the zebrafish (Danio rerio), an important aquatic model. Zebrafish offer several experimental attributes that enable rapid, large-scale gnotobiotic experimentation with high replication rates and exquisite optical resolution. Here we describe detailed protocols for three procedures that form the foundation of zebrafish gnotobiology: derivation of GF embryos, microbial association of GF animals, and long-term, GF husbandry. Our aim is to provide sufficient guidance in zebrafish gnotobiotic methodology to expand and enrich this exciting field of research. PMID:28129860

Challenges in modelling homogeneous catalysis: new answers from ab initio molecular dynamics to the controversy over the Wacker process.

PubMed

Stirling, András; Nair, Nisanth N; Lledós, Agustí; Ujaque, Gregori

2014-07-21

We present here a review of the mechanistic studies of the Wacker process stressing the long controversy about the key reaction steps. We give an overview of the previous experimental and theoretical studies on the topic. Then we describe the importance of the most recent Ab Initio Molecular Dynamics (AIMD) calculations in modelling organometallic reactivity in water. As a prototypical example of homogeneous catalytic reactions, the Wacker process poses serious challenges to modelling. The adequate description of the multiple role of the water solvent is very difficult by using static quantum chemical approaches including cluster and continuum solvent models. In contrast, such reaction systems are suitable for AIMD, and by combining with rare event sampling techniques, the method provides reaction mechanisms and the corresponding free energy profiles. The review also highlights how AIMD has helped to obtain a novel understanding of the mechanism and kinetics of the Wacker process.

A gene network model accounting for development and evolution of mammalian teeth

PubMed Central

Salazar-Ciudad, Isaac; Jernvall, Jukka

2002-01-01

Generation of morphological diversity remains a challenge for evolutionary biologists because it is unclear how an ultimately finite number of genes involved in initial pattern formation integrates with morphogenesis. Ideally, models used to search for the simplest developmental principles on how genes produce form should account for both developmental process and evolutionary change. Here we present a model reproducing the morphology of mammalian teeth by integrating experimental data on gene interactions and growth into a morphodynamic mechanism in which developing morphology has a causal role in patterning. The model predicts the course of tooth-shape development in different mammalian species and also reproduces key transitions in evolution. Furthermore, we reproduce the known expression patterns of several genes involved in tooth development and their dynamics over developmental time. Large morphological effects frequently can be achieved by small changes, according to this model, and similar morphologies can be produced by different changes. This finding may be consistent with why predicting the morphological outcomes of molecular experiments is challenging. Nevertheless, models incorporating morphology and gene activity show promise for linking genotypes to phenotypes. PMID:12048258

Numerical simulation of overflow at vertical weirs using a hybrid level set/VOF method

NASA Astrophysics Data System (ADS)

Lv, Xin; Zou, Qingping; Reeve, Dominic

2011-10-01

This paper presents the applications of a newly developed free surface flow model to the practical, while challenging overflow problems for weirs. Since the model takes advantage of the strengths of both the level set and volume of fluid methods and solves the Navier-Stokes equations on an unstructured mesh, it is capable of resolving the time evolution of very complex vortical motions, air entrainment and pressure variations due to violent deformations following overflow of the weir crest. In the present study, two different types of vertical weir, namely broad-crested and sharp-crested, are considered for validation purposes. The calculated overflow parameters such as pressure head distributions, velocity distributions, and water surface profiles are compared against experimental data as well as numerical results available in literature. A very good quantitative agreement has been obtained. The numerical model, thus, offers a good alternative to traditional experimental methods in the study of weir problems.

Quantitative Subsurface Atomic Structure Fingerprint for 2D Materials and Heterostructures by First-Principles-Calibrated Contact-Resonance Atomic Force Microscopy.

PubMed

Tu, Qing; Lange, Björn; Parlak, Zehra; Lopes, Joao Marcelo J; Blum, Volker; Zauscher, Stefan

2016-07-26

Interfaces and subsurface layers are critical for the performance of devices made of 2D materials and heterostructures. Facile, nondestructive, and quantitative ways to characterize the structure of atomically thin, layered materials are thus essential to ensure control of the resultant properties. Here, we show that contact-resonance atomic force microscopy-which is exquisitely sensitive to stiffness changes that arise from even a single atomic layer of a van der Waals-adhered material-is a powerful experimental tool to address this challenge. A combined density functional theory and continuum modeling approach is introduced that yields sub-surface-sensitive, nanomechanical fingerprints associated with specific, well-defined structure models of individual surface domains. Where such models are known, this information can be correlated with experimentally obtained contact-resonance frequency maps to reveal the (sub)surface structure of different domains on the sample.

Towards the Physics of Calcium Signalling in Plants

PubMed Central

Vaz Martins, Teresa; Evans, Matthew J.; Woolfenden, Hugh C.; Morris, Richard J.

2013-01-01

Calcium is an abundant element with a wide variety of important roles within cells. Calcium ions are inter- and intra-cellular messengers that are involved in numerous signalling pathways. Fluctuating compartment-specific calcium ion concentrations can lead to localised and even plant-wide oscillations that can regulate downstream events. Understanding the mechanisms that give rise to these complex patterns that vary both in space and time can be challenging, even in cases for which individual components have been identified. Taking a systems biology approach, mathematical and computational techniques can be employed to produce models that recapitulate experimental observations and capture our current understanding of the system. Useful models make novel predictions that can be investigated and falsified experimentally. This review brings together recent work on the modelling of calcium signalling in plants, from the scale of ion channels through to plant-wide responses to external stimuli. Some in silico results that have informed later experiments are highlighted. PMID:27137393

Exploring magnetized liner inertial fusion with a semi-analytic model

DOE PAGES

McBride, Ryan D.; Slutz, Stephen A.; Vesey, Roger A.; ...

2016-01-01

In this study, we explore magnetized liner inertial fusion (MagLIF) [S. A. Slutz et al., Phys. Plasmas 17, 056303 (2010)] using a semi-analytic model [R. D. McBride and S. A. Slutz, Phys. Plasmas 22, 052708 (2015)]. Specifically, we present simulation results from this model that: (a) illustrate the parameter space, energetics, and overall system efficiencies of MagLIF; (b) demonstrate the dependence of radiative loss rates on the radial fraction of the fuel that is preheated; (c) explore some of the recent experimental results of the MagLIF program at Sandia National Laboratories [M. R. Gomez et al., Phys. Rev. Lett. 113,more » 155003 (2014)]; (d) highlight the experimental challenges presently facing the MagLIF program; and (e) demonstrate how increases to the preheat energy, fuel density, axial magnetic field, and drive current could affect future MagLIF performance.« less

Exploring magnetized liner inertial fusion with a semi-analytic model

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

McBride, R. D.; Slutz, S. A.; Vesey, R. A.

In this paper, we explore magnetized liner inertial fusion (MagLIF) [S. A. Slutz et al., Phys. Plasmas 17, 056303 (2010)] using a semi-analytic model [R. D. McBride and S. A. Slutz, Phys. Plasmas 22, 052708 (2015)]. Specifically, we present simulation results from this model that: (a) illustrate the parameter space, energetics, and overall system efficiencies of MagLIF; (b) demonstrate the dependence of radiative loss rates on the radial fraction of the fuel that is preheated; (c) explore some of the recent experimental results of the MagLIF program at Sandia National Laboratories [M. R. Gomez et al., Phys. Rev. Lett. 113,more » 155003 (2014)]; (d) highlight the experimental challenges presently facing the MagLIF program; and (e) demonstrate how increases to the preheat energy, fuel density, axial magnetic field, and drive current could affect future MagLIF performance.« less

Exploring magnetized liner inertial fusion with a semi-analytic model

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

McBride, Ryan D.; Slutz, Stephen A.; Vesey, Roger A.

In this study, we explore magnetized liner inertial fusion (MagLIF) [S. A. Slutz et al., Phys. Plasmas 17, 056303 (2010)] using a semi-analytic model [R. D. McBride and S. A. Slutz, Phys. Plasmas 22, 052708 (2015)]. Specifically, we present simulation results from this model that: (a) illustrate the parameter space, energetics, and overall system efficiencies of MagLIF; (b) demonstrate the dependence of radiative loss rates on the radial fraction of the fuel that is preheated; (c) explore some of the recent experimental results of the MagLIF program at Sandia National Laboratories [M. R. Gomez et al., Phys. Rev. Lett. 113,more » 155003 (2014)]; (d) highlight the experimental challenges presently facing the MagLIF program; and (e) demonstrate how increases to the preheat energy, fuel density, axial magnetic field, and drive current could affect future MagLIF performance.« less

Thermophysical properties of liquid UO2, ZrO2 and corium by molecular dynamics and predictive models

NASA Astrophysics Data System (ADS)

Kim, Woong Kee; Shim, Ji Hoon; Kaviany, Massoud

2017-08-01

Predicting the fate of accident-melted nuclear fuel-cladding requires the understanding of the thermophysical properties which are lacking or have large scatter due to high-temperature experimental challenges. Using equilibrium classical molecular dynamics (MD), we predict the properties of melted UO2 and ZrO2 and compare them with the available experimental data and the predictive models. The existing interatomic potential models have been developed mainly for the polymorphic solid phases of these oxides, so they cannot be used to predict all the properties accurately. We compare and decipher the distinctions of those MD predictions using the specific property-related autocorrelation decays. The predicted properties are density, specific heat, heat of fusion, compressibility, viscosity, surface tension, and the molecular and electronic thermal conductivities. After the comparisons, we provide readily usable temperature-dependent correlations (including UO2-ZrO2 compounds, i.e. corium melt).

Parameter discovery in stochastic biological models using simulated annealing and statistical model checking.

PubMed

Hussain, Faraz; Jha, Sumit K; Jha, Susmit; Langmead, Christopher J

2014-01-01

Stochastic models are increasingly used to study the behaviour of biochemical systems. While the structure of such models is often readily available from first principles, unknown quantitative features of the model are incorporated into the model as parameters. Algorithmic discovery of parameter values from experimentally observed facts remains a challenge for the computational systems biology community. We present a new parameter discovery algorithm that uses simulated annealing, sequential hypothesis testing, and statistical model checking to learn the parameters in a stochastic model. We apply our technique to a model of glucose and insulin metabolism used for in-silico validation of artificial pancreata and demonstrate its effectiveness by developing parallel CUDA-based implementation for parameter synthesis in this model.

NASA Workshop on Distributed Parameter Modeling and Control of Flexible Aerospace Systems

NASA Technical Reports Server (NTRS)

Marks, Virginia B. (Compiler); Keckler, Claude R. (Compiler)

1994-01-01

Although significant advances have been made in modeling and controlling flexible systems, there remains a need for improvements in model accuracy and in control performance. The finite element models of flexible systems are unduly complex and are almost intractable to optimum parameter estimation for refinement using experimental data. Distributed parameter or continuum modeling offers some advantages and some challenges in both modeling and control. Continuum models often result in a significantly reduced number of model parameters, thereby enabling optimum parameter estimation. The dynamic equations of motion of continuum models provide the advantage of allowing the embedding of the control system dynamics, thus forming a complete set of system dynamics. There is also increased insight provided by the continuum model approach.

Experimental aerosolized guinea pig-adapted Zaire ebolavirus (variant: Mayinga) causes lethal pneumonia in guinea pigs.

PubMed

Twenhafel, N A; Shaia, C I; Bunton, T E; Shamblin, J D; Wollen, S E; Pitt, L M; Sizemore, D R; Ogg, M M; Johnston, S C

2015-01-01

Eight guinea pigs were aerosolized with guinea pig-adapted Zaire ebolavirus (variant: Mayinga) and developed lethal interstitial pneumonia that was distinct from lesions described in guinea pigs challenged subcutaneously, nonhuman primates challenged by the aerosol route, and natural infection in humans. Guinea pigs succumbed with significant pathologic changes primarily restricted to the lungs. Intracytoplasmic inclusion bodies were observed in many alveolar macrophages. Perivasculitis was noted within the lungs. These changes are unlike those of documented subcutaneously challenged guinea pigs and aerosolized filoviral infections in nonhuman primates and human cases. Similar to findings in subcutaneously challenged guinea pigs, there were only mild lesions in the liver and spleen. To our knowledge, this is the first report of aerosol challenge of guinea pigs with guinea pig-adapted Zaire ebolavirus (variant: Mayinga). Before choosing this model for use in aerosolized ebolavirus studies, scientists and pathologists should be aware that aerosolized guinea pig-adapted Zaire ebolavirus (variant: Mayinga) causes lethal pneumonia in guinea pigs. © The Author(s) 2014.

A randomized trial to evaluate the effect of a trace mineral premix on the incidence of active digital dermatitis lesions in cattle.

PubMed

Gomez, A; Bernardoni, N; Rieman, J; Dusick, A; Hartshorn, R; Read, D H; Socha, M T; Cook, N B; Döpfer, D

2014-10-01

A balanced, parallel-group, single-blinded randomized efficacy study divided into 2 periods was conducted to evaluate the effect of a premix containing higher than typically recommended levels of organic trace minerals and iodine (HOTMI) in reducing the incidence of active digital dermatitis (DD) lesions acquired naturally and induced by an experimental infection challenge model. For the natural exposure phase of the study, 120 healthy Holstein steers 5 to 7 mo of age without signs of hoof disease were randomized into 2 groups of 60 animals. The control group was fed a standard trace mineral supplement and the treatment group was fed the HOTMI premix, both for a period of 60 d. On d 60, 15 steers free of macroscopic DD lesions were randomly selected from each group for the challenge phase and transported to an experimental facility, where they were acclimated and then challenged within a DD infection model. The same diet group allocation was maintained during the 60 d of the challenge phase. The primary outcome measured was the development of an active DD lesion greater than 20mm in diameter across its largest dimension. No lesions were identified during the natural exposure phase. During the challenge phase, 55% (11/20) and 30% (6/20) of feet were diagnosed with an active DD lesion in the control and treatment groups, respectively. Diagnosis of DD was confirmed by histopathologic demonstration of invasive Treponema spp. within eroded and hyperplastic epidermis and ulcerated papillary dermis. All DD confirmed lesions had dark-field microscopic features compatible with DD and were positive for Treponema spp. by PCR. As a secondary outcome, the average DD lesion size observed in all feet was also evaluated. Overall mean (standard deviation) lesion size was 17.1 (2.36) mm and 11.1 (3.33) mm for the control and treatment groups, respectively, with this difference being driven by acute DD lesions >20mm. A trend existed for the HOTMI premix to reduce the total DD infection rate and the average size of the experimentally induced lesions. Further research is needed to validate the effect of this intervention strategy in the field and to generate prevention and control measures aimed at optimizing claw health based on nutritional programs. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Preclinical evaluation of bacterially produced RSV-G protein vaccine: Strong protection against RSV challenge in cotton rat model.

PubMed

Fuentes, Sandra; Klenow, Laura; Golding, Hana; Khurana, Surender

2017-02-10

In current study, we evaluated the safety and protective efficacy of recombinant unglycosylated RSV G protein ectodomain produced in E. coli (in presence and absence of oil-in-water adjuvant) in a preclinical RSV susceptible cotton rat challenge model compared to formaldehyde inactivated RSV (FI-RSV) and live RSV experimental infection. The adjuvanted G protein vaccine induced robust neutralization antibody responses comparable to those generated by live RSV infection. Importantly, adjuvanted G protein significantly reduced viral loads in both the lungs and nose at early time points following viral challenge. Antibody kinetics determined by Surface Plasmon Resonance showed that adjuvanted G generated 10-fold higher G-binding antibodies compared to non-adjvuanted G vaccine and live RSV infection, which correlated strongly with both neutralization titers and viral load titers in the nose and lungs post-viral challenge. Antibody diversity analysis revealed immunodominant antigenic sites in the N- and C-termini of the RSV-G protein, that were boosted >10-fold by adjuvant and inversely correlated with viral load titers. Enhanced lung pathology was observed only in animals vaccinated with FI-RSV, but not in animals vaccinated with unadjuvanted or adjuvanted RSV-G vaccine after viral challenge. The bacterially produced unglycosylated G protein could be developed as a protective vaccine against RSV disease.

Chronic varied stress modulates experimental autoimmune encephalomyelitis in Wistar rats.

PubMed

Correa, S G; Rodriguez-Galán, M C; Rivero, V E; Riera, C M

1998-06-01

Stress disturbs homeostasis by altering the equilibrium of various hormones which have a significant impact on immune responses. Few studies have examined the influence of stressors on autoimmune disease in animal models. In our work, we studied the effects of long-term exposure (14 days) to chronic varied stress (CVS) in a model of experimental autoimmune encephalomyelitis (EAE) in Wistar rats. We studied whether the exposure to CVS before or after the immune challenge would correlate with differences in the clinical course of the disease. We also examined whether the CVS would modulate the magnitude of the cellular or the humoral immune response. We observed opposite effects on the clinical signs in animals stressed before or after the immune challenge. The clinical signs of the disease were attenuated in animals stressed before but not after the immune challenge. Relationships were found in the modulation of the clinical severity related to the time of exposure to the CVS, the histological alterations and the proliferative results. Stressed animals with milder clinical signs presented an exacerbated humoral response against myelin antigens while stressed animals with more severe clinical symptoms exhibited a significantly diminished one. Besides, we detected the presence of specific IgG1 associated with the exposure to CVS before the induction of EAE. Our results show that, depending on the timing of the exposure of Wistar rats to the CVS, the neuroendocrine disbalance favors a more pronounced humoral or cellular profile of the response.

Characterization of passive permeability at the blood-tumor barrier in five preclinical models of brain metastases of breast cancer

PubMed Central

Adkins, Chris E.; Mohammad, Afroz S.; Terrell-Hall, Tori; Dolan, Emma L.; Shah, Neal; Sechrest, Emily; Griffith, Jessica; Lockman, Paul R.

2016-01-01

The blood brain barrier (BBB) is compromised in brain metastases, allowing for enhanced drug permeation into brain. The extent and heterogeneity of BBB permeability in metastatic lesions is important when considering the administration of chemotherapeutics. Since permeability characteristics have been described in limited experimental models of brain metastases, we sought to define these changes in five brain-tropic breast cancer cell lines: MDA-MB-231BR (triple negative), MDA-MB-231BR-HER2, JIMT-1-BR3, 4T1-BR5 (murine), and SUM190 (inflammatory HER2 expressing). Permeability was assessed using quantitative autoradiography and fluorescence microscopy by co-administration of the tracers 14C-aminoisobutyric acid (AIB) and Texas Red conjugated dextran (TRD) prior to euthanasia. Each experimental brain metastases model produced variably increased permeability to both tracers; additionally, the magnitude of heterogeneity was different among each model with the highest ranges observed in the SUM190 (up to 45-fold increase in AIB) and MDA-MB-231BR-HER2 (up to 33-fold in AIB) models while the lowest range was observed in the JIMT-1-BR3 (up to 5.5-fold in AIB) model. There was no strong correlation observed between lesion size and permeability in any of these preclinical models of brain metastases. Interestingly, the experimental models resulting in smaller mean metastases size resulted in shorter median survival while models producing larger lesions had longer median survival. These findings strengthen the evidence of heterogeneity in brain metastases of breast cancer by utilizing five unique experimental models and simultaneously emphasize the challenges of chemotherapeutic approaches to treat brain metastases. PMID:26944053

Animal models of asthma: utility and limitations.

PubMed

Aun, Marcelo Vivolo; Bonamichi-Santos, Rafael; Arantes-Costa, Fernanda Magalhães; Kalil, Jorge; Giavina-Bianchi, Pedro

2017-01-01

Clinical studies in asthma are not able to clear up all aspects of disease pathophysiology. Animal models have been developed to better understand these mechanisms and to evaluate both safety and efficacy of therapies before starting clinical trials. Several species of animals have been used in experimental models of asthma, such as Drosophila , rats, guinea pigs, cats, dogs, pigs, primates and equines. However, the most common species studied in the last two decades is mice, particularly BALB/c. Animal models of asthma try to mimic the pathophysiology of human disease. They classically include two phases: sensitization and challenge. Sensitization is traditionally performed by intraperitoneal and subcutaneous routes, but intranasal instillation of allergens has been increasingly used because human asthma is induced by inhalation of allergens. Challenges with allergens are performed through aerosol, intranasal or intratracheal instillation. However, few studies have compared different routes of sensitization and challenge. The causative allergen is another important issue in developing a good animal model. Despite being more traditional and leading to intense inflammation, ovalbumin has been replaced by aeroallergens, such as house dust mites, to use the allergens that cause human disease. Finally, researchers should define outcomes to be evaluated, such as serum-specific antibodies, airway hyperresponsiveness, inflammation and remodeling. The present review analyzes the animal models of asthma, assessing differences between species, allergens and routes of allergen administration.

The adult nasopharyngeal microbiome as a determinant of pneumococcal acquisition.

PubMed

Cremers, Amelieke Jh; Zomer, Aldert L; Gritzfeld, Jenna F; Ferwerda, Gerben; van Hijum, Sacha Aft; Ferreira, Daniela M; Shak, Joshua R; Klugman, Keith P; Boekhorst, Jos; Timmerman, Harro M; de Jonge, Marien I; Gordon, Stephen B; Hermans, Peter Wm

2014-01-01

Several cohort studies have indicated associations between S. pneumoniae and other microbes in the nasopharynx. To study causal relationships between the nasopharyngeal microbiome and pneumococcal carriage, we employed an experimental human pneumococcal carriage model. Healthy adult volunteers were assessed for pneumococcal carriage by culture of nasal wash samples (NWS). Those without natural pneumococcal carriage received an intranasal pneumococcal inoculation with serotype 6B or 23F. The composition of the nasopharyngeal microbiome was longitudinally studied by 16S rDNA pyrosequencing on NWS collected before and after challenge. Among 40 selected volunteers, 10 were natural carriers and 30 were experimentally challenged. At baseline, five distinct nasopharyngeal microbiome profiles were identified. The phylogenetic distance between microbiomes of natural pneumococcal carriers was particularly large compared to non-carriers. A more diverse microbiome prior to inoculation was associated with the establishment of pneumococcal carriage. Perturbation of microbiome diversity upon pneumococcal challenge was strain specific. Shifts in microbiome profile occurred after pneumococcal exposure, and those volunteers who acquired carriage more often diverted from their original profile. S. pneumoniae was little prominent in the microbiome of pneumococcal carriers. Pneumococcal acquisition in healthy adults is more likely to occur in a diverse microbiome and appears to promote microbial heterogeneity.

Controlled human infection with RSV: The opportunities of experimental challenge.

PubMed

Habibi, Maximillian S; Chiu, Christopher

2017-01-11

Despite the recent explosion in RSV vaccine development, there remain substantial hurdles to overcome before licensing of effective vaccines will allow widespread use, particularly in high-risk populations. Incomplete understanding of mechanisms and correlates of protection against RSV mean that, for the time being, successful RSV vaccines must directly demonstrate efficacy, which necessitates large and costly clinical trials in naturally infected patients. To mitigate the risks inherent in progressing to these late-stage trials, experimental human RSV infection studies have recently been re-established, representing the interface between pre-clinical models and observational studies of patients. Not only can they be used for early proof-of-concept clinical trials to test vaccine efficacy, but human challenge studies also offer the potential to better understand protective immunity against RSV infection to improve vaccine design and delivery. In the past, controlled human infection studies with RSV have been instrumental in elucidating the influence of factors such as route of infection and type of inoculum on the course of disease. Recently, efficacy trials of novel RSV antiviral drugs have also been successfully undertaken. Now, with advances in technology, detailed investigations of human mucosal immunity in the RSV-infected airway are possible. These have indicated defects in RSV-induced humoral and CD8+ T cell immunity that may contribute to the recurrent symptomatic infection that occurs throughout life and should be circumvented by optimal vaccines. Here, we discuss the insights derived from RSV human challenge models; the major impediments to their more widespread uptake; and their potential benefit in accelerating vaccine development, including future directions to further enhance the relevance of these models to at-risk patient populations. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Synthetic biology as it relates to CAM photosynthesis: challenges and opportunities.

PubMed

DePaoli, Henrique C; Borland, Anne M; Tuskan, Gerald A; Cushman, John C; Yang, Xiaohan

2014-07-01

To meet future food and energy security needs, which are amplified by increasing population growth and reduced natural resource availability, metabolic engineering efforts have moved from manipulating single genes/proteins to introducing multiple genes and novel pathways to improve photosynthetic efficiency in a more comprehensive manner. Biochemical carbon-concentrating mechanisms such as crassulacean acid metabolism (CAM), which improves photosynthetic, water-use, and possibly nutrient-use efficiency, represent a strategic target for synthetic biology to engineer more productive C3 crops for a warmer and drier world. One key challenge for introducing multigene traits like CAM onto a background of C3 photosynthesis is to gain a better understanding of the dynamic spatial and temporal regulatory events that underpin photosynthetic metabolism. With the aid of systems and computational biology, vast amounts of experimental data encompassing transcriptomics, proteomics, and metabolomics can be related in a network to create dynamic models. Such models can undergo simulations to discover key regulatory elements in metabolism and suggest strategic substitution or augmentation by synthetic components to improve photosynthetic performance and water-use efficiency in C3 crops. Another key challenge in the application of synthetic biology to photosynthesis research is to develop efficient systems for multigene assembly and stacking. Here, we review recent progress in computational modelling as applied to plant photosynthesis, with attention to the requirements for CAM, and recent advances in synthetic biology tool development. Lastly, we discuss possible options for multigene pathway construction in plants with an emphasis on CAM-into-C3 engineering. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Dysregulation of metabolic pathways in a mouse model of allergic asthma.

PubMed

Quinn, K D; Schedel, M; Nkrumah-Elie, Y; Joetham, A; Armstrong, M; Cruickshank-Quinn, C; Reisdorph, R; Gelfand, E W; Reisdorph, N

2017-09-01

Asthma is a complex lung disease resulting from the interplay of genetic and environmental factors. To understand the molecular changes that occur during the development of allergic asthma without genetic and environmental confounders, an experimental model of allergic asthma in mice was used. Our goals were to (1) identify changes at the small molecule level due to allergen exposure, (2) determine perturbed pathways due to disease, and (3) determine whether small molecule changes correlate with lung function. In this experimental model of allergic asthma, matched bronchoalveolar lavage (BAL) fluid and plasma were collected from three groups of C57BL6 mice (control vs sensitized and/or challenged with ovalbumin, n=3-5/group) 6 hour, 24 hour, and 48 hour after the last challenge. Samples were analyzed using liquid chromatography-mass spectrometry-based metabolomics. Airway hyper-responsiveness (AHR) measurements and differential cell counts were performed. In total, 398 and 368 dysregulated metabolites in the BAL fluid and plasma of sensitized and challenged mice were identified, respectively. These belonged to four, interconnected pathways relevant to asthma pathogenesis: sphingolipid metabolism (P=6.6×10 -5 ), arginine and proline metabolism (P=1.12×10 -7 ), glycerophospholipid metabolism (P=1.3×10 -10 ), and the neurotrophin signaling pathway (P=7.0×10 -6 ). Furthermore, within the arginine and proline metabolism pathway, a positive correlation between urea-1-carboxylate and AHR was observed in plasma metabolites, while ornithine revealed a reciprocal effect. In addition, agmatine positively correlated with lung eosinophilia. These findings point to potential targets and pathways that may be central to asthma pathogenesis and can serve as novel therapeutic targets. © 2017 EAACI and John Wiley and Sons A/S. Published by John Wiley and Sons Ltd.

Resistance and Protective Immunity in Redfish Lake Sockeye Salmon Exposed to M Type Infectious Hematopoietic Necrosis Virus (IHNV)

USGS Publications Warehouse

Kurath, Gael; Garver, Kyle; Purcell, Maureen K.; LaPatra, Scott E.

2010-01-01

Differential virulence of infectious hematopoietic necrosis virus (IHNV) isolates from the U and M phylogenetic subgroups is clearly evident in the Redfish Lake (RFL) strain of sockeye salmon Oncorhynchus nerka. In these fish, experimental immersion challenges with U isolates cause extremely high mortality and M isolates cause low or no mortality. When survivors of M virus immersion challenges were exposed to a secondary challenge with virulent U type virus they experienced high mortality, indicating that the primary M challenge did not elicit protective immunity. Delivery of a moderate dose (2 × 104 plaque-forming units [PFU]/fish) of virus by intraperitoneal injection challenge did not overcome RFL sockeye salmon resistance to M type IHNV. Injection challenge with a high dose (5 × 106 PFU/fish) of M type virus caused 10% mortality, and in this case survivors did develop protective immunity against a secondary U type virus challenge. Thus, although it is possible for M type IHNV to elicit cross-protective immunity in this disease model, it does not develop after immersion challenge despite entry, transient replication of M virus to low levels, stimulation of innate immune genes, and development of neutralizing antibodies in some fish.

Efficacy of rabies immunoglobulins in an experimental post-exposure prophylaxis rodent model.

PubMed

Servat, Alexandre; Lutsch, Charles; Delore, Valentine; Lang, Jean; Veitch, Keith; Cliquet, Florence

2003-12-12

In a recently published Syrian hamster animal challenge study [Vaccine 19 (2001) 2273], a highly purified, heat-treated equine rabies immunoglobulin (pERIG HT, Favirab) did not elicit satisfactory protection. The efficacies of this batch, a second stage pERIG HT batch and reference RIG preparations (Imorab, Imogam Rage pasteurised, Berna antiserum) were compared in mice challenged with either Ariana canine field strain or CVS strain. Survival rates against Ariana challenge with the second pERIG HT batch were indistinguishable from those of other licensed preparations (83-90% survival), but the deficient batch did not provide satisfactory protection (53%). These data confirm the inadequate response to a first stage pERIG HT batch, but a current batch provides equivalent protection to that afforded by licensed HRIG and ERIG preparations.

Efficacy of a Gal-lectin subunit vaccine against experimental Entamoeba histolytica infection and colitis in baboons (Papio sp.).

PubMed

Abd Alla, Mohamed D; Wolf, Roman; White, Gary L; Kosanke, Stanley D; Cary, David; Verweij, Jaco J; Zhang, Mie-Jie; Ravdin, Jonathan I

2012-04-26

To determine the efficacy of a Gal-lectin based intranasal synthetic peptide vaccine, we developed a new experimental primate model of Entamoeba histolytica intestinal infection. Release of xenic E. histolytica trophozoites (5×10(6)) into the small bowel of baboons (Papio sp.) resulted in a rapid intestinal anti-amebic antibody response and a brief infection; however, release of trophozoites directly into the cecum (5 baboons) elicited a sustained E. histolytica infection, as determined by quantitative fecal PCR, and an ulcerative, inflammatory colitis observed on colonoscopy and histopathology. In three controlled experiments, baboons received four immunizations at seven day intervals of 1600 μg of the vaccine/nostril, with Cholera toxin, 20 μg/nostril as adjuvant; vaccinated (n=6) and control baboons (n=6) baboons were then challenged via colonoscopy with xenic trophozoites (5×10(6)). During 90 days of follow up, 250 of 415 (60.24%) fecal samples in control baboons had a (+) PCR for E. histolytica, compared to only 36 of 423 (8.51%) samples from vaccinated baboons (P<0.001). All 6 vaccinated baboons were free of infection by the 51st day after challenge, 5 of 6 controls positive had (+) fecal PCRs for up to 126 days post-challenge (P=0.019). Inflammatory colitis developed in 4 of 6 control baboons post-challenge, with invasive E. histolytica trophozoites present in 2 of the 4 on histopathology. There was no evidence of inflammatory colitis or parasite invasion in any of the vaccinated baboons; there was a strong inverse correlation between positive ELISA OD value indicating the presence of intestinal anti-peptide IgA antibodies and baboons having a positive fecal PCR CT value, P<0.001. In conclusion, we developed a novel primate model of E. histolytica intestinal infection and demonstrated that a Gal-lectin-based intranasal synthetic peptide vaccine was highly efficacious in preventing experimental E. histolytica infection and colitis in baboons. Copyright © 2012 Elsevier Ltd. All rights reserved.

Ultrasonic Vibration Assisted Grinding of Bio-ceramic Materials: Modeling, Simulation, and Experimental Investigations on Edge Chipping

NASA Astrophysics Data System (ADS)

Tesfay, Hayelom D.

Bio-ceramics are those engineered materials that find their applications in the field of biomedical engineering or medicine. They have been widely used in dental restorations, repairing bones, joint replacements, pacemakers, kidney dialysis machines, and respirators. etc. due to their physico-chemical properties, such as excellent corrosion resistance, good biocompatibility, high strength and high wear resistance. Because of their inherent brittleness and hardness nature they are difficult to machine to exact sizes and dimensions. Abrasive machining processes such as grinding is one of the most widely used manufacturing processes for bioceramics. However, the principal technical challenge resulted from these machining is edge chipping. Edge chipping is a common edge failure commonly observed during the machining of bio-ceramic materials. The presence of edge chipping on bio-ceramic products affects dimensional accuracy, increases manufacturing cost, hider their industrial applications and causes potential failure during service. To overcome these technological challenges, a new ultrasonic vibration-assisted grinding (UVAG) manufacturing method has been developed and employed in this research. The ultimate aim of this study is to develop a new cost-effective manufacturing process relevant to eliminate edge chippings in grinding of bio-ceramic materials. In this dissertation, comprehensive investigations will be carried out using experimental, theoretical, and numerical approaches to evaluate the effect of ultrasonic vibrations on edge chipping of bioceramics. Moreover, effects of nine input variables (static load, vibration frequency, grinding depth, spindle speed, grinding distance, tool speed, grain size, grain number, and vibration amplitude) on edge chipping will be studied based on the developed models. Following a description of previous research and existing approaches, a series of experimental tests on three bio-ceramic materials (Lava, partially fired Lava, and Alumina) were conducted. Based on the experimental results, analytical models for UVAG and CG (conventional grinding without ultrasonic vibration) processes were developed. As for the numerical study, an extended finite element method (XFEM) based on Virtual Crack Closure Technique (VCCT) in ABAQUS was used to model the formation of edge chippings both for UVAG and CG processes. The experimental results are compared against the numerical FEA and the analytical models. The experimental, theoretical, and computational simulation results revealed that the edge chipping size of bioceramics can be significantly reduced with the assistance of ultrasonic vibration. The investigation procedures and the results obtained in this dissertation would be used as a reference and practical guidance for choosing reasonable process variables as well as designing mathematical (analytical and numerical) models in manufacturing industries and academic institutions when the edge chippings of brittle materials are expected to be controlled.

In vivo therapeutic efficacy and pharmacokinetics of colistin sulfate in an experimental model of enterotoxigenic Escherichia coli infection in weaned pigs.

PubMed

Rhouma, Mohamed; Beaudry, Francis; Thériault, William; Bergeron, Nadia; Beauchamp, Guy; Laurent-Lewandowski, Sylvette; Fairbrother, John Morris; Letellier, Ann

2016-05-27

Enterotoxigenic Escherichia coli (ETEC: F4) associated with post-weaning diarrhea (PWD) in pigs has developed resistance against several antimicrobial families, leading to increased use of colistin sulfate (CS) for the treatment of this disease. The objective of this study was to determine the efficacy of oral CS treatment in experimental PWD due to ETEC: F4 challenge and determine the effect of this challenge on CS intestinal absorption. In this study, 96 pigs were divided into two trials based on CS dose (100 000 or 50 000 IU/kg). Fecal shedding of ETEC: F4, total E. coli, and CS-resistant E. coli, diarrhea scores, and weight changes were evaluated. Colistin sulfate plasma concentrations were determined by HPLC-MS/MS. Regardless of the dose, CS treatment resulted in a reduction of fecal ETEC: F4 and total E. coli shedding, and in diarrhea scores but only during the treatment period. However, CS treatment resulted in a slight increase in fecal shedding of CS resistant E. coli and did not prevent weight loss in challenged pigs. In addition, challenge with ETEC: F4 resulted in an increase of CS intestinal absorption. Our study is among the first to demonstrate that under controlled conditions, CS was effective in reducing fecal shedding of ETEC: F4 and total E. coli in experimental PWD. However, CS treatment was associated with a slight selection pressure on E. coli and did not prevent pig weight loss. Further studies are needed in field conditions, to better characterize CS therapeutic regimen efficacy and bacterial resistance dissemination.

Modeling Pre- and Post- Wildfire Hydrologic Response to Vegetation Change in the Valles Caldera National Preserve, NM

NASA Astrophysics Data System (ADS)

Gregory, A. E.; Benedict, K. K.; Zhang, S.; Savickas, J.

2017-12-01

Large scale, high severity wildfires in forests have become increasingly prevalent in the western United States due to fire exclusion. Although past work has focused on the immediate consequences of wildfire (ie. runoff magnitude and debris flow), little has been done to understand the post wildfire hydrologic consequences of vegetation regrowth. Furthermore, vegetation is often characterized by static parameterizations within hydrological models. In order to understand the temporal relationship between hydrologic processes and revegetation, we modularized and partially automated the hydrologic modeling process to increase connectivity between remotely sensed data, the Virtual Watershed Platform (a data management resource, called the VWP), input meteorological data, and the Precipitation-Runoff Modeling System (PRMS). This process was used to run simulations in the Valles Caldera of NM, an area impacted by the 2011 Las Conchas Fire, in PRMS before and after the Las Conchas to evaluate hydrologic process changes. The modeling environment addressed some of the existing challenges faced by hydrological modelers. At present, modelers are somewhat limited in their ability to push the boundaries of hydrologic understanding. Specific issues faced by modelers include limited computational resources to model processes at large spatial and temporal scales, data storage capacity and accessibility from the modeling platform, computational and time contraints for experimental modeling, and the skills to integrate modeling software in ways that have not been explored. By taking an interdisciplinary approach, we were able to address some of these challenges by leveraging the skills of hydrologic, data, and computer scientists; and the technical capabilities provided by a combination of on-demand/high-performance computing, distributed data, and cloud services. The hydrologic modeling process was modularized to include options for distributing meteorological data, parameter space experimentation, data format transformation, looping, validation of models and containerization for enabling new analytic scenarios. The user interacts with the modules through Jupyter Notebooks which can be connected to an on-demand computing and HPC environment, and data services built as part of the VWP.

A Review of Numerical Simulation and Analytical Modeling for Medical Devices Safety in MRI

PubMed Central

Kabil, J.; Belguerras, L.; Trattnig, S.; Pasquier, C.; Missoffe, A.

2016-01-01

Summary Objectives To review past and present challenges and ongoing trends in numerical simulation for MRI (Magnetic Resonance Imaging) safety evaluation of medical devices. Methods A wide literature review on numerical and analytical simulation on simple or complex medical devices in MRI electromagnetic fields shows the evolutions through time and a growing concern for MRI safety over the years. Major issues and achievements are described, as well as current trends and perspectives in this research field. Results Numerical simulation of medical devices is constantly evolving, supported by calculation methods now well-established. Implants with simple geometry can often be simulated in a computational human model, but one issue remaining today is the experimental validation of these human models. A great concern is to assess RF heating on implants too complex to be traditionally simulated, like pacemaker leads. Thus, ongoing researches focus on alternative hybrids methods, both numerical and experimental, with for example a transfer function method. For the static field and gradient fields, analytical models can be used for dimensioning simple implants shapes, but limited for complex geometries that cannot be studied with simplifying assumptions. Conclusions Numerical simulation is an essential tool for MRI safety testing of medical devices. The main issues remain the accuracy of simulations compared to real life and the studies of complex devices; but as the research field is constantly evolving, some promising ideas are now under investigation to take up the challenges. PMID:27830244

Modeling Tumor Clonal Evolution for Drug Combinations Design

PubMed Central

Zhao, Boyang; Hemann, Michael T.; Lauffenburger, Douglas A.

2016-01-01

Cancer is a clonal evolutionary process. This presents challenges for effective therapeutic intervention, given the constant selective pressure towards drug resistance. Mathematical modeling from population genetics, evolutionary dynamics, and engineering perspectives are being increasingly employed to study tumor progression, intratumoral heterogeneity, drug resistance, and rational drug scheduling and combinations design. In this review, we discuss promising opportunities these inter-disciplinary approaches hold for advances in cancer biology and treatment. We propose that quantitative modeling perspectives can complement emerging experimental technologies to facilitate enhanced understanding of disease progression and improved capabilities for therapeutic drug regimen designs. PMID:28435907

Salmonella Fecal Shedding and Immune Responses are Dose- and Serotype- Dependent in Pigs

PubMed Central

Ivanek, Renata; Österberg, Julia; Gautam, Raju; Sternberg Lewerin, Susanna

2012-01-01

Despite the public health importance of Salmonella infection in pigs, little is known about the associated dynamics of fecal shedding and immunity. In this study, we investigated the transitions of pigs through the states of Salmonella fecal shedding and immune response post-Salmonella inoculation as affected by the challenge dose and serotype. Continuous-time multistate Markov models were developed using published experimental data. The model for shedding had four transient states, of which two were shedding (continuous and intermittent shedding) and two non-shedding (latency and intermittent non-shedding), and one absorbing state representing permanent cessation of shedding. The immune response model had two transient states representing responses below and above the seroconversion level. The effects of two doses [low (0.65×106 CFU/pig) and high (0.65×109 CFU/pig)] and four serotypes (Salmonella Yoruba, Salmonella Cubana, Salmonella Typhimurium, and Salmonella Derby) on the models' transition intensities were evaluated using a proportional intensities model. Results indicated statistically significant effects of the challenge dose and serotype on the dynamics of shedding and immune response. The time spent in the specific states was also estimated. Continuous shedding was on average 10–26 days longer, while intermittent non-shedding was 2–4 days shorter, in pigs challenged with the high compared to low dose. Interestingly, among pigs challenged with the high dose, the continuous and intermittent shedding states were on average up to 10–17 and 3–4 days longer, respectively, in pigs infected with S. Cubana compared to the other three serotypes. Pigs challenged with the high dose of S. Typhimurium or S. Derby seroconverted on average up to 8–11 days faster compared to the low dose. These findings highlight that Salmonella fecal shedding and immune response following Salmonella challenge are dose- and serotype-dependent and that the detection of specific Salmonella strains and immune responses in pigs are time-sensitive. PMID:22523553

Spectral response, dark current, and noise analyses in resonant tunneling quantum dot infrared photodetectors.

PubMed

Jahromi, Hamed Dehdashti; Mahmoodi, Ali; Sheikhi, Mohammad Hossein; Zarifkar, Abbas

2016-10-20

Reduction of dark current at high-temperature operation is a great challenge in conventional quantum dot infrared photodetectors, as the rate of thermal excitations resulting in the dark current increases exponentially with temperature. A resonant tunneling barrier is the best candidate for suppression of dark current, enhancement in signal-to-noise ratio, and selective extraction of different wavelength response. In this paper, we use a physical model developed by the authors recently to design a proper resonant tunneling barrier for quantum infrared photodetectors and to study and analyze the spectral response of these devices. The calculated transmission coefficient of electrons by this model and its dependency on bias voltage are in agreement with experimental results. Furthermore, based on the calculated transmission coefficient, the dark current of a quantum dot infrared photodetector with a resonant tunneling barrier is calculated and compared with the experimental data. The validity of our model is proven through this comparison. Theoretical dark current by our model shows better agreement with the experimental data and is more accurate than the previously developed model. Moreover, noise in the device is calculated. Finally, the effect of different parameters, such as temperature, size of quantum dots, and bias voltage, on the performance of the device is simulated and studied.

[Experimental whooping cough of nonhuman primate].

PubMed

Kubrava, D T; Medkova, A Iu; Siniashina, L N; Shevtsova, Z V; Matua, A Z; Kondzharia, I G; Barkaia, V S; Elistratova, Zh V; Karataev, G I; Mikvabia, Z Ia; Gintsburg, A L

2013-01-01

Despite considerable success in study of Bordetella pertussis virulence factors, pathogenesis of whooping cough, duration of B. pertussis bacteria persistence, types and mechanisms of immune response are still keep underinvestigated. It can be explained by the absence ofadequate experimental animal model for pertussis study. Our study estimates clinical and laboratory parameters of whooping cough in non-human primates of the Old World in the process of intranasan infection by virulent B. pertussis bacteria. Also the duration of B. pertussis bacteria persistence in animals was investigated. 14 animal units of 4 species of non-human primates of the Old World were used for intranasal infection. The examination of infect animals included: visual exploration of nasopharynx, thermometry, clinical and biochemical blood analyses, identification ofB. pertussis, using microbiologic and molecular genetic analyses, estimation of innate and adoptive immune factors. The development of infectious process was accompanied by generation of B. pertussis bacteria, catarrhal inflammation of nasopharyngeal mucosa, leucocytosis, hypoglycemia specific for pertussis, and activation of innate and adaptive immunity for all primates regardless of specie were seen. While repeated experimental infection in primates single bacterial colonies were registered during only first week after challenge. It occurs like the absence of inflammation of nasopharyngeal mucosa and the lack of laboratory marks of whooping cough, recorded after first challenge. The evident booster effect of humoral immunity was observed. As a model for investigation of B. pertussis bacteria persistence and immune response against whooping cough we suggest the usage of rhesus macaque as more available to experiments.

Verification of target motion effects on SAR imagery using the Gotcha GMTI challenge dataset

NASA Astrophysics Data System (ADS)

Hack, Dan E.; Saville, Michael A.

2010-04-01

This paper investigates the relationship between a ground moving target's kinematic state and its SAR image. While effects such as cross-range offset, defocus, and smearing appear well understood, their derivations in the literature typically employ simplifications of the radar/target geometry and assume point scattering targets. This study adopts a geometrical model for understanding target motion effects in SAR imagery, termed the target migration path, and focuses on experimental verification of predicted motion effects using both simulated and empirical datasets based on the Gotcha GMTI challenge dataset. Specifically, moving target imagery is generated from three data sources: first, simulated phase history for a moving point target; second, simulated phase history for a moving vehicle derived from a simulated Mazda MPV X-band signature; and third, empirical phase history from the Gotcha GMTI challenge dataset. Both simulated target trajectories match the truth GPS target position history from the Gotcha GMTI challenge dataset, allowing direct comparison between all three imagery sets and the predicted target migration path. This paper concludes with a discussion of the parallels between the target migration path and the measurement model within a Kalman filtering framework, followed by conclusions.

Fundamental Activity Constraints Lead to Specific Interpretations of the Connectome.

PubMed

Schuecker, Jannis; Schmidt, Maximilian; van Albada, Sacha J; Diesmann, Markus; Helias, Moritz

2017-02-01

The continuous integration of experimental data into coherent models of the brain is an increasing challenge of modern neuroscience. Such models provide a bridge between structure and activity, and identify the mechanisms giving rise to experimental observations. Nevertheless, structurally realistic network models of spiking neurons are necessarily underconstrained even if experimental data on brain connectivity are incorporated to the best of our knowledge. Guided by physiological observations, any model must therefore explore the parameter ranges within the uncertainty of the data. Based on simulation results alone, however, the mechanisms underlying stable and physiologically realistic activity often remain obscure. We here employ a mean-field reduction of the dynamics, which allows us to include activity constraints into the process of model construction. We shape the phase space of a multi-scale network model of the vision-related areas of macaque cortex by systematically refining its connectivity. Fundamental constraints on the activity, i.e., prohibiting quiescence and requiring global stability, prove sufficient to obtain realistic layer- and area-specific activity. Only small adaptations of the structure are required, showing that the network operates close to an instability. The procedure identifies components of the network critical to its collective dynamics and creates hypotheses for structural data and future experiments. The method can be applied to networks involving any neuron model with a known gain function.

A perspective on modeling the multiscale response of energetic materials

NASA Astrophysics Data System (ADS)

Rice, Betsy M.

2017-01-01

The response of an energetic material to insult is perhaps one of the most difficult processes to model due to concurrent chemical and physical phenomena occurring over scales ranging from atomistic to continuum. Unraveling the interdependencies of these complex processes across the scales through modeling can only be done within a multiscale framework. In this paper, I will describe progress in the development of a predictive, experimentally validated multiscale reactive modeling capability for energetic materials at the Army Research Laboratory. I will also describe new challenges and research opportunities that have arisen in the course of our development which should be pursued in the future.

Robust model-based analysis of single-particle tracking experiments with Spot-On

PubMed Central

Grimm, Jonathan B; Lavis, Luke D

2018-01-01

Single-particle tracking (SPT) has become an important method to bridge biochemistry and cell biology since it allows direct observation of protein binding and diffusion dynamics in live cells. However, accurately inferring information from SPT studies is challenging due to biases in both data analysis and experimental design. To address analysis bias, we introduce ‘Spot-On’, an intuitive web-interface. Spot-On implements a kinetic modeling framework that accounts for known biases, including molecules moving out-of-focus, and robustly infers diffusion constants and subpopulations from pooled single-molecule trajectories. To minimize inherent experimental biases, we implement and validate stroboscopic photo-activation SPT (spaSPT), which minimizes motion-blur bias and tracking errors. We validate Spot-On using experimentally realistic simulations and show that Spot-On outperforms other methods. We then apply Spot-On to spaSPT data from live mammalian cells spanning a wide range of nuclear dynamics and demonstrate that Spot-On consistently and robustly infers subpopulation fractions and diffusion constants. PMID:29300163

Robust model-based analysis of single-particle tracking experiments with Spot-On.

PubMed

Hansen, Anders S; Woringer, Maxime; Grimm, Jonathan B; Lavis, Luke D; Tjian, Robert; Darzacq, Xavier

2018-01-04

Single-particle tracking (SPT) has become an important method to bridge biochemistry and cell biology since it allows direct observation of protein binding and diffusion dynamics in live cells. However, accurately inferring information from SPT studies is challenging due to biases in both data analysis and experimental design. To address analysis bias, we introduce 'Spot-On', an intuitive web-interface. Spot-On implements a kinetic modeling framework that accounts for known biases, including molecules moving out-of-focus, and robustly infers diffusion constants and subpopulations from pooled single-molecule trajectories. To minimize inherent experimental biases, we implement and validate stroboscopic photo-activation SPT (spaSPT), which minimizes motion-blur bias and tracking errors. We validate Spot-On using experimentally realistic simulations and show that Spot-On outperforms other methods. We then apply Spot-On to spaSPT data from live mammalian cells spanning a wide range of nuclear dynamics and demonstrate that Spot-On consistently and robustly infers subpopulation fractions and diffusion constants. © 2018, Hansen et al.

Unravelling the electrochemical double layer by direct probing of the solid/liquid interface

DOE PAGES

Favaro, Marco; Jeong, Beomgyun; Ross, Philip N.; ...

2016-08-31

The electrochemical double layer plays a critical role in electrochemical processes. Whilst there have been many theoretical models predicting structural and electrical organization of the electrochemical double layer, the experimental verification of these models has been challenging due to the limitations of available experimental techniques. The induced potential drop in the electrolyte has never been directly observed and verified experimentally, to the best of our knowledge. In this study, we report the direct probing of the potential drop as well as the potential of zero charge by means of ambient pressure X-ray photoelectron spectroscopy performed under polarization conditions. By analyzingmore » the spectra of the solvent (water) and a spectator neutral molecule with numerical simulations of the electric field, we discern the shape of the electrochemical double layer profile. In addition, we determine how the electrochemical double layer changes as a function of both the electrolyte concentration and applied potential.« less

Neuropharmacological sequelae of persistent CNS viral infections: lessons from Borna disease virus.

PubMed

Solbrig, Marylou V; Koob, George F

2003-03-01

Borna Disease Virus (BDV) is a neurotropic RNA virus that is worldwide in distribution, causing movement and behavior disorders in a wide range of animal species. BDV has also been reported to be associated with neuropsychiatric diseases of humans by serologic study and by recovery of nucleic acid or virus from blood or brain. Natural infections of horses and sheep produce encephalitis with erratic excited behaviors, hyperkinetic movement or gait abnormalities; naturally infected cats have ataxic "staggering disease." Experimentally infected primates develop hyperactivity, aggression, disinhibition, then apathy; prosimians (lower primates) have hyperactivity, circadian disruption, abnormal social and dominance behaviors, and postural disorders. However, the neuropharmacological determinants of BD phenotypes in laboratory and natural hosts are incompletely understood. Here we review how experimentally infected rodents have provided models for examining behavioral, pharmacologic, and biochemical responses to viral challenge, and how rodents experimentally infected as neonates or as adolescents are providing models for examining age-specific neuropharmacological adaptations to viral injury.

New insights into RAS biology reinvigorate interest in mathematical modeling of RAS signaling

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

Erickson, Keesha E.; Rukhlenko, Oleksii S.; Posner, Richard G.

RAS is the most frequently mutated gene across human cancers, but developing inhibitors of mutant RAS has proven to be challenging. Given the difficulties of targeting RAS directly, drugs that impact the other components of pathways where mutant RAS operates may potentially be effective. However, the system-level features, including different localizations of RAS isoforms, competition between downstream effectors, and interlocking feedback and feed-forward loops, must be understood to fully grasp the opportunities and limitations of inhibiting specific targets. Mathematical modeling can help us discern the system-level impacts of these features in normal and cancer cells. New technologies enable the acquisitionmore » of experimental data that will facilitate development of realistic models of oncogenic RAS behavior. In light of the wealth of empirical data accumulated over decades of study and the advancement of experimental methods for gathering new data, modelers now have the opportunity to advance progress toward realization of targeted treatment for mutant RAS-driven cancers.« less

New insights into RAS biology reinvigorate interest in mathematical modeling of RAS signaling

DOE PAGES

Erickson, Keesha E.; Rukhlenko, Oleksii S.; Posner, Richard G.; ...

2018-03-05

RAS is the most frequently mutated gene across human cancers, but developing inhibitors of mutant RAS has proven to be challenging. Given the difficulties of targeting RAS directly, drugs that impact the other components of pathways where mutant RAS operates may potentially be effective. However, the system-level features, including different localizations of RAS isoforms, competition between downstream effectors, and interlocking feedback and feed-forward loops, must be understood to fully grasp the opportunities and limitations of inhibiting specific targets. Mathematical modeling can help us discern the system-level impacts of these features in normal and cancer cells. New technologies enable the acquisitionmore » of experimental data that will facilitate development of realistic models of oncogenic RAS behavior. In light of the wealth of empirical data accumulated over decades of study and the advancement of experimental methods for gathering new data, modelers now have the opportunity to advance progress toward realization of targeted treatment for mutant RAS-driven cancers.« less

New insights into RAS biology reinvigorate interest in mathematical modeling of RAS signaling.

PubMed

Erickson, Keesha E; Rukhlenko, Oleksii S; Posner, Richard G; Hlavacek, William S; Kholodenko, Boris N

2018-03-05

RAS is the most frequently mutated gene across human cancers, but developing inhibitors of mutant RAS has proven to be challenging. Given the difficulties of targeting RAS directly, drugs that impact the other components of pathways where mutant RAS operates may potentially be effective. However, the system-level features, including different localizations of RAS isoforms, competition between downstream effectors, and interlocking feedback and feed-forward loops, must be understood to fully grasp the opportunities and limitations of inhibiting specific targets. Mathematical modeling can help us discern the system-level impacts of these features in normal and cancer cells. New technologies enable the acquisition of experimental data that will facilitate development of realistic models of oncogenic RAS behavior. In light of the wealth of empirical data accumulated over decades of study and the advancement of experimental methods for gathering new data, modelers now have the opportunity to advance progress toward realization of targeted treatment for mutant RAS-driven cancers. Copyright © 2018 Elsevier Ltd. All rights reserved.

Mechanical signaling coordinates the embryonic heart

NASA Astrophysics Data System (ADS)

Chiou, Kevin; Rocks, Jason; Prosser, Benjamin; Discher, Dennis; Liu, Andrea

The heart is an active material which relies on robust signaling mechanisms between cells in order to produce well-timed, coordinated beats. Heart tissue is composed primarily of active heart muscle cells (cardiomyocytes) embedded in a passive extracellular matrix. During a heartbeat, cardiomyocyte contractions are coordinated across the heart to form a wavefront that propagates through the tissue to pump blood. In the adult heart, this contractile wave is coordinated via intercellular electrical signaling.Here we present theoretical and experimental evidence for mechanical coordination of embryonic heartbeats. We model cardiomyocytes as mechanically excitable Eshelby inclusions embedded in an overdamped elastic-fluid biphasic medium. For physiological parameters, this model replicates recent experimental measurements of the contractile wavefront which are not captured by electrical signaling models. We additionally challenge our model by pharmacologically blocking gap junctions, inhibiting electrical signaling between myocytes. We find that while adult hearts stop beating almost immediately after gap junctions are blocked, embryonic hearts continue beating even at significantly higher concentrations, providing strong support for a mechanical signaling mechanism.

Thermochemical Modeling of Nonequilibrium Oxygen Flows

NASA Astrophysics Data System (ADS)

Neitzel, Kevin Joseph

The development of hypersonic vehicles leans heavily on computational simulation due to the high enthalpy flow conditions that are expensive and technically challenging to replicate experimentally. The accuracy of the nonequilibrium modeling in the computer simulations dictates the design margin that is required for the thermal protection system and flight dynamics. Previous hypersonic vehicles, such as Apollo and the Space Shuttle, were primarily concerned with re-entry TPS design. The strong flow conditions of re-entry, involving Mach numbers of 25, quickly dissociate the oxygen molecules in air. Sustained flight, hypersonic vehicles will be designed to operate in Mach number ranges of 5 to 10. The oxygen molecules will not quickly dissociate and will play an important role in the flow field behavior. The development of nonequilibrium models of oxygen is crucial for limiting modeling uncertainty. Thermochemical nonequilibrium modeling is investigated for oxygen flows. Specifically, the vibrational relaxation and dissociation behavior that dominate the nonequilibrium physics in this flight regime are studied in detail. The widely used two-temperature (2T) approach is compared to the higher fidelity and more computationally expensive state-to-state (STS) approach. This dissertation utilizes a wide range of rate sources, including newly available STS rates, to conduct a comprehensive study of modeling approaches for hypersonic nonequilibrium thermochemical modeling. Additionally, the physical accuracy of the computational methods are assessed by comparing the numerical results with available experimental data. The numerical results and experimental measurements present strong nonequilibrium, and even non-Boltzmann behavior in the vibrational energy mode for the sustained hypersonic flight regime. The STS approach is able to better capture the behavior observed in the experimental data, especially for stronger nonequilibrium conditions. Additionally, a reduced order model (ROM) modification to the 2T model is developed to improve the capability of the 2T approach framework.

Susceptibility of Australian Redfin Perch Perca fluviatilis Experimentally Challenged with Epizootic Hematopoietic Necrosis Virus (EHNV).

PubMed

Becker, Joy A; Tweedie, Alison; Gilligan, Dean; Asmus, Martin; Whittington, Richard J

2016-06-01

The ranavirus epizootic hematopoietic necrosis virus (EHNV) is endemic to Australia and is listed by the Office International des Epizooties. Clinical outbreaks have only been observed in wild populations of Redfin Perch Perca fluviatilis (also known as Eurasian Perch) and farmed populations of Rainbow Trout Oncorhynchus mykiss. The initial outbreaks of EHNV describe all age-classes of Redfin Perch as being susceptible and can lead to epidemic fish kills. Subsequently, experimental challenge studies using either cohabitation with the virus or injection exposures resulted in mixed susceptibilities across various age-groupings of Redfin Perch. We used an experimental bath challenge model to investigate the susceptibility of Redfin Perch collected from areas with and without a history of EHNV outbreaks. The median survival time for fish from Blowering Dam in New South Wales, a zone with a history of EHNV outbreaks, was 35 d, compared with fish from other areas, which had a median survival between 12 and 28 d postexposure. Redfin Perch from Blowering Dam demonstrated an increased mortality associated with epizootic hematopoietic necrosis up to approximately day 14 after exposure, and then there was a significantly reduced risk of mortality until the end of the trial compared with all other fish. Redfin Perch from Blowering Dam had markedly decreased susceptibility to EHNV, and less than 40% became infected following a bath challenge. In contrast, Redfin Perch from neighboring (e.g., Bethungra Dam and Tarcutta Creek) and distant water bodies (e.g., in Western Australia) with no previous history of EHNVdisplayed moderate to high susceptibility when given a bath challenge. Potential factors for the observed changes in the host-pathogen relationship include intense positive selection pressure for resistant fish following epizootic hematopoietic necrosis outbreaks and subsequent attenuation of the virulence of the virus in resistant fish. Received August 22, 2015; accepted February 13, 2016.

Multi-channel probes to understand fission dynamics

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

Mosby, Shea Morgan

2016-04-15

Explaining the origin of the elements is a major outstanding question in nuclear astrophysics. Observed elemental abundance distribution shows strong nuclear physics effects. In conclusion, neutron-induced reactions are important for nuclear astrophysics and applied fields in nuclear energy and security. LANSCE has a program to address many of these questions directly with neutron beams on (near-)stable nuclei. Increasing demand for correlated data to test details of fission models poses additional challenges. Possibilities exist to extend existing experimental efforts to radioactive beam facilities. Kinematic focusing from using inverse kinematics has potential to circumvent some challenges associated with measuring correlations between fissionmore » output channels.« less

Refined approach for quantification of in vivo ischemia-reperfusion injury in the mouse heart

PubMed Central

Medway, Debra J.; Schulz-Menger, Jeanette; Schneider, Jurgen E.; Neubauer, Stefan; Lygate, Craig A.

2009-01-01

Cardiac ischemia-reperfusion experiments in the mouse are important in vivo models of human disease. Infarct size is a particularly important scientific readout as virtually all cardiocirculatory pathways are affected by it. Therefore, such measurements must be exact and valid. The histological analysis, however, remains technically challenging, and the resulting quality is often unsatisfactory. For this report we have scrutinized each step involved in standard double-staining histology. We have tested published approaches and challenged their practicality. As a result, we propose an improved and streamlined protocol, which consistently yields high-quality histology, thereby minimizing experimental noise and group sizes. PMID:19820193

Mixing behavior of a model cellulosic biomass slurry during settling and resuspension

DOE PAGES

Crawford, Nathan C.; Sprague, Michael A.; Stickel, Jonathan J.

2016-01-29

Thorough mixing during biochemical deconstruction of biomass is crucial for achieving maximum process yields and economic success. However, due to the complex morphology and surface chemistry of biomass particles, biomass mixing is challenging and currently it is not well understood. This study investigates the bulk rheology of negatively buoyant, non-Brownian α-cellulose particles during settling and resuspension. The torque signal of a vane mixer across two distinct experimental setups (vane-in-cup and vane-in-beaker) was used to understand how mixing conditions affect the distribution of biomass particles. During experimentation, a bifurcated torque response as a function of vane speed was observed, indicating thatmore » the slurry transitions from a “settling-dominant” regime to a “suspension-dominant” regime. The torque response of well-characterized fluids (i.e., DI water) were then used to empirically identify when sufficient mixing turbulence was established in each experimental setup. The predicted critical mixing speeds were in agreement with measured values, suggesting that secondary flows are required in order to keep the cellulose particles fully suspended. In addition, a simple scaling relationship was developed to model the entire torque signal of the slurry throughout settling and resuspension. Furthermore, qualitative and semi-quantitative agreement between the model and experimental results was observed.« less

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

Sanz Rodrigo, Javier; Chávez Arroyo, Roberto Aurelio; Moriarty, Patrick

The increasing size of wind turbines, with rotors already spanning more than 150 m diameter and hub heights above 100 m, requires proper modeling of the atmospheric boundary layer (ABL) from the surface to the free atmosphere. Furthermore, large wind farm arrays create their own boundary layer structure with unique physics. This poses significant challenges to traditional wind engineering models that rely on surface-layer theories and engineering wind farm models to simulate the flow in and around wind farms. However, adopting an ABL approach offers the opportunity to better integrate wind farm design tools and meteorological models. The challenge ismore » how to build the bridge between atmospheric and wind engineering model communities and how to establish a comprehensive evaluation process that identifies relevant physical phenomena for wind energy applications with modeling and experimental requirements. A framework for model verification, validation, and uncertainty quantification is established to guide this process by a systematic evaluation of the modeling system at increasing levels of complexity. In terms of atmospheric physics, 'building the bridge' means developing models for the so-called 'terra incognita,' a term used to designate the turbulent scales that transition from mesoscale to microscale. This range of scales within atmospheric research deals with the transition from parameterized to resolved turbulence and the improvement of surface boundary-layer parameterizations. The coupling of meteorological and wind engineering flow models and the definition of a formal model evaluation methodology, is a strong area of research for the next generation of wind conditions assessment and wind farm and wind turbine design tools. Some fundamental challenges are identified in order to guide future research in this area.« less

Global Quantitative Modeling of Chromatin Factor Interactions

PubMed Central

Zhou, Jian; Troyanskaya, Olga G.

2014-01-01

Chromatin is the driver of gene regulation, yet understanding the molecular interactions underlying chromatin factor combinatorial patterns (or the “chromatin codes”) remains a fundamental challenge in chromatin biology. Here we developed a global modeling framework that leverages chromatin profiling data to produce a systems-level view of the macromolecular complex of chromatin. Our model ultilizes maximum entropy modeling with regularization-based structure learning to statistically dissect dependencies between chromatin factors and produce an accurate probability distribution of chromatin code. Our unsupervised quantitative model, trained on genome-wide chromatin profiles of 73 histone marks and chromatin proteins from modENCODE, enabled making various data-driven inferences about chromatin profiles and interactions. We provided a highly accurate predictor of chromatin factor pairwise interactions validated by known experimental evidence, and for the first time enabled higher-order interaction prediction. Our predictions can thus help guide future experimental studies. The model can also serve as an inference engine for predicting unknown chromatin profiles — we demonstrated that with this approach we can leverage data from well-characterized cell types to help understand less-studied cell type or conditions. PMID:24675896

Prediction of Liquid Slosh Damping Using a High Resolution CFD Tool

NASA Technical Reports Server (NTRS)

Yang, H. Q.; Purandare, Ravi; Peugeot, John; West, Jeff

2012-01-01

Propellant slosh is a potential source of disturbance critical to the stability of space vehicles. The slosh dynamics are typically represented by a mechanical model of a spring mass damper. This mechanical model is then included in the equation of motion of the entire vehicle for Guidance, Navigation and Control analysis. Our previous effort has demonstrated the soundness of a CFD approach in modeling the detailed fluid dynamics of tank slosh and the excellent accuracy in extracting mechanical properties (slosh natural frequency, slosh mass, and slosh mass center coordinates). For a practical partially-filled smooth wall propellant tank with a diameter of 1 meter, the damping ratio is as low as 0.0005 (or 0.05%). To accurately predict this very low damping value is a challenge for any CFD tool, as one must resolve a thin boundary layer near the wall and must minimize numerical damping. This work extends our previous effort to extract this challenging parameter from first principles: slosh damping for smooth wall and for ring baffle. First the experimental data correlated into the industry standard for smooth wall were used as the baseline validation. It is demonstrated that with proper grid resolution, CFD can indeed accurately predict low damping values from smooth walls for different tank sizes. The damping due to ring baffles at different depths from the free surface and for different sizes of tank was then simulated, and fairly good agreement with experimental correlation was observed. The study demonstrates that CFD technology can be applied to the design of future propellant tanks with complex configurations and with smooth walls or multiple baffles, where previous experimental data is not available.

A non-invasive experimental approach for surface temperature measurements on semi-crystalline thermoplastics

NASA Astrophysics Data System (ADS)

Boztepe, Sinan; Gilblas, Remi; de Almeida, Olivier; Le Maoult, Yannick; Schmidt, Fabrice

2017-10-01

Most of the thermoforming processes of thermoplastic polymers and their composites are performed adopting a combined heating and forming stages at which a precursor is heated prior to the forming. This step is done in order to improve formability by softening the thermoplastic polymer. Due to low thermal conductivity and semi-transparency of polymers, infrared (IR) heating is widely used for thermoforming of such materials. Predictive radiation heat transfer models for temperature distributions are therefore critical for optimizations of thermoforming process. One of the key challenges is to build a predictive model including the physical background of radiation heat transfer phenomenon in semi-crystalline thermoplastics as their microcrystalline structure introduces an optically heterogeneous medium. In addition, the accuracy of a predictive model is required to be validated experimentally where IR thermography is one of the suitable methods for such a validation as it provides a non-invasive, full-field surface temperature measurement. Although IR cameras provide a non-invasive measurement, a key issue for obtaining a reliable measurement depends on the optical characteristics of a heated material and the operating spectral band of IR camera. It is desired that the surface of a material to be measured has a spectral band where the material behaves opaque and an employed IR camera operates in the corresponding band. In this study, the optical characteristics of the PO-based polymer are discussed and, an experimental approach is proposed in order to measure the surface temperature of the PO-based polymer via IR thermography. The preliminary analyses showed that IR thermographic measurements may not be simply performed on PO-based polymers and require a correction method as their semi-transparent medium introduce a challenge to obtain reliable surface temperature measurements.

Large-scale online semantic indexing of biomedical articles via an ensemble of multi-label classification models.

PubMed

Papanikolaou, Yannis; Tsoumakas, Grigorios; Laliotis, Manos; Markantonatos, Nikos; Vlahavas, Ioannis

2017-09-22

In this paper we present the approach that we employed to deal with large scale multi-label semantic indexing of biomedical papers. This work was mainly implemented within the context of the BioASQ challenge (2013-2017), a challenge concerned with biomedical semantic indexing and question answering. Our main contribution is a MUlti-Label Ensemble method (MULE) that incorporates a McNemar statistical significance test in order to validate the combination of the constituent machine learning algorithms. Some secondary contributions include a study on the temporal aspects of the BioASQ corpus (observations apply also to the BioASQ's super-set, the PubMed articles collection) and the proper parametrization of the algorithms used to deal with this challenging classification task. The ensemble method that we developed is compared to other approaches in experimental scenarios with subsets of the BioASQ corpus giving positive results. In our participation in the BioASQ challenge we obtained the first place in 2013 and the second place in the four following years, steadily outperforming MTI, the indexing system of the National Library of Medicine (NLM). The results of our experimental comparisons, suggest that employing a statistical significance test to validate the ensemble method's choices, is the optimal approach for ensembling multi-label classifiers, especially in contexts with many rare labels.

D-Optimal Experimental Design for Contaminant Source Identification

NASA Astrophysics Data System (ADS)

Sai Baba, A. K.; Alexanderian, A.

2016-12-01

Contaminant source identification seeks to estimate the release history of a conservative solute given point concentration measurements at some time after the release. This can be mathematically expressed as an inverse problem, with a linear observation operator or a parameter-to-observation map, which we tackle using a Bayesian approach. Acquisition of experimental data can be laborious and expensive. The goal is to control the experimental parameters - in our case, the sparsity of the sensors, to maximize the information gain subject to some physical or budget constraints. This is known as optimal experimental design (OED). D-optimal experimental design seeks to maximize the expected information gain, and has long been considered the gold standard in the statistics community. Our goal is to develop scalable methods for D-optimal experimental designs involving large-scale PDE constrained problems with high-dimensional parameter fields. A major challenge for the OED, is that a nonlinear optimization algorithm for the D-optimality criterion requires repeated evaluation of objective function and gradient involving the determinant of large and dense matrices - this cost can be prohibitively expensive for applications of interest. We propose novel randomized matrix techniques that bring down the computational costs of the objective function and gradient evaluations by several orders of magnitude compared to the naive approach. The effect of randomized estimators on the accuracy and the convergence of the optimization solver will be discussed. The features and benefits of our new approach will be demonstrated on a challenging model problem from contaminant source identification involving the inference of the initial condition from spatio-temporal observations in a time-dependent advection-diffusion problem.

Prospectus: towards the development of high-fidelity models of wall turbulence at large Reynolds number

NASA Astrophysics Data System (ADS)

Klewicki, J. C.; Chini, G. P.; Gibson, J. F.

2017-03-01

Recent and on-going advances in mathematical methods and analysis techniques, coupled with the experimental and computational capacity to capture detailed flow structure at increasingly large Reynolds numbers, afford an unprecedented opportunity to develop realistic models of high Reynolds number turbulent wall-flow dynamics. A distinctive attribute of this new generation of models is their grounding in the Navier-Stokes equations. By adhering to this challenging constraint, high-fidelity models ultimately can be developed that not only predict flow properties at high Reynolds numbers, but that possess a mathematical structure that faithfully captures the underlying flow physics. These first-principles models are needed, for example, to reliably manipulate flow behaviours at extreme Reynolds numbers. This theme issue of Philosophical Transactions of the Royal Society A provides a selection of contributions from the community of researchers who are working towards the development of such models. Broadly speaking, the research topics represented herein report on dynamical structure, mechanisms and transport; scale interactions and self-similarity; model reductions that restrict nonlinear interactions; and modern asymptotic theories. In this prospectus, the challenges associated with modelling turbulent wall-flows at large Reynolds numbers are briefly outlined, and the connections between the contributing papers are highlighted.

Challenges associated with the prediction of tropical storms in the Bay of Bengal when using the WRF model

NASA Astrophysics Data System (ADS)

Machineni, N.; Veldore, V.; Mesquita, M. D. S.

2016-12-01

Accuracy in predicting tropical cyclones over low lying coastal regions is pivotal for understanding storm tracks and their subsequent impacts. The present study highlights the challenges in predicting the Bay of Bengal (BOB) cyclone "AILA" (during 23rd to 25th May 2009) using the Weather Research and Forecast model, Advanced research core module (WRF-ARW). The model configuration uses a two-way interactive nested domain with 10 km resolution over BOB. Its initial and boundary conditions are driven from the NCEP FNL operational global analysis data at every 6 hours. A total of 74 sensitivity experiments were conducted to test the following factors and levels: a) parametrization schemes: two microphysics and two cumulus physics schemes used to select appropriate combination over study region, b) model domain:including/excluding Himalayas, c) vertical resolution: eight various increasing/decreasing vertical levels have been carried out to evaluate the storm track dependencies on these factors, d) domain size: and increasing (decreasing) the grid points of model domain in east-west direction shows that approximately 50-100 km track difference for every two points. Our results show that, the experiments including the Himalayas provide a better representation of cyclone track and speed. In order to reduce the computational time required to do such tremendous amount of experiment, we hypothesize to use statistical tools of experimental design which can involve all the factors that determine the cyclone tracks. A proper experimental design might provide unbiased results and also we might need less number of experiments.

Challenges associated with the prediction of tropical storms in the Bay of Bengal when using the WRF model

NASA Astrophysics Data System (ADS)

Machineni, Nehru; Veldore, Vidyunmala; Mesquita, Michel d. S.

2017-04-01

Accuracy in predicting tropical cyclones over low lying coastal regions is pivotal for understanding storm tracks and their subsequent impacts. The present study highlights the challenges in predicting the Bay of Bengal (BOB) cyclone "AILA" (during 23rd to 25th May 2009) using the Weather Research and Forecast model, Advanced research core module (WRF-ARW). The model configuration uses a two-way interactive nested domain with 10 km resolution over BOB. Its initial and boundary conditions are driven from the NCEP FNL operational global analysis data at every 6 hours. A total of 74 sensitivity experiments were conducted to test the following factors and levels: a) parametrization schemes: two microphysics and two cumulus physics schemes used to select appropriate combination over study region, b) model domain:including/excluding Himalayas, c) vertical resolution: eight various increasing/decreasing vertical levels have been carried out to evaluate the storm track dependencies on these factors, d) domain size: and increasing (decreasing) the grid points of model domain in east-west direction shows that approximately 50-100 km track difference for every two points. Our results show that, the experiments including the Himalayas provide a better representation of cyclone track and speed. In order to reduce the computational time required to do such tremendous amount of experiment, we hypothesize to use statistical tools of experimental design which can involve all the factors that determine the cyclone tracks. A proper experimental design might provide unbiased results and also we might need less number of experiments.

Using Propensity Score Methods to Approximate Factorial Experimental Designs to Analyze the Relationship between Two Variables and an Outcome

ERIC Educational Resources Information Center

Dong, Nianbo

2015-01-01

Researchers have become increasingly interested in programs' main and interaction effects of two variables (A and B, e.g., two treatment variables or one treatment variable and one moderator) on outcomes. A challenge for estimating main and interaction effects is to eliminate selection bias across A-by-B groups. I introduce Rubin's causal model to…

Rocket-Engine Injector Development: A Case Study of a Single Injector (Briefing Charts)

DTIC Science & Technology

2014-01-01

model and experiment, not at matching conditions Axisymmetric CFD (VOF in Fluent) results every 1.5 ms Experimental results every 0.5 ms,  MFR  ~10*above...through AFRL funding in an attempt to overcome the challenges of optically dense sprays • Time-gated ballistic imaging provides a shadowgraph of large

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

Kufareva, Irina; Gustavsson, Martin; Zheng, Yi

Chemokines and their cell surface G protein–coupled receptors are critical for cell migration, not only in many fundamental biological processes but also in inflammatory diseases and cancer. Recent X-ray structures of two chemokines complexed with full-length receptors provided unprecedented insight into the atomic details of chemokine recognition and receptor activation, and computational modeling informed by new experiments leverages these insights to gain understanding of many more receptor:chemokine pairs. In parallel, chemokine receptor structures with small molecules reveal the complicated and diverse structural foundations of small molecule antagonism and allostery, highlight the inherent physicochemical challenges of receptor:chemokine interfaces, and suggest novelmore » epitopes that can be exploited to overcome these challenges. The structures and models promote unique understanding of chemokine receptor biology, including the interpretation of two decades of experimental studies, and will undoubtedly assist future drug discovery endeavors.« less

Simulation Modeling for Off-Nominal Conditions - Where Are We Today?

NASA Technical Reports Server (NTRS)

Shah, Gautam H.; Foster, John V.; Cunningham, Kevin

2010-01-01

The modeling of aircraft flight characteris4cs in off-nominal or otherwise adverse conditions has become increasingly important for simulation in the loss-of-control arena. Adverse conditions include environmentally-induced upsets such as wind shear or wake vortex encounters; off-nominal flight conditions, such as stall or departure; on-board systems failures; and structural failures or aircraft damage. Spirited discussions in the research community are taking place as to the fidelity and data requirements for adequate representation of vehicle dynamics under such conditions for a host of research areas, including recovery training, flight controls development, trajectory guidance/planning, and envelope limiting. The increasing need for multiple sources of data (empirical, computational, experimental) for modeling across a larger flight envelope leads to challenges in developing methods of appropriately applying or combining such data, particularly in a dynamic flight environment with a physically and/or aerodynamically asymmetric vehicle. Traditional simplifications and symmetry assumptions in current modeling methodology may no longer be valid. Furthermore, once modeled, challenges abound in the validation of flight dynamics characteristics in adverse flight regimes

Comparison of Abortion and Infection after Experimental Challenge of Pregnant Bison and Cattle with Brucella abortus Strain 2308▿

PubMed Central

Olsen, S. C.; Johnson, C.

2011-01-01

A comparative study was conducted using data from naive bison (n = 45) and cattle (n = 46) from 8 and 6 studies, respectively, in which a standardized Brucella abortus strain 2308 experimental challenge was administered during midgestation. The incidence of abortion, fetal infection, uterine or mammary infection, or infection in maternal tissues after experimental challenge was greater (P < 0.05) in bison than in cattle. In animals that did abort, the time between experimental challenge and abortion was shorter (P < 0.05) for bison than for cattle. Brucella colonization of four target tissues and serologic responses on the standard tube agglutination test at the time of abortion did not differ (P > 0.05) between cattle and bison. The results of our study suggest that naive bison and cattle have similarities and differences after experimental exposure to a virulent B. abortus strain. Although our data suggest that bison may be more susceptible to infection with Brucella, some pathogenic characteristics of brucellosis were similar between bison and cattle. PMID:21976222

Updating the Finite Element Model of the Aerostructures Test Wing Using Ground Vibration Test Data

NASA Technical Reports Server (NTRS)

Lung, Shun-Fat; Pak, Chan-Gi

2009-01-01

Improved and/or accelerated decision making is a crucial step during flutter certification processes. Unfortunately, most finite element structural dynamics models have uncertainties associated with model validity. Tuning the finite element model using measured data to minimize the model uncertainties is a challenging task in the area of structural dynamics. The model tuning process requires not only satisfactory correlations between analytical and experimental results, but also the retention of the mass and stiffness properties of the structures. Minimizing the difference between analytical and experimental results is a type of optimization problem. By utilizing the multidisciplinary design, analysis, and optimization (MDAO) tool in order to optimize the objective function and constraints; the mass properties, the natural frequencies, and the mode shapes can be matched to the target data to retain the mass matrix orthogonality. This approach has been applied to minimize the model uncertainties for the structural dynamics model of the aerostructures test wing (ATW), which was designed and tested at the National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California). This study has shown that natural frequencies and corresponding mode shapes from the updated finite element model have excellent agreement with corresponding measured data.

Updating the Finite Element Model of the Aerostructures Test Wing using Ground Vibration Test Data

NASA Technical Reports Server (NTRS)

Lung, Shun-fat; Pak, Chan-gi

2009-01-01

Improved and/or accelerated decision making is a crucial step during flutter certification processes. Unfortunately, most finite element structural dynamics models have uncertainties associated with model validity. Tuning the finite element model using measured data to minimize the model uncertainties is a challenging task in the area of structural dynamics. The model tuning process requires not only satisfactory correlations between analytical and experimental results, but also the retention of the mass and stiffness properties of the structures. Minimizing the difference between analytical and experimental results is a type of optimization problem. By utilizing the multidisciplinary design, analysis, and optimization (MDAO) tool in order to optimize the objective function and constraints; the mass properties, the natural frequencies, and the mode shapes can be matched to the target data to retain the mass matrix orthogonality. This approach has been applied to minimize the model uncertainties for the structural dynamics model of the Aerostructures Test Wing (ATW), which was designed and tested at the National Aeronautics and Space Administration (NASA) Dryden Flight Research Center (DFRC) (Edwards, California). This study has shown that natural frequencies and corresponding mode shapes from the updated finite element model have excellent agreement with corresponding measured data.

Modeling of hydrogen evolution reaction on the surface of GaInP2

NASA Astrophysics Data System (ADS)

Choi, Woon Ih; Wood, Brandon; Schwegler, Eric; Ogitsu, Tadashi

2012-02-01

GaInP2 is promising candidate material for hydrogen production using sunlight. It reduces solvated proton into hydrogen molecule using light-induced excited electrons in the photoelectrochemical cell. However, it is challenging to model hydrogen evolution reaction (HER) using first-principles molecular dynamics. Instead, we use Anderson-Newns model and generalized solvent coordinate in Marcus-Hush theory to describe adiabatic free energy surface of HER. Model parameters are fitted from the DFT calculations. We model Volmer-Heyrovsky reaction path on the surfaces of CuPt phase of GaInP2. We also discuss effects of surface oxide and catalyst atoms that exist on top of bare surfaces in experimental circumstances.

Modeling sediment transport after ditch network maintenance of a forested peatland

NASA Astrophysics Data System (ADS)

Haahti, K.; Marttila, H.; Warsta, L.; Kokkonen, T.; Finér, L.; Koivusalo, H.

2016-11-01

Elevated suspended sediment (SS) loads released from peatlands after drainage operations and the resulting negative effect on the ecological status of the receiving water bodies have been widely recognized. Understanding the processes controlling erosion and sediment transport within the ditch network forms a prerequisite for adequate sediment control. While numerous experimental studies have been reported in this field, model based assessments are rare. This study presents a modeling approach to investigate sediment transport in a peatland ditch network. The transport model describes bed erosion, rain-induced bank erosion, floc deposition, and consolidation of the bed. Coupled to a distributed hydrological model, sediment transport was simulated in a 5.2 ha forestry-drained peatland catchment for 2 years after ditch cleaning. Comparing simulation results to measured SS concentrations suggested that the loose peat material, produced during excavation, contributed markedly to elevated SS concentrations immediately after ditch cleaning. Both snowmelt and summer rainstorms contributed critically to annual loads. Springtime peat erosion during snowmelt was driven by ditch flow whereas during summer rainfalls, bank erosion by raindrop impact was identified as an important process. Relating modeling results to observed spatial topographic changes in the ditch network was challenging and the results were difficult to verify. Nevertheless, the model has potential to identify risk areas for erosion. The results demonstrate that modeling is effective in separating the importance of different processes and complements pure experimental approaches. Modeling results can aid planning and designing efficient sediment control measures and guide the focus of experimental studies.

Rodent Models of Experimental Endometriosis: Identifying Mechanisms of Disease and Therapeutic Targets

PubMed Central

Bruner-Tran, Kaylon L.; Mokshagundam, Shilpa; Herington, Jennifer L.; Ding, Tianbing; Osteen, Kevin G.

2018-01-01

Background: Although it has been more than a century since endometriosis was initially described in the literature, understanding the etiology and natural history of the disease has been challenging. However, the broad utility of murine and rat models of experimental endometriosis has enabled the elucidation of a number of potentially targetable processes which may otherwise promote this disease. Objective: To review a variety of studies utilizing rodent models of endometriosis to illustrate their utility in examining mechanisms associated with development and progression of this disease. Results: Use of rodent models of endometriosis has provided a much broader understanding of the risk factors for the initial development of endometriosis, the cellular pathology of the disease and the identification of potential therapeutic targets. Conclusion: Although there are limitations with any animal model, the variety of experimental endometriosis models that have been developed has enabled investigation into numerous aspects of this disease. Thanks to these models, our under-standing of the early processes of disease development, the role of steroid responsiveness, inflammatory processes and the peritoneal environment has been advanced. More recent models have begun to shed light on how epigenetic alterations con-tribute to the molecular basis of this disease as well as the multiple comorbidities which plague many patients. Continued de-velopments of animal models which aid in unraveling the mechanisms of endometriosis development provide the best oppor-tunity to identify therapeutic strategies to prevent or regress this enigmatic disease.

Boxes of Model Building and Visualization.

PubMed

Turk, Dušan

2017-01-01

Macromolecular crystallography and electron microscopy (single-particle and in situ tomography) are merging into a single approach used by the two coalescing scientific communities. The merger is a consequence of technical developments that enabled determination of atomic structures of macromolecules by electron microscopy. Technological progress in experimental methods of macromolecular structure determination, computer hardware, and software changed and continues to change the nature of model building and visualization of molecular structures. However, the increase in automation and availability of structure validation are reducing interactive manual model building to fiddling with details. On the other hand, interactive modeling tools increasingly rely on search and complex energy calculation procedures, which make manually driven changes in geometry increasingly powerful and at the same time less demanding. Thus, the need for accurate manual positioning of a model is decreasing. The user's push only needs to be sufficient to bring the model within the increasing convergence radius of the computing tools. It seems that we can now better than ever determine an average single structure. The tools work better, requirements for engagement of human brain are lowered, and the frontier of intellectual and scientific challenges has moved on. The quest for resolution of new challenges requires out-of-the-box thinking. A few issues such as model bias and correctness of structure, ongoing developments in parameters defining geometric restraints, limitations of the ideal average single structure, and limitations of Bragg spot data are discussed here, together with the challenges that lie ahead.

Ab Initio Structural Modeling of and Experimental Validation for Chlamydia trachomatis Protein CT296 Reveal Structural Similarity to Fe(II) 2-Oxoglutarate-Dependent Enzymes▿

PubMed Central

Kemege, Kyle E.; Hickey, John M.; Lovell, Scott; Battaile, Kevin P.; Zhang, Yang; Hefty, P. Scott

2011-01-01

Chlamydia trachomatis is a medically important pathogen that encodes a relatively high percentage of proteins with unknown function. The three-dimensional structure of a protein can be very informative regarding the protein's functional characteristics; however, determining protein structures experimentally can be very challenging. Computational methods that model protein structures with sufficient accuracy to facilitate functional studies have had notable successes. To evaluate the accuracy and potential impact of computational protein structure modeling of hypothetical proteins encoded by Chlamydia, a successful computational method termed I-TASSER was utilized to model the three-dimensional structure of a hypothetical protein encoded by open reading frame (ORF) CT296. CT296 has been reported to exhibit functional properties of a divalent cation transcription repressor (DcrA), with similarity to the Escherichia coli iron-responsive transcriptional repressor, Fur. Unexpectedly, the I-TASSER model of CT296 exhibited no structural similarity to any DNA-interacting proteins or motifs. To validate the I-TASSER-generated model, the structure of CT296 was solved experimentally using X-ray crystallography. Impressively, the ab initio I-TASSER-generated model closely matched (2.72-Å Cα root mean square deviation [RMSD]) the high-resolution (1.8-Å) crystal structure of CT296. Modeled and experimentally determined structures of CT296 share structural characteristics of non-heme Fe(II) 2-oxoglutarate-dependent enzymes, although key enzymatic residues are not conserved, suggesting a unique biochemical process is likely associated with CT296 function. Additionally, functional analyses did not support prior reports that CT296 has properties shared with divalent cation repressors such as Fur. PMID:21965559

Ab initio structural modeling of and experimental validation for Chlamydia trachomatis protein CT296 reveal structural similarity to Fe(II) 2-oxoglutarate-dependent enzymes

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

Kemege, Kyle E.; Hickey, John M.; Lovell, Scott

2012-02-13

Chlamydia trachomatis is a medically important pathogen that encodes a relatively high percentage of proteins with unknown function. The three-dimensional structure of a protein can be very informative regarding the protein's functional characteristics; however, determining protein structures experimentally can be very challenging. Computational methods that model protein structures with sufficient accuracy to facilitate functional studies have had notable successes. To evaluate the accuracy and potential impact of computational protein structure modeling of hypothetical proteins encoded by Chlamydia, a successful computational method termed I-TASSER was utilized to model the three-dimensional structure of a hypothetical protein encoded by open reading frame (ORF)more » CT296. CT296 has been reported to exhibit functional properties of a divalent cation transcription repressor (DcrA), with similarity to the Escherichia coli iron-responsive transcriptional repressor, Fur. Unexpectedly, the I-TASSER model of CT296 exhibited no structural similarity to any DNA-interacting proteins or motifs. To validate the I-TASSER-generated model, the structure of CT296 was solved experimentally using X-ray crystallography. Impressively, the ab initio I-TASSER-generated model closely matched (2.72-{angstrom} C{alpha} root mean square deviation [RMSD]) the high-resolution (1.8-{angstrom}) crystal structure of CT296. Modeled and experimentally determined structures of CT296 share structural characteristics of non-heme Fe(II) 2-oxoglutarate-dependent enzymes, although key enzymatic residues are not conserved, suggesting a unique biochemical process is likely associated with CT296 function. Additionally, functional analyses did not support prior reports that CT296 has properties shared with divalent cation repressors such as Fur.« less

Experimental Actinobacillus pleuropneumoniae challenge in swine: Comparison of computed tomographic and radiographic findings during disease

PubMed Central

2012-01-01

Background In pigs, diseases of the respiratory tract like pleuropneumonia due to Actinobacillus pleuropneumoniae (App) infection have led to high economic losses for decades. Further research on disease pathogenesis, pathogen-host-interactions and new prophylactic and therapeutic approaches are needed. In most studies, a large number of experimental animals are required to assess lung alterations at different stages of the disease. In order to reduce the required number of animals but nevertheless gather information on the nature and extent of lung alterations in living pigs, a computed tomographic scoring system for quantifying gross pathological findings was developed. In this study, five healthy pigs served as control animals while 24 pigs were infected with App, the causative agent of pleuropneumonia in pigs, in an established model for respiratory tract disease. Results Computed tomographic (CT) findings during the course of App challenge were verified by radiological imaging, clinical, serological, gross pathology and histological examinations. Findings from clinical examinations and both CT and radiological imaging, were recorded on day 7 and day 21 after challenge. Clinical signs after experimental App challenge were indicative of acute to chronic disease. Lung CT findings of infected pigs comprised ground-glass opacities and consolidation. On day 7 and 21 the clinical scores significantly correlated with the scores of both imaging techniques. At day 21, significant correlations were found between clinical scores, CT scores and lung lesion scores. In 19 out of 22 challenged pigs the determined disease grades (not affected, slightly affected, moderately affected, severely affected) from CT and gross pathological examination were in accordance. Disease classification by radiography and gross pathology agreed in 11 out of 24 pigs. Conclusions High-resolution, high-contrast CT examination with no overlapping of organs is superior to radiography in the assessment of pneumonic lung lesions after App challenge. The new CT scoring system allows for quantification of gross pathological lung alterations in living pigs. However, computed tomographic findings are not informative of the etiology of respiratory disease. PMID:22546414

The SAMPL4 host-guest blind prediction challenge: an overview.

PubMed

Muddana, Hari S; Fenley, Andrew T; Mobley, David L; Gilson, Michael K

2014-04-01

Prospective validation of methods for computing binding affinities can help assess their predictive power and thus set reasonable expectations for their performance in drug design applications. Supramolecular host-guest systems are excellent model systems for testing such affinity prediction methods, because their small size and limited conformational flexibility, relative to proteins, allows higher throughput and better numerical convergence. The SAMPL4 prediction challenge therefore included a series of host-guest systems, based on two hosts, cucurbit[7]uril and octa-acid. Binding affinities in aqueous solution were measured experimentally for a total of 23 guest molecules. Participants submitted 35 sets of computational predictions for these host-guest systems, based on methods ranging from simple docking, to extensive free energy simulations, to quantum mechanical calculations. Over half of the predictions provided better correlations with experiment than two simple null models, but most methods underperformed the null models in terms of root mean squared error and linear regression slope. Interestingly, the overall performance across all SAMPL4 submissions was similar to that for the prior SAMPL3 host-guest challenge, although the experimentalists took steps to simplify the current challenge. While some methods performed fairly consistently across both hosts, no single approach emerged as consistent top performer, and the nonsystematic nature of the various submissions made it impossible to draw definitive conclusions regarding the best choices of energy models or sampling algorithms. Salt effects emerged as an issue in the calculation of absolute binding affinities of cucurbit[7]uril-guest systems, but were not expected to affect the relative affinities significantly. Useful directions for future rounds of the challenge might involve encouraging participants to carry out some calculations that replicate each others' studies, and to systematically explore parameter options.

Extension of local front reconstruction method with controlled coalescence model

NASA Astrophysics Data System (ADS)

Rajkotwala, A. H.; Mirsandi, H.; Peters, E. A. J. F.; Baltussen, M. W.; van der Geld, C. W. M.; Kuerten, J. G. M.; Kuipers, J. A. M.

2018-02-01

The physics of droplet collisions involves a wide range of length scales. This poses a challenge to accurately simulate such flows with standard fixed grid methods due to their inability to resolve all relevant scales with an affordable number of computational grid cells. A solution is to couple a fixed grid method with subgrid models that account for microscale effects. In this paper, we improved and extended the Local Front Reconstruction Method (LFRM) with a film drainage model of Zang and Law [Phys. Fluids 23, 042102 (2011)]. The new framework is first validated by (near) head-on collision of two equal tetradecane droplets using experimental film drainage times. When the experimental film drainage times are used, the LFRM method is better in predicting the droplet collisions, especially at high velocity in comparison with other fixed grid methods (i.e., the front tracking method and the coupled level set and volume of fluid method). When the film drainage model is invoked, the method shows a good qualitative match with experiments, but a quantitative correspondence of the predicted film drainage time with the experimental drainage time is not obtained indicating that further development of film drainage model is required. However, it can be safely concluded that the LFRM coupled with film drainage models is much better in predicting the collision dynamics than the traditional methods.

The neurotoxicant, cuprizone, as a model to study demyelination and remyelination in the central nervous system.

PubMed

Matsushima, G K; Morell, P

2001-01-01

Myelin of the adult CNS is vulnerable to a variety of metabolic, toxic, and autoimmune insults. That remyelination can ensue, following demyelinating insult, has been well demonstrated. Details of the process of remyelination are, however difficult to ascertain since in most experimental models of demyelination/remyelination the severity, localization of lesion site, or time course of the pathophysiology is variable from animal to animal. In contrast, an experimental model in which massive demyelination can be reproducibly induced in large areas of mouse brain is exposure to the copper chelator, cuprizone, in the diet. We review work from several laboratories over the past 3 decades, with emphasis on our own recent studies, which suggest an overall picture of cellular events involved in demyelination/remyelination. When 8 week old C57BL/6 mice are fed 0.2% cuprizone in the diet, mature olidgodendroglia are specifically insulted (cannot fulfill the metabolic demand of support of vast amounts of myelin) and go through apoptosis. This is closely followed by recruitment of microglia and phagoctytosis of myelin. Studies of myelin gene expression, coordinated with morphological studies, indicate that even in the face of continued metabolic challenge, oligodendroglial progenitor cells proliferate and invade demyelinated areas. If the cuprizone challenge is terminated, an almost complete remyelination takes place in a matter of weeks. Communication between different cell types by soluble factors may be inferred. This material is presented in the context of a model compatible with present data -- and which can be tested more rigorously with the cuprizone model. The reproducibility of the model indicates that it may allow for testing of manipulations (e.g. available knockouts or transgenics on the common genetic background, or pharmacological treatments) which may accelerate or repress the process of demyelination and or remyelination.

A conservation law for virus infection kinetics in vitro.

PubMed

Kakizoe, Yusuke; Morita, Satoru; Nakaoka, Shinji; Takeuchi, Yasuhiro; Sato, Kei; Miura, Tomoyuki; Beauchemin, Catherine A A; Iwami, Shingo

2015-07-07

Conservation laws are among the most important properties of a physical system, but are not commonplace in biology. We derived a conservation law from the basic model for viral infections which consists in a small set of ordinary differential equations. We challenged the conservation law experimentally for the case of a virus infection in a cell culture. We found that the derived, conserved quantity remained almost constant throughout the infection period, implying that the derived conservation law holds in this biological system. We also suggest a potential use for the conservation law in evaluating the accuracy of experimental measurements. Copyright © 2015 Elsevier Ltd. All rights reserved.

Polarization of the Cosmic Microwave Background: Are These Guys Serious?

NASA Technical Reports Server (NTRS)

Kogut, Alan

2007-01-01

The polarization of the cosmic microwave background (CMB) could contain the oldest information in the universe, dating from an inflationary epoch just after the Big Bang. Detecting this signal presents an experimental challenge, as it is both faint and hidden behind complicated foregrounds. The rewards, however, are great, as a positive detection would not only establish inflation as a physical reality but also provide a model-independent measurement of the relevant energy scale. I will present the scientific motivation behind measurements of the CMB polarization and discuss how recent experimental progress could lead to a detection in the not-very-distant future.

Experimental Applications of Automatic Test Markup Language (ATML)

NASA Technical Reports Server (NTRS)

Lansdowne, Chatwin A.; McCartney, Patrick; Gorringe, Chris

2012-01-01

The authors describe challenging use-cases for Automatic Test Markup Language (ATML), and evaluate solutions. The first case uses ATML Test Results to deliver active features to support test procedure development and test flow, and bridging mixed software development environments. The second case examines adding attributes to Systems Modelling Language (SysML) to create a linkage for deriving information from a model to fill in an ATML document set. Both cases are outside the original concept of operations for ATML but are typical when integrating large heterogeneous systems with modular contributions from multiple disciplines.

Quantum Monte Carlo study of the phase diagram of solid molecular hydrogen at extreme pressures

PubMed Central

Drummond, N. D.; Monserrat, Bartomeu; Lloyd-Williams, Jonathan H.; Ríos, P. López; Pickard, Chris J.; Needs, R. J.

2015-01-01

Establishing the phase diagram of hydrogen is a major challenge for experimental and theoretical physics. Experiment alone cannot establish the atomic structure of solid hydrogen at high pressure, because hydrogen scatters X-rays only weakly. Instead, our understanding of the atomic structure is largely based on density functional theory (DFT). By comparing Raman spectra for low-energy structures found in DFT searches with experimental spectra, candidate atomic structures have been identified for each experimentally observed phase. Unfortunately, DFT predicts a metallic structure to be energetically favoured at a broad range of pressures up to 400 GPa, where it is known experimentally that hydrogen is non-metallic. Here we show that more advanced theoretical methods (diffusion quantum Monte Carlo calculations) find the metallic structure to be uncompetitive, and predict a phase diagram in reasonable agreement with experiment. This greatly strengthens the claim that the candidate atomic structures accurately model the experimentally observed phases. PMID:26215251

Demystifying the cytokine network: Mathematical models point the way.

PubMed

Morel, Penelope A; Lee, Robin E C; Faeder, James R

2017-10-01

Cytokines provide the means by which immune cells communicate with each other and with parenchymal cells. There are over one hundred cytokines and many exist in families that share receptor components and signal transduction pathways, creating complex networks. Reductionist approaches to understanding the role of specific cytokines, through the use of gene-targeted mice, have revealed further complexity in the form of redundancy and pleiotropy in cytokine function. Creating an understanding of the complex interactions between cytokines and their target cells is challenging experimentally. Mathematical and computational modeling provides a robust set of tools by which complex interactions between cytokines can be studied and analyzed, in the process creating novel insights that can be further tested experimentally. This review will discuss and provide examples of the different modeling approaches that have been used to increase our understanding of cytokine networks. This includes discussion of knowledge-based and data-driven modeling approaches and the recent advance in single-cell analysis. The use of modeling to optimize cytokine-based therapies will also be discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Reconstruction of Tissue-Specific Metabolic Networks Using CORDA

PubMed Central

Schultz, André; Qutub, Amina A.

2016-01-01

Human metabolism involves thousands of reactions and metabolites. To interpret this complexity, computational modeling becomes an essential experimental tool. One of the most popular techniques to study human metabolism as a whole is genome scale modeling. A key challenge to applying genome scale modeling is identifying critical metabolic reactions across diverse human tissues. Here we introduce a novel algorithm called Cost Optimization Reaction Dependency Assessment (CORDA) to build genome scale models in a tissue-specific manner. CORDA performs more efficiently computationally, shows better agreement to experimental data, and displays better model functionality and capacity when compared to previous algorithms. CORDA also returns reaction associations that can greatly assist in any manual curation to be performed following the automated reconstruction process. Using CORDA, we developed a library of 76 healthy and 20 cancer tissue-specific reconstructions. These reconstructions identified which metabolic pathways are shared across diverse human tissues. Moreover, we identified changes in reactions and pathways that are differentially included and present different capacity profiles in cancer compared to healthy tissues, including up-regulation of folate metabolism, the down-regulation of thiamine metabolism, and tight regulation of oxidative phosphorylation. PMID:26942765

Effects of low-level chronic irradiation on the radiosensitivity of mammals: Modeling studies

NASA Astrophysics Data System (ADS)

Smirnova, O. A.

Mathematical models of the major hematopoietic lines are used to study the modifying effects of low-level chronic preirradiation on radiosensitivity of mammals which resulted in their reduced radiosensitivity (acquired radioresistance) and elevated radiosensitivity (hypersensitivity) to the subsequent radiation exposure. These effects of preirradiation manifest themselves, respectively, in decreased and increased mortality of preirradiated experimental animals (mice) after challenge acute exposure in comparison with that for previously nonirradiated ones. Analysis of the modeling results reveals the biological mechanisms of these radioprotection and radiosensitization effects, and enables one to estimate the ranges of dose rate and duration of chronic preirradiation where these effects are realized. Juxtapositions of the modeling predictions with the relevant experimental data show their qualitative agreement. All this testifies to the importance of accounting the nonlinear effect of low-level chronic irradiation on radiosensitivity of the hematopoiesis system and organism as a whole, when the radiation risk for astronauts on long-term space missions is estimated. The developed models of hematopoiesis can be used, after appropriate identification, as a component of the mathematical tools for radiation risk assessment.

Micro-porous layer stochastic reconstruction and transport parameter determination

NASA Astrophysics Data System (ADS)

El Hannach, Mohamed; Singh, Randhir; Djilali, Ned; Kjeang, Erik

2015-05-01

The Micro-Porous Layer (MPL) is a porous, thin layer commonly used in fuel cells at the interfaces between the catalyst layers and gas diffusion media. It is generally made from spherical carbon nanoparticles and PTFE acting as hydrophobic agent. The scale and brittle nature of the MPL structure makes it challenging to study experimentally. In the present work, a 3D stochastic model is developed to virtually reconstruct the MPL structure. The carbon nanoparticle and PTFE phases are fully distinguished by the algorithm. The model is shown to capture the actual structural morphology of the MPL and is validated by comparing the results to available experimental data. The model shows a good capability in generating a realistic MPL successfully using a set of parameters introduced to capture specific morphological features of the MPL. A numerical model that resolves diffusive transport at the pore scale is used to compute the effective transport properties of the reconstructed MPLs. A parametric study is conducted to illustrate the capability of the model as an MPL design tool that can be used to guide and optimize the functionality of the material.

Verification of Electromagnetic Physics Models for Parallel Computing Architectures in the GeantV Project

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

Amadio, G.; et al.

An intensive R&D and programming effort is required to accomplish new challenges posed by future experimental high-energy particle physics (HEP) programs. The GeantV project aims to narrow the gap between the performance of the existing HEP detector simulation software and the ideal performance achievable, exploiting latest advances in computing technology. The project has developed a particle detector simulation prototype capable of transporting in parallel particles in complex geometries exploiting instruction level microparallelism (SIMD and SIMT), task-level parallelism (multithreading) and high-level parallelism (MPI), leveraging both the multi-core and the many-core opportunities. We present preliminary verification results concerning the electromagnetic (EM) physicsmore » models developed for parallel computing architectures within the GeantV project. In order to exploit the potential of vectorization and accelerators and to make the physics model effectively parallelizable, advanced sampling techniques have been implemented and tested. In this paper we introduce a set of automated statistical tests in order to verify the vectorized models by checking their consistency with the corresponding Geant4 models and to validate them against experimental data.« less

Data Mining of Macromolecular Structures.

PubMed

van Beusekom, Bart; Perrakis, Anastassis; Joosten, Robbie P

2016-01-01

The use of macromolecular structures is widespread for a variety of applications, from teaching protein structure principles all the way to ligand optimization in drug development. Applying data mining techniques on these experimentally determined structures requires a highly uniform, standardized structural data source. The Protein Data Bank (PDB) has evolved over the years toward becoming the standard resource for macromolecular structures. However, the process selecting the data most suitable for specific applications is still very much based on personal preferences and understanding of the experimental techniques used to obtain these models. In this chapter, we will first explain the challenges with data standardization, annotation, and uniformity in the PDB entries determined by X-ray crystallography. We then discuss the specific effect that crystallographic data quality and model optimization methods have on structural models and how validation tools can be used to make informed choices. We also discuss specific advantages of using the PDB_REDO databank as a resource for structural data. Finally, we will provide guidelines on how to select the most suitable protein structure models for detailed analysis and how to select a set of structure models suitable for data mining.

Experimental infection of Muscovy ducks with highly pathogenic avian influenza virus (H5N1) belonging to clade 2.2.

PubMed

Guionie, Olivier; Guillou-Cloarec, Cécile; Courtois, David; Bougeard, B Stéphanie; Amelot, Michel; Jestin, Véronique

2010-03-01

Highly pathogenic (HP) H5N1 avian influenza (AI) is enzootic in several countries of Asia and Africa and constitutes a major threat, at the world level, for both animal and public health. Ducks play an important role in the epidemiology of AI, including HP H5N1 AI. Although vaccination can be a useful tool to control AI, duck vaccination has not proved very efficient in the field, indicating a need to develop new vaccines and a challenge model to evaluate the protection for duck species. Although Muscovy duck is the duck species most often reared in France, the primary duck-producing country in Europe, and is also produced in Asia, it is rarely studied. Our team recently demonstrated a good cross-reactivity with hemagglutinin from clade 2.2 and inferred that this could be a good vaccine candidate for ducks. Two challenges using two French H5N1 HP strains, 1) A/mute swan/France/06299/06 (Swan/06299), clade 2.2.1, and 2) A/mute swan/France/070203/07 (Swan/070203), clade 2.2 (but different from subclade 2.2.1), were performed (each) on 20 Muscovy ducks (including five contacts) inoculated by oculo-nasal route (6 log10 median egg infectious doses per duck). Clinical signs were recorded daily, and cloacal and oropharyngeal swabs were collected throughout the assay. Autopsies were done on all dead ducks, and organs were taken for analyses. Virus was measured by quantitative reverse transcriptase-PCR based on the M gene AI virus. Ducks presented severe nervous signs in both challenges. Swan/070203 strain led to 80% morbidity (12/15 sick ducks) and 73% mortality (11/15 ducks) at 13.5 days postinfection (dpi), whereas Swan/06299 strain produced 100% mortality at 6.5 dpi. Viral RNA load was significantly lower via the cloacal route than via the oropharyngeal route in both trials, presenting a peak in the first challenge at 3.5 dpi and being more stable in the second challenge. The brain was the organ containing the highest viral RNA load in both challenges. Viral RNA load in a given organ was similar or statistically significantly higher in ducks challenged with Swan/06299 strain. Thus, the Swan/06299 strain was more virulent and could be used as a putative challenge model. Moreover, challenged ducks and contacts contained the same amounts of viral RNA load, demonstrating the rapid and efficient transmission of H5N1 HP in Muscovy ducks in our experimental conditions.

Helicobacter pylori induces an antimicrobial response in rhesus macaques in a cag pathogenicity island-dependent manner.

PubMed

Hornsby, Michael J; Huff, Jennifer L; Kays, Robert J; Canfield, Don R; Bevins, Charles L; Solnick, Jay V

2008-04-01

We used the rhesus macaque model to study the effects of the cag pathogenicity island (cag PAI) on the H pylori host-pathogen interaction. H pylori-specific pathogen-free (SPF) monkeys were experimentally challenged with wild-type (WT) H pylori strain J166 (J166WT, n = 4) or its cag PAI isogenic knockout (J166Deltacag PAI, n = 4). Animals underwent endoscopy before and 1, 4, 8, and 13 weeks after challenge. Gastric biopsies were collected for quantitative culture, histopathology, and host gene expression analysis. Quantitative cultures showed that all experimentally challenged animals were infected with J166WT or its isogenic J166Deltacag PAI. Histopathology demonstrated that inflammation and expansion of the lamina propria were attenuated in animals infected with J166Deltacag PAI compared with J166WT. Microarray analysis showed that of the 119 up-regulated genes in the J166WT-infected animals, several encode innate antimicrobial effector proteins, including elafin, siderocalin, DMBT1, DUOX2, and several novel paralogues of human-beta defensin-2. Quantitative RT-PCR confirmed that high-level induction of each of these genes depended on the presence of the cag PAI. Immunohistochemistry confirmed increased human-beta defensin-2 epithelial cell staining in animals challenged with J166WT compared with either J166Deltacag PAI-challenged or uninfected control animals. We propose that one function of the cag PAI is to induce an antimicrobial host response that may serve to increase the competitive advantage of H pylori in the gastric niche and could even provide a protective benefit to the host.

Strategies for carbohydrate model building, refinement and validation

PubMed Central

2017-01-01

Sugars are the most stereochemically intricate family of biomolecules and present substantial challenges to anyone trying to understand their nomenclature, reactions or branched structures. Current crystallographic programs provide an abstraction layer allowing inexpert structural biologists to build complete protein or nucleic acid model components automatically either from scratch or with little manual intervention. This is, however, still not generally true for sugars. The need for carbohydrate-specific building and validation tools has been highlighted a number of times in the past, concomitantly with the introduction of a new generation of experimental methods that have been ramping up the production of protein–sugar complexes and glycoproteins for the past decade. While some incipient advances have been made to address these demands, correctly modelling and refining carbohydrates remains a challenge. This article will address many of the typical difficulties that a structural biologist may face when dealing with carbohydrates, with an emphasis on problem solving in the resolution range where X-ray crystallography and cryo-electron microscopy are expected to overlap in the next decade. PMID:28177313

Isotope effect of mercury diffusion in air

PubMed Central

Koster van Groos, Paul G.; Esser, Bradley K.; Williams, Ross W.; Hunt, James R.

2014-01-01

Identifying and reducing impacts from mercury sources in the environment remains a considerable challenge and requires process based models to quantify mercury stocks and flows. The stable isotope composition of mercury in environmental samples can help address this challenge by serving as a tracer of specific sources and processes. Mercury isotope variations are small and result only from isotope fractionation during transport, equilibrium, and transformation processes. Because these processes occur in both industrial and environmental settings, knowledge of their associated isotope effects is required to interpret mercury isotope data. To improve the mechanistic modeling of mercury isotope effects during gas phase diffusion, an experimental program tested the applicability of kinetic gas theory. Gas-phase elemental mercury diffusion through small bore needles from finite sources demonstrated mass dependent diffusivities leading to isotope fractionation described by a Rayleigh distillation model. The measured relative atomic diffusivities among mercury isotopes in air are large and in agreement with kinetic gas theory. Mercury diffusion in air offers a reasonable explanation of recent field results reported in the literature. PMID:24364380

Shifting foundations: the mechanical cell wall and development.

PubMed

Braybrook, Siobhan A; Jönsson, Henrik

2016-02-01

The cell wall has long been acknowledged as an important physical mediator of growth in plants. Recent experimental and modelling work has brought the importance of cell wall mechanics into the forefront again. These data have challenged existing dogmas that relate cell wall structure to cell/organ growth, that uncouple elasticity from extensibility, and those which treat the cell wall as a passive and non-stressed material. Within this review we describe experiments and models which have changed the ways in which we view the mechanical cell wall, leading to new hypotheses and research avenues. It has become increasingly apparent that while we often wish to simplify our systems, we now require more complex multi-scale experiments and models in order to gain further insight into growth mechanics. We are currently experiencing an exciting and challenging shift in the foundations of our understanding of cell wall mechanics in growth and development. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Isotope effect of mercury diffusion in air.

PubMed

Koster van Groos, Paul G; Esser, Bradley K; Williams, Ross W; Hunt, James R

2014-01-01

Identifying and reducing impacts from mercury sources in the environment remains a considerable challenge and requires process based models to quantify mercury stocks and flows. The stable isotope composition of mercury in environmental samples can help address this challenge by serving as a tracer of specific sources and processes. Mercury isotope variations are small and result only from isotope fractionation during transport, equilibrium, and transformation processes. Because these processes occur in both industrial and environmental settings, knowledge of their associated isotope effects is required to interpret mercury isotope data. To improve the mechanistic modeling of mercury isotope effects during gas phase diffusion, an experimental program tested the applicability of kinetic gas theory. Gas-phase elemental mercury diffusion through small bore needles from finite sources demonstrated mass dependent diffusivities leading to isotope fractionation described by a Rayleigh distillation model. The measured relative atomic diffusivities among mercury isotopes in air are large and in agreement with kinetic gas theory. Mercury diffusion in air offers a reasonable explanation of recent field results reported in the literature.

Strategies for carbohydrate model building, refinement and validation.

PubMed

Agirre, Jon

2017-02-01

Sugars are the most stereochemically intricate family of biomolecules and present substantial challenges to anyone trying to understand their nomenclature, reactions or branched structures. Current crystallographic programs provide an abstraction layer allowing inexpert structural biologists to build complete protein or nucleic acid model components automatically either from scratch or with little manual intervention. This is, however, still not generally true for sugars. The need for carbohydrate-specific building and validation tools has been highlighted a number of times in the past, concomitantly with the introduction of a new generation of experimental methods that have been ramping up the production of protein-sugar complexes and glycoproteins for the past decade. While some incipient advances have been made to address these demands, correctly modelling and refining carbohydrates remains a challenge. This article will address many of the typical difficulties that a structural biologist may face when dealing with carbohydrates, with an emphasis on problem solving in the resolution range where X-ray crystallography and cryo-electron microscopy are expected to overlap in the next decade.

Causal inferences on the effectiveness of complex social programs: Navigating assumptions, sources of complexity and evaluation design challenges.

PubMed

Chatterji, Madhabi

2016-12-01

This paper explores avenues for navigating evaluation design challenges posed by complex social programs (CSPs) and their environments when conducting studies that call for generalizable, causal inferences on the intervention's effectiveness. A definition is provided of a CSP drawing on examples from different fields, and an evaluation case is analyzed in depth to derive seven (7) major sources of complexity that typify CSPs, threatening assumptions of textbook-recommended experimental designs for performing impact evaluations. Theoretically-supported, alternative methodological strategies are discussed to navigate assumptions and counter the design challenges posed by the complex configurations and ecology of CSPs. Specific recommendations include: sequential refinement of the evaluation design through systems thinking, systems-informed logic modeling; and use of extended term, mixed methods (ETMM) approaches with exploratory and confirmatory phases of the evaluation. In the proposed approach, logic models are refined through direct induction and interactions with stakeholders. To better guide assumption evaluation, question-framing, and selection of appropriate methodological strategies, a multiphase evaluation design is recommended. Copyright © 2016 Elsevier Ltd. All rights reserved.

Attention-Modulating Effects of Cognitive Enhancers

PubMed Central

Levin, Edward D.; Bushnell, Philip J.; Rezvani, Amir H.

2011-01-01

Attention can be readily measured in experimental animal models. Animal models of attention have been used to better understand the neural systems involved in attention, how attention is impaired, and how therapeutic treatments can ameliorate attentional deficits. This review focuses on the ways in which animal models are used to better understand the neuronal mechanism of attention and how to develop new therapeutic treatments for attentional impairment. Several behavioral test methods have been developed for experimental animal studies of attention, including a 5-choice serial reaction time task (5-CSRTT), a signal detection task (SDT), and a novel object recognition (NOR) test. These tasks can be used together with genetic, lesion, pharmacological and behavioral models of attentional impairment to test the efficacy of novel therapeutic treatments. The most prominent genetic model is the spontaneously hypertensive rat (SHR). Well-characterized lesion models include frontal cortical or hippocamapal lesions. Pharmacological models include challenge with the NMDA glutamate antagonist dizocilpine (MK-801), the nicotinic cholinergic antagonist mecamylamine and the muscarinic cholinergic antagonist scopolamine. Behavioral models include distracting stimuli and attenuated target stimuli. Important validation of these behavioral tests and models of attentional impairments for developing effective treatments for attentional dysfunction is the fact that stimulant treatments effective for attention deficit hyperactivity disorder (ADHD), such as methylphenidate (Ritalin®), are effective in the experimental animal models. Newer lines of treatment including nicotinic agonists, α4β2 nicotinic receptor desensitizers, and histamine H3 antagonists, have also been found to be effective in improving attention in these animal models. Good carryover has also been seen for the attentional improvement of nicotine in experimental animal models and in human populations. Animal models of attention can be effectively used for the development of new treatments of attentional impairment in ADHD and other syndromes in which have attentional impairments occur, such as Alzheimer’s disease and schizophrenia. PMID:21334367

Secure quantum key distribution

NASA Astrophysics Data System (ADS)

Lo, Hoi-Kwong; Curty, Marcos; Tamaki, Kiyoshi

2014-08-01

Secure communication is crucial in the Internet Age, and quantum mechanics stands poised to revolutionize cryptography as we know it today. In this Review, we introduce the motivation and the current state of the art of research in quantum cryptography. In particular, we discuss the present security model together with its assumptions, strengths and weaknesses. After briefly introducing recent experimental progress and challenges, we survey the latest developments in quantum hacking and countermeasures against it.

Promoting the Multidimensional Character of Scientific Reasoning.

PubMed

Bradshaw, William S; Nelson, Jennifer; Adams, Byron J; Bell, John D

2017-04-01

This study reports part of a long-term program to help students improve scientific reasoning using higher-order cognitive tasks set in the discipline of cell biology. This skill was assessed using problems requiring the construction of valid conclusions drawn from authentic research data. We report here efforts to confirm the hypothesis that data interpretation is a complex, multifaceted exercise. Confirmation was obtained using a statistical treatment showing that various such problems rank students differently-each contains a unique set of cognitive challenges. Additional analyses of performance results have allowed us to demonstrate that individuals differ in their capacity to navigate five independent generic elements that constitute successful data interpretation: biological context, connection to course concepts, experimental protocols, data inference, and integration of isolated experimental observations into a coherent model. We offer these aspects of scientific thinking as a "data analysis skills inventory," along with usable sample problems that illustrate each element. Additionally, we show that this kind of reasoning is rigorous in that it is difficult for most novice students, who are unable to intuitively implement strategies for improving these skills. Instructors armed with knowledge of the specific challenges presented by different types of problems can provide specific helpful feedback during formative practice. The use of this instructional model is most likely to require changes in traditional classroom instruction.

Modeling of Materials for Energy Storage: A Challenge for Density Functional Theory

NASA Astrophysics Data System (ADS)

Kaltak, Merzuk; Fernandez-Serra, Marivi; Hybertsen, Mark S.

Hollandite α-MnO2 is a promising material for rechargeable batteries and is studied extensively in the community because of its interesting tunnel structure and the corresponding large capacity for lithium as well as sodium ions. However, the presence of partially reduced Mn ions due to doping with Ag or during lithiation makes hollandite a challenging system for density functional theory and the conventionally employed PBE+U method. A naive attempt to model the ternary system LixAgyMnO2 with density functionals, similar to those employed for the case y = 0 , fails and predicts a strong monoclinic distortion of the experimentally observed tetragonal unit cell for Ag2Mn8O16. Structure and binding energies are compared with experimental data and show the importance of van der Waals interactions as well as the necessity for an accurate description of the cooperative Jan-Teller effects for silver hollandite AgyMnO2. Based on these observations a ternary phase diagram is calculated allowing to predict the physical and chemical properties of LixAgyMnO2, such as stable stoichiometries, open circuit voltages, the formation of Ag metal and the structural change during lithiation. Department of Energy (DOE) under award #DE-SC0012673.

Turbine engine rotor health monitoring evaluation by means of finite element analyses and spin tests data

NASA Astrophysics Data System (ADS)

Abdul-Aziz, Ali; Woike, Mark R.; Clem, Michelle; Baaklini, George Y.

2014-04-01

Generally, rotating engine components undergo high centrifugal loading environment which subject them to various types of failure initiation mechanisms. Health monitoring of these components is a necessity and is often challenging to implement. This is primarily due to numerous factors including the presence of scattered loading conditions, flaw sizes, component geometry and materials properties, all which hinder the simplicity of applying health monitoring applications. This paper represents a summary work of combined experimental and analytical modeling that included data collection from a spin test experiment of a rotor disk addressing the aforementioned durability issues. It further covers presentation of results obtained from a finite element modeling study to characterize the structural durability of a cracked rotor as it relates to the experimental findings. The experimental data include blade tip clearance, blade tip timing and shaft displacement measurements. The tests were conducted at the NASA Glenn Research Center's Rotordynamics Laboratory, a high precision spin rig. The results are evaluated and examined to determine their significance on the development of a health monitoring system to pre-predict cracks and other anomalies and to assist in initiating a supplemental physics based fault prediction analytical model.

Quantum dots as contrast agents for endoscopy: mathematical modeling and experimental validation of the optimal excitation wavelength

NASA Astrophysics Data System (ADS)

Roy, Mathieu; DaCosta, Ralph S.; Weersink, Robert; Netchev, George; Davidson, Sean R. H.; Chan, Warren; Wilson, Brian C.

2007-02-01

Our group is investigating the use of ZnS-capped CdSe quantum dot (QD) bioconjugates combined with fluorescence endoscopy for improved early cancer detection in the esophagus, colon and lung. A major challenge in using fluorescent contrast agents in vivo is to extract the relevant signal from the tissue autofluorescence (AF). Our studies are aimed at maximizing the QD signal to AF background ratio (SBR) to facilitate detection. This work quantitatively evaluates the effect of the excitation wavelength on the SBR, using both experimental measurements and mathematical modeling. Experimental SBR measurements were done by imaging QD solutions placed onto (surface) or embedded in (sub-surface) ex vivo murine tissue samples (brain, kidney, liver, lung), using a polymethylmethacrylate (PMMA) microchannel phantom. The results suggest that the maximum contrast is reached when the excitation wavelength is set at 400+/-20 μm for the surface configuration. For the sub-surface configuration, the optimal excitation wavelength varies with the tissue type and QD emission wavelengths. Our mathematical model, based on an approximation to the diffusion equation, successfully predicts the optimal excitation wavelength for the surface configuration, but needs further modifications to be accurate in the sub-surface configuration.

Preclinical evaluation of bacterially produced RSV-G protein vaccine: Strong protection against RSV challenge in cotton rat model

PubMed Central

Fuentes, Sandra; Klenow, Laura; Golding, Hana; Khurana, Surender

2017-01-01

In current study, we evaluated the safety and protective efficacy of recombinant unglycosylated RSV G protein ectodomain produced in E. coli (in presence and absence of oil-in-water adjuvant) in a preclinical RSV susceptible cotton rat challenge model compared to formaldehyde inactivated RSV (FI-RSV) and live RSV experimental infection. The adjuvanted G protein vaccine induced robust neutralization antibody responses comparable to those generated by live RSV infection. Importantly, adjuvanted G protein significantly reduced viral loads in both the lungs and nose at early time points following viral challenge. Antibody kinetics determined by Surface Plasmon Resonance showed that adjuvanted G generated 10-fold higher G-binding antibodies compared to non-adjvuanted G vaccine and live RSV infection, which correlated strongly with both neutralization titers and viral load titers in the nose and lungs post-viral challenge. Antibody diversity analysis revealed immunodominant antigenic sites in the N- and C-termini of the RSV-G protein, that were boosted >10-fold by adjuvant and inversely correlated with viral load titers. Enhanced lung pathology was observed only in animals vaccinated with FI-RSV, but not in animals vaccinated with unadjuvanted or adjuvanted RSV-G vaccine after viral challenge. The bacterially produced unglycosylated G protein could be developed as a protective vaccine against RSV disease. PMID:28186208

Experimental induction of necrotic enteritis in chickens by a netB-positive Japanese isolate of Clostridium perfringens.

PubMed

To, Ho; Suzuki, Takayuki; Kawahara, Fumiya; Uetsuka, Koji; Nagai, Shinya; Nunoya, Tetsuo

2017-02-28

Necrotic enteritis (NE) is one of the most important bacterial diseases in terms of economic losses. Clostridium perfringens necrotic enteritis toxin B, NetB, was recently proposed as a new key virulent factor for the development of NE. The goal of this work was to develop a necrotic enteritis model in chickens by using a Japanese isolate of C. perfringens. The Japanese isolate has been found to contain netB gene, which had the same nucleotide and deduced amino acid sequences as those of prototype gene characterized in Australian strain EHE-NE18, and also expressed in vitro a 33-kDa protein identified as NetB toxin by nano-scale liquid chromatographic tandem mass spectrometry. In the challenge experiment, broiler chickens fed a commercial chicken starter diet for 14 days post-hatch were changed to a high protein feed mixed 50:50 with fishmeal for 6 days. At day 21 of age, feed was withheld for 24 hr, and each chicken was orally challenged twice daily with 2 ml each of C. perfringens culture (10 9 to 10 10 CFU) on 5 consecutive days. The gross necrotic lesions were observed in 90 and 12.5% of challenged and control chickens, respectively. To our knowledge, this is the first study that demonstrated that a netB-positive Japanese isolate of C. perfringens is able to induce the clinical signs and lesions characteristic of NE in the experimental model, which may be useful for evaluating the pathogenicity of field isolates, the efficacy of a vaccine or a specific drug against NE.

Molecular Modeling of Water Interfaces: From Molecular Spectroscopy to Thermodynamics.

PubMed

Nagata, Yuki; Ohto, Tatsuhiko; Backus, Ellen H G; Bonn, Mischa

2016-04-28

Understanding aqueous interfaces at the molecular level is not only fundamentally important, but also highly relevant for a variety of disciplines. For instance, electrode-water interfaces are relevant for electrochemistry, as are mineral-water interfaces for geochemistry and air-water interfaces for environmental chemistry; water-lipid interfaces constitute the boundaries of the cell membrane, and are thus relevant for biochemistry. One of the major challenges in these fields is to link macroscopic properties such as interfacial reactivity, solubility, and permeability as well as macroscopic thermodynamic and spectroscopic observables to the structure, structural changes, and dynamics of molecules at these interfaces. Simulations, by themselves, or in conjunction with appropriate experiments, can provide such molecular-level insights into aqueous interfaces. In this contribution, we review the current state-of-the-art of three levels of molecular dynamics (MD) simulation: ab initio, force field, and coarse-grained. We discuss the advantages, the potential, and the limitations of each approach for studying aqueous interfaces, by assessing computations of the sum-frequency generation spectra and surface tension. The comparison of experimental and simulation data provides information on the challenges of future MD simulations, such as improving the force field models and the van der Waals corrections in ab initio MD simulations. Once good agreement between experimental observables and simulation can be established, the simulation can be used to provide insights into the processes at a level of detail that is generally inaccessible to experiments. As an example we discuss the mechanism of the evaporation of water. We finish by presenting an outlook outlining four future challenges for molecular dynamics simulations of aqueous interfacial systems.

Validation of an Actuator Line Model Coupled to a Dynamic Stall Model for Pitching Motions Characteristic to Vertical Axis Turbines

NASA Astrophysics Data System (ADS)

Mendoza, Victor; Bachant, Peter; Wosnik, Martin; Goude, Anders

2016-09-01

Vertical axis wind turbines (VAWT) can be used to extract renewable energy from wind flows. A simpler design, low cost of maintenance, and the ability to accept flow from all directions perpendicular to the rotor axis are some of the most important advantages over conventional horizontal axis wind turbines (HAWT). However, VAWT encounter complex and unsteady fluid dynamics, which present significant modeling challenges. One of the most relevant phenomena is dynamic stall, which is caused by the unsteady variation of angle of attack throughout the blade rotation, and is the focus of the present study. Dynamic stall is usually used as a passive control for VAWT operating conditions, hence the importance of predicting its effects. In this study, a coupled model is implemented with the open-source CFD toolbox OpenFOAM for solving the Navier-Stokes equations, where an actuator line model and dynamic stall model are used to compute the blade loading and body force. Force coefficients obtained from the model are validated with experimental data of pitching airfoil in similar operating conditions as an H-rotor type VAWT. Numerical results show reasonable agreement with experimental data for pitching motion.

Mathematical Models of Blast-Induced TBI: Current Status, Challenges, and Prospects

PubMed Central

Gupta, Raj K.; Przekwas, Andrzej

2013-01-01

Blast-induced traumatic brain injury (TBI) has become a signature wound of recent military activities and is the leading cause of death and long-term disability among U.S. soldiers. The current limited understanding of brain injury mechanisms impedes the development of protection, diagnostic, and treatment strategies. We believe mathematical models of blast wave brain injury biomechanics and neurobiology, complemented with in vitro and in vivo experimental studies, will enable a better understanding of injury mechanisms and accelerate the development of both protective and treatment strategies. The goal of this paper is to review the current state of the art in mathematical and computational modeling of blast-induced TBI, identify research gaps, and recommend future developments. A brief overview of blast wave physics, injury biomechanics, and the neurobiology of brain injury is used as a foundation for a more detailed discussion of multiscale mathematical models of primary biomechanics and secondary injury and repair mechanisms. The paper also presents a discussion of model development strategies, experimental approaches to generate benchmark data for model validation, and potential applications of the model for prevention and protection against blast wave TBI. PMID:23755039

Automatic Parameterization Strategy for Cardiac Electrophysiology Simulations.

PubMed

Costa, Caroline Mendonca; Hoetzl, Elena; Rocha, Bernardo Martins; Prassl, Anton J; Plank, Gernot

2013-10-01

Driven by recent advances in medical imaging, image segmentation and numerical techniques, computer models of ventricular electrophysiology account for increasingly finer levels of anatomical and biophysical detail. However, considering the large number of model parameters involved parameterization poses a major challenge. A minimum requirement in combined experimental and modeling studies is to achieve good agreement in activation and repolarization sequences between model and experiment or patient data. In this study, we propose basic techniques which aid in determining bidomain parameters to match activation sequences. An iterative parameterization algorithm is implemented which determines appropriate bulk conductivities which yield prescribed velocities. In addition, a method is proposed for splitting the computed bulk conductivities into individual bidomain conductivities by prescribing anisotropy ratios.

Toward a multiscale modeling framework for understanding serotonergic function

PubMed Central

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

2017-01-01

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

Equation of State of the Two-Dimensional Hubbard Model

NASA Astrophysics Data System (ADS)

Cocchi, Eugenio; Miller, Luke A.; Drewes, Jan H.; Koschorreck, Marco; Pertot, Daniel; Brennecke, Ferdinand; Köhl, Michael

2016-04-01

The subtle interplay between kinetic energy, interactions, and dimensionality challenges our comprehension of strongly correlated physics observed, for example, in the solid state. In this quest, the Hubbard model has emerged as a conceptually simple, yet rich model describing such physics. Here we present an experimental determination of the equation of state of the repulsive two-dimensional Hubbard model over a broad range of interactions 0 ≲U /t ≲20 and temperatures, down to kBT /t =0.63 (2 ) using high-resolution imaging of ultracold fermionic atoms in optical lattices. We show density profiles, compressibilities, and double occupancies over the whole doping range, and, hence, our results constitute benchmarks for state-of-the-art theoretical approaches.

Considering RNAi experimental design in parasitic helminths.

PubMed

Dalzell, Johnathan J; Warnock, Neil D; McVeigh, Paul; Marks, Nikki J; Mousley, Angela; Atkinson, Louise; Maule, Aaron G

2012-04-01

Almost a decade has passed since the first report of RNA interference (RNAi) in a parasitic helminth. Whilst much progress has been made with RNAi informing gene function studies in disparate nematode and flatworm parasites, substantial and seemingly prohibitive difficulties have been encountered in some species, hindering progress. An appraisal of current practices, trends and ideals of RNAi experimental design in parasitic helminths is both timely and necessary for a number of reasons: firstly, the increasing availability of parasitic helminth genome/transcriptome resources means there is a growing need for gene function tools such as RNAi; secondly, fundamental differences and unique challenges exist for parasite species which do not apply to model organisms; thirdly, the inherent variation in experimental design, and reported difficulties with reproducibility undermine confidence. Ideally, RNAi studies of gene function should adopt standardised experimental design to aid reproducibility, interpretation and comparative analyses. Although the huge variations in parasite biology and experimental endpoints make RNAi experimental design standardization difficult or impractical, we must strive to validate RNAi experimentation in helminth parasites. To aid this process we identify multiple approaches to RNAi experimental validation and highlight those which we deem to be critical for gene function studies in helminth parasites.

Experiments in sensing transient rotational acceleration cues on a flight simulator

NASA Technical Reports Server (NTRS)

Parrish, R. V.

1979-01-01

Results are presented for two transient motion sensing experiments which were motivated by the identification of an anomalous roll cue (a 'jerk' attributed to an acceleration spike) in a prior investigation of realistic fighter motion simulation. The experimental results suggest the consideration of several issues for motion washout and challenge current sensory system modeling efforts. Although no sensory modeling effort is made it is argued that such models must incorporate the ability to handle transient inputs of short duration (some of which are less than the accepted latency times for sensing), and must represent separate channels for rotational acceleration and velocity sensing.

In vivo imaging in NHP models of malaria: challenges, progress and outlooks.

PubMed

Beignon, Anne-Sophie; Le Grand, Roger; Chapon, Catherine

2014-02-01

Animal models of malaria, mainly mice, have made a large contribution to our knowledge of host-pathogen interactions and immune responses, and to drug and vaccine design. Non-human primate (NHP) models for malaria are admittedly under-used, although they are probably closer models than mice for human malaria; in particular, NHP models allow the use of human pathogens (Plasmodium falciparum, Plasmodium vivax, Plasmodium malariae and Plasmodium knowlesi). NHPs, whether natural hosts or experimentally challenged with a simian Plasmodium, can also serve as robust pre-clinical models. Some simian parasites are closely related to a human counterpart, with which they may share a common ancestor, and display similar major features with the human infection and pathology. NHP models allow longitudinal studies, from the early events following sporozoite inoculation to the later events, including analysis of organs and tissues, particularly liver, spleen, brain and bone marrow. NHP models have one other significant advantage over mouse models: NHPs are our closest relatives and thus their biology is very similar to ours. Recently developed in vivo imaging tools have provided insight into malaria parasite infection and disease in mouse models. One advantage of these tools is that they limit the need for invasive procedures, such as tissue biopsies. Many such technologies are now available for NHP studies and provide new opportunities for elucidating host/parasite interactions. The aim of this review is to bring the malaria community up to date on what is currently possible and what soon will be, in terms of in vivo imaging in NHP models of malaria, to consider the pros and the cons of the various techniques, and to identify challenges. © 2013.

Development, fabrication, and modeling of highly sensitive conjugated polymer based piezoresistive sensors in electronic skin applications

NASA Astrophysics Data System (ADS)

Khalili, Nazanin; Naguib, Hani E.; Kwon, Roy H.

2016-04-01

Human intervention can be replaced through development of tools resulted from utilizing sensing devices possessing a wide range of applications including humanoid robots or remote and minimally invasive surgeries. Similar to the five human senses, sensors interface with their surroundings to stimulate a suitable response or action. The sense of touch which arises in human skin is among the most challenging senses to emulate due to its ultra high sensitivity. This has brought forth novel challenging issues to consider in the field of biomimetic robotics. In this work, using a multiphase reaction, a polypyrrole (PPy) based hydrogel is developed as a resistive type pressure sensor with an intrinsically elastic microstructure stemming from three dimensional hollow spheres. Furthermore, a semi-analytical constriction resistance model accounting for the real contact area between the PPy hydrogel sensors and the electrode along with the dependency of the contact resistance change on the applied load is developed. The model is then solved using a Monte Carlo technique and the sensitivity of the sensor is obtained. The experimental results showed the good tracking ability of the proposed model.

NIMROD Modeling of Sawtooth Modes Using Hot-Particle Closures

NASA Astrophysics Data System (ADS)

Kruger, Scott; Jenkins, T. G.; Held, E. D.; King, J. R.

2015-11-01

In DIII-D shot 96043, RF heating gives rise to an energetic ion population that alters the sawtooth stability boundary, replacing conventional sawtooth cycles by longer-period, larger-amplitude `giant sawtooth' oscillations. We explore the use of particle-in-cell closures within the NIMROD code to numerically represent the RF-induced hot-particle distribution, and investigate the role of this distribution in determining the altered mode onset threshold and subsequent nonlinear evolution. Equilibrium reconstructions from the experimental data are used to enable these detailed validation studies. Effects of other parameters on the sawtooth behavior, such as the plasma Lundquist number and hot-particle beta-fraction, are also considered. The fast energetic particles present many challenges for the PIC closure. We review new algorithm and performance improvements to address these challenges, and provide a preliminary assessment of the efficacy of the PIC closure versus a continuum model for energetic particle modeling. We also compare our results with those of, and discuss plans for a more complete validation campaign for this discharge. Supported by US Department of Energy via the SciDAC Center for Extended MHD Modeling (CEMM).

Slamming: Recent Progress in the Evaluation of Impact Pressures

NASA Astrophysics Data System (ADS)

Dias, Frédéric; Ghidaglia, Jean-Michel

2018-01-01

Slamming, the violent impact between a liquid and solid, has been known to be important for a long time in the ship hydrodynamics community. More recently, applications ranging from the transport of liquefied natural gas (LNG) in LNG carriers to the harvesting of wave energy with oscillating wave surge converters have led to renewed interest in the topic. The main reason for this renewed interest is that the extreme impact pressures generated during slamming can affect the integrity of the structures involved. Slamming fluid mechanics is challenging to describe, as much from an experimental viewpoint as from a numerical viewpoint, because of the large span of spatial and temporal scales involved. Even the physical mechanisms of slamming are challenging: What physical phenomena must be included in slamming models? An important issue deals with the practical modeling of slamming: Are there any simple models available? Are numerical models viable? What are the consequences for the design of structures? This article describes the loading processes involved in slamming, offers state-of-the-art results, and highlights unresolved issues worthy of further research.

[Study on the anti-NTHi infection of Hap recombinant protein in vivo].

PubMed

Li, Wan-yi; Wang, Bao-ning; Zuo, Feng-qiong; Zeng, Wei; Feng, Feng; Kuang, Yu; Jiang, Zhong-hua; Li, Ming-yuan

2010-07-01

To observe the immune effect of Hap recombinant protein on murine model of bronchopneumonia infected with NTHi, and explore the mechanism about the anti-NTHi infection. The C57BL/6 mice intranasally immunized with purified Hap recombinant protein and CT-B were challenged by NTHi encased in agar beads. The immunifaction of anti-infection was observed through encocyte counting of BALF, bacteria detection of lung and the pathologyical change of lung tissue. In the challenge with NTHi experiment, the inflammatory exudation of the infected murine and pathological change of lung tissue was relieved by combined immunization of Hap recombinant protein and CT-B, and quantity of NTHi in lung of the infected murine was reduced obviously. The Hap recombinant protein also had good ability of anti-NTHi infection in the murine model of NTHi bronchopneumonia. This study could offer the oretical and experimental basis for development of new vaccine against NTHi.

Lap time simulation and design optimisation of a brushed DC electric motorcycle for the Isle of Man TT Zero Challenge

NASA Astrophysics Data System (ADS)

Dal Bianco, N.; Lot, R.; Matthys, K.

2018-01-01

This works regards the design of an electric motorcycle for the annual Isle of Man TT Zero Challenge. Optimal control theory was used to perform lap time simulation and design optimisation. A bespoked model was developed, featuring 3D road topology, vehicle dynamics and electric power train, composed of a lithium battery pack, brushed DC motors and motor controller. The model runs simulations over the entire ? or ? of the Snaefell Mountain Course. The work is validated using experimental data from the BX chassis of the Brunel Racing team, which ran during the 2009 to 2015 TT Zero races. Optimal control is used to improve drive train and power train configurations. Findings demonstrate computational efficiency, good lap time prediction and design optimisation potential, achieving a 2 minutes reduction of the reference lap time through changes in final drive gear ratio, battery pack size and motor configuration.

A Taylor Expansion-Based Adaptive Design Strategy for Global Surrogate Modeling With Applications in Groundwater Modeling

NASA Astrophysics Data System (ADS)

Mo, Shaoxing; Lu, Dan; Shi, Xiaoqing; Zhang, Guannan; Ye, Ming; Wu, Jianfeng; Wu, Jichun

2017-12-01

Global sensitivity analysis (GSA) and uncertainty quantification (UQ) for groundwater modeling are challenging because of the model complexity and significant computational requirements. To reduce the massive computational cost, a cheap-to-evaluate surrogate model is usually constructed to approximate and replace the expensive groundwater models in the GSA and UQ. Constructing an accurate surrogate requires actual model simulations on a number of parameter samples. Thus, a robust experimental design strategy is desired to locate informative samples so as to reduce the computational cost in surrogate construction and consequently to improve the efficiency in the GSA and UQ. In this study, we develop a Taylor expansion-based adaptive design (TEAD) that aims to build an accurate global surrogate model with a small training sample size. TEAD defines a novel hybrid score function to search informative samples, and a robust stopping criterion to terminate the sample search that guarantees the resulted approximation errors satisfy the desired accuracy. The good performance of TEAD in building global surrogate models is demonstrated in seven analytical functions with different dimensionality and complexity in comparison to two widely used experimental design methods. The application of the TEAD-based surrogate method in two groundwater models shows that the TEAD design can effectively improve the computational efficiency of GSA and UQ for groundwater modeling.

Development of anti-inflammatory drugs - the research and development process.

PubMed

Knowles, Richard Graham

2014-01-01

The research and development process for novel drugs to treat inflammatory diseases is described, and several current issues and debates relevant to this are raised: the decline in productivity, attrition, challenges and trends in developing anti-inflammatory drugs, the poor clinical predictivity of experimental models of inflammatory diseases, heterogeneity within inflammatory diseases, 'improving on the Beatles' in treating inflammation, and the relationships between big pharma and biotechs. The pharmaceutical research and development community is responding to these challenges in multiple ways which it is hoped will lead to the discovery and development of a new generation of anti-inflammatory medicines. © 2013 Nordic Pharmacological Society. Published by John Wiley & Sons Ltd.

Self-assembly kinetics of microscale components: A parametric evaluation

NASA Astrophysics Data System (ADS)

Carballo, Jose M.

The goal of the present work is to develop, and evaluate a parametric model of a basic microscale Self-Assembly (SA) interaction that provides scaling predictions of process rates as a function of key process variables. At the microscale, assembly by "grasp and release" is generally challenging. Recent research efforts have proposed adapting nanoscale self-assembly (SA) processes to the microscale. SA offers the potential for reduced equipment cost and increased throughput by harnessing attractive forces (most commonly, capillary) to spontaneously assemble components. However, there are challenges for implementing microscale SA as a commercial process. The existing lack of design tools prevents simple process optimization. Previous efforts have characterized a specific aspect of the SA process. However, the existing microscale SA models do not characterize the inter-component interactions. All existing models have simplified the outcome of SA interactions as an experimentally-derived value specific to a particular configuration, instead of evaluating it outcome as a function of component level parameters (such as speed, geometry, bonding energy and direction). The present study parameterizes the outcome of interactions, and evaluates the effect of key parameters. The present work closes the gap between existing microscale SA models to add a key piece towards a complete design tool for general microscale SA process modeling. First, this work proposes a simple model for defining the probability of assembly of basic SA interactions. A basic SA interaction is defined as the event where a single part arrives on an assembly site. The model describes the probability of assembly as a function of kinetic energy, binding energy, orientation and incidence angle for the component and the assembly site. Secondly, an experimental SA system was designed, and implemented to create individual SA interactions while controlling process parameters independently. SA experiments measured the outcome of SA interactions, while studying the independent effects of each parameter. As a first step towards a complete scaling model, experiments were performed to evaluate the effects of part geometry and part travel direction under low kinetic energy conditions. Experimental results show minimal dependence of assembly yield on the incidence angle of the parts, and significant effects induced by changes in part geometry. The results from this work indicate that SA could be modeled as an energy-based process due to the small path dependence effects. Assembly probability is linearly related to the orientation probability. The proportionality constant is based on the area fraction of the sites with an amplification factor. This amplification factor accounts for the ability of capillary forces to align parts with only very small areas of contact when they have a low kinetic energy. Results provide unprecedented insight about SA interactions. The present study is a key step towards completing a basic model of a general SA process. Moreover, the outcome from this work can complement existing SA process models, in order to create a complete design tool for microscale SA systems. In addition to SA experiments, Monte Carlo simulations of experimental part-site interactions were conducted. This study confirmed that a major contributor to experimental variation is the stochastic nature of experimental SA interactions and the limited sample size of the experiments. Furthermore, the simulations serve as a tool for defining an optimum sampling strategy to minimize the uncertainty in future SA experiments.

A continuous optimization approach for inferring parameters in mathematical models of regulatory networks.

PubMed

Deng, Zhimin; Tian, Tianhai

2014-07-29

The advances of systems biology have raised a large number of sophisticated mathematical models for describing the dynamic property of complex biological systems. One of the major steps in developing mathematical models is to estimate unknown parameters of the model based on experimentally measured quantities. However, experimental conditions limit the amount of data that is available for mathematical modelling. The number of unknown parameters in mathematical models may be larger than the number of observation data. The imbalance between the number of experimental data and number of unknown parameters makes reverse-engineering problems particularly challenging. To address the issue of inadequate experimental data, we propose a continuous optimization approach for making reliable inference of model parameters. This approach first uses a spline interpolation to generate continuous functions of system dynamics as well as the first and second order derivatives of continuous functions. The expanded dataset is the basis to infer unknown model parameters using various continuous optimization criteria, including the error of simulation only, error of both simulation and the first derivative, or error of simulation as well as the first and second derivatives. We use three case studies to demonstrate the accuracy and reliability of the proposed new approach. Compared with the corresponding discrete criteria using experimental data at the measurement time points only, numerical results of the ERK kinase activation module show that the continuous absolute-error criteria using both function and high order derivatives generate estimates with better accuracy. This result is also supported by the second and third case studies for the G1/S transition network and the MAP kinase pathway, respectively. This suggests that the continuous absolute-error criteria lead to more accurate estimates than the corresponding discrete criteria. We also study the robustness property of these three models to examine the reliability of estimates. Simulation results show that the models with estimated parameters using continuous fitness functions have better robustness properties than those using the corresponding discrete fitness functions. The inference studies and robustness analysis suggest that the proposed continuous optimization criteria are effective and robust for estimating unknown parameters in mathematical models.

A dual-docking microfluidic cell migration assay (D2-Chip) for testing neutrophil chemotaxis and the memory effect.

PubMed

Yang, Ke; Wu, Jiandong; Xu, Guoqing; Xie, Dongxue; Peretz-Soroka, Hagit; Santos, Susy; Alexander, Murray; Zhu, Ling; Zhang, Michael; Liu, Yong; Lin, Francis

2017-04-18

Chemotaxis is a classic mechanism for guiding cell migration and an important topic in both fundamental cell biology and health sciences. Neutrophils are a widely used model to study eukaryotic cell migration and neutrophil chemotaxis itself can lead to protective or harmful immune actions to the body. While much has been learnt from past research about how neutrophils effectively navigate through a chemoattractant gradient, many interesting questions remain unclear. For example, while it is tempting to model neutrophil chemotaxis using the well-established biased random walk theory, the experimental proof was challenged by the cell's highly persistent migrating nature. A special experimental design is required to test the key predictions from the random walk model. Another question that has interested the cell migration community for decades concerns the existence of chemotactic memory and its underlying mechanism. Although chemotactic memory has been suggested in various studies, a clear quantitative experimental demonstration will improve our understanding of the migratory memory effect. Motivated by these questions, we developed a microfluidic cell migration assay (so-called dual-docking chip or D 2 -Chip) that can test both the biased random walk model and the memory effect for neutrophil chemotaxis on a single chip enabled by multi-region gradient generation and dual-region cell alignment. Our results provide experimental support for the biased random walk model and chemotactic memory for neutrophil chemotaxis. Quantitative data analyses provide new insights into neutrophil chemotaxis and memory by making connections to entropic disorder, cell morphology and oscillating migratory response.

Layout optimization of DRAM cells using rigorous simulation model for NTD

NASA Astrophysics Data System (ADS)

Jeon, Jinhyuck; Kim, Shinyoung; Park, Chanha; Yang, Hyunjo; Yim, Donggyu; Kuechler, Bernd; Zimmermann, Rainer; Muelders, Thomas; Klostermann, Ulrich; Schmoeller, Thomas; Do, Mun-hoe; Choi, Jung-Hoe

2014-03-01

DRAM chip space is mainly determined by the size of the memory cell array patterns which consist of periodic memory cell features and edges of the periodic array. Resolution Enhancement Techniques (RET) are used to optimize the periodic pattern process performance. Computational Lithography such as source mask optimization (SMO) to find the optimal off axis illumination and optical proximity correction (OPC) combined with model based SRAF placement are applied to print patterns on target. For 20nm Memory Cell optimization we see challenges that demand additional tool competence for layout optimization. The first challenge is a memory core pattern of brick-wall type with a k1 of 0.28, so it allows only two spectral beams to interfere. We will show how to analytically derive the only valid geometrically limited source. Another consequence of two-beam interference limitation is a "super stable" core pattern, with the advantage of high depth of focus (DoF) but also low sensitivity to proximity corrections or changes of contact aspect ratio. This makes an array edge correction very difficult. The edge can be the most critical pattern since it forms the transition from the very stable regime of periodic patterns to non-periodic periphery, so it combines the most critical pitch and highest susceptibility to defocus. Above challenge makes the layout correction to a complex optimization task demanding a layout optimization that finds a solution with optimal process stability taking into account DoF, exposure dose latitude (EL), mask error enhancement factor (MEEF) and mask manufacturability constraints. This can only be achieved by simultaneously considering all criteria while placing and sizing SRAFs and main mask features. The second challenge is the use of a negative tone development (NTD) type resist, which has a strong resist effect and is difficult to characterize experimentally due to negative resist profile taper angles that perturb CD at bottom characterization by scanning electron microscope (SEM) measurements. High resist impact and difficult model data acquisition demand for a simulation model that hat is capable of extrapolating reliably beyond its calibration dataset. We use rigorous simulation models to provide that predictive performance. We have discussed the need of a rigorous mask optimization process for DRAM contact cell layout yielding mask layouts that are optimal in process performance, mask manufacturability and accuracy. In this paper, we have shown the step by step process from analytical illumination source derivation, a NTD and application tailored model calibration to layout optimization such as OPC and SRAF placement. Finally the work has been verified with simulation and experimental results on wafer.

Determination of ultra-short laser induced damage threshold of KH{sub 2}PO{sub 4} crystal: Numerical calculation and experimental verification

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

Cheng, Jian; Department of Physics, The Ohio State University, 191 W. Woodruff Ave, Columbus, OH 43210; Chen, Mingjun, E-mail: chenmj@hit.edu.cn, E-mail: chowdhury.24@osu.edu

Rapid growth and ultra-precision machining of large-size KDP (KH{sub 2}PO{sub 4}) crystals with high laser damage resistance are tough challenges in the development of large laser systems. It is of high interest and practical significance to have theoretical models for scientists and manufacturers to determine the laser-induced damage threshold (LIDT) of actually prepared KDP optics. Here, we numerically and experimentally investigate the laser-induced damage on KDP crystals in ultra-short pulse laser regime. On basis of the rate equation for free electron generation, a model dedicated to predicting the LIDT is developed by considering the synergistic effect of photoionization, impact ionizationmore » and decay of electrons. Laser damage tests are performed to measure the single-pulse LIDT with several testing protocols. The testing results combined with previously reported experimental data agree well with those calculated by the model. By taking the light intensification into consideration, the model is successfully applied to quantitatively evaluate the effect of surface flaws inevitably introduced in the preparation processes on the laser damage resistance of KDP crystals. This work can not only contribute to further understanding of the laser damage mechanisms of optical materials, but also provide available models for evaluating the laser damage resistance of exquisitely prepared optical components used in high power laser systems.« less

Nuclear Explosion Monitoring Advances and Challenges

NASA Astrophysics Data System (ADS)

Baker, G. E.

2015-12-01

We address the state-of-the-art in areas important to monitoring, current challenges, specific efforts that illustrate approaches addressing shortcomings in capabilities, and additional approaches that might be helpful. The exponential increase in the number of events that must be screened as magnitude thresholds decrease presents one of the greatest challenges. Ongoing efforts to exploit repeat seismic events using waveform correlation, subspace methods, and empirical matched field processing holds as much "game-changing" promise as anything being done, and further efforts to develop and apply such methods efficiently are critical. Greater accuracy of travel time, signal loss, and full waveform predictions are still needed to better locate and discriminate seismic events. Important developments include methods to model velocities using multiple types of data; to model attenuation with better separation of source, path, and site effects; and to model focusing and defocusing of surface waves. Current efforts to model higher frequency full waveforms are likely to improve source characterization while more effective estimation of attenuation from ambient noise holds promise for filling in gaps. Censoring in attenuation modeling is a critical problem to address. Quantifying uncertainty of discriminants is key to their operational use. Efforts to do so for moment tensor (MT) inversion are particularly important, and fundamental progress on the statistics of MT distributions is the most important advance needed in the near term in this area. Source physics is seeing great progress through theoretical, experimental, and simulation studies. The biggest need is to accurately predict the effects of source conditions on seismic generation. Uniqueness is the challenge here. Progress will depend on studies that probe what distinguishes mechanisms, rather than whether one of many possible mechanisms is consistent with some set of observations.

Kinetic modeling of cell metabolism for microbial production.

PubMed

Costa, Rafael S; Hartmann, Andras; Vinga, Susana

2016-02-10

Kinetic models of cellular metabolism are important tools for the rational design of metabolic engineering strategies and to explain properties of complex biological systems. The recent developments in high-throughput experimental data are leading to new computational approaches for building kinetic models of metabolism. Herein, we briefly survey the available databases, standards and software tools that can be applied for kinetic models of metabolism. In addition, we give an overview about recently developed ordinary differential equations (ODE)-based kinetic models of metabolism and some of the main applications of such models are illustrated in guiding metabolic engineering design. Finally, we review the kinetic modeling approaches of large-scale networks that are emerging, discussing their main advantages, challenges and limitations. Copyright © 2015 Elsevier B.V. All rights reserved.

An analytical-numerical approach for parameter determination of a five-parameter single-diode model of photovoltaic cells and modules

NASA Astrophysics Data System (ADS)

Hejri, Mohammad; Mokhtari, Hossein; Azizian, Mohammad Reza; Söder, Lennart

2016-04-01

Parameter extraction of the five-parameter single-diode model of solar cells and modules from experimental data is a challenging problem. These parameters are evaluated from a set of nonlinear equations that cannot be solved analytically. On the other hand, a numerical solution of such equations needs a suitable initial guess to converge to a solution. This paper presents a new set of approximate analytical solutions for the parameters of a five-parameter single-diode model of photovoltaic (PV) cells and modules. The proposed solutions provide a good initial point which guarantees numerical analysis convergence. The proposed technique needs only a few data from the PV current-voltage characteristics, i.e. open circuit voltage Voc, short circuit current Isc and maximum power point current and voltage Im; Vm making it a fast and low cost parameter determination technique. The accuracy of the presented theoretical I-V curves is verified by experimental data.

Tribute to the contribution of Gerard Lallenment to structural dynamics

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

Los Alamos National Laboratory

The Society for Experimental Mechanics and the International Modal Analysis Conference recognize the remarkable contribution to experimental mechanics, mechanical engineering and structural dynamics of Professor Gerard Lallement, from the University of Franche-Comte, France. A special session is organized during the IMAC-XX to outline the many achievements of Gerard Lallement in the fields of modal analysis, structural system identification, the theory and practice of structural modification, component mode synthesis and finite element model updating. The purpose of this publication is not to provide an exhaustive account of Gerard Lallement's contribution to structural dynamics. Numerous references are provided that should help themore » interested reader learn more about the many aspects of his work. Instead, the significance of this work is illustrated by discussing the role of structural dynamics in industrial applications and its future challenges. The technical aspects of Gerard Lallement's work are illustrated with a discussion of structural modification, modeling error localization and model updating.« less

Adaptive classifier for steel strip surface defects

NASA Astrophysics Data System (ADS)

Jiang, Mingming; Li, Guangyao; Xie, Li; Xiao, Mang; Yi, Li

2017-01-01

Surface defects detection system has been receiving increased attention as its precision, speed and less cost. One of the most challenges is reacting to accuracy deterioration with time as aged equipment and changed processes. These variables will make a tiny change to the real world model but a big impact on the classification result. In this paper, we propose a new adaptive classifier with a Bayes kernel (BYEC) which update the model with small sample to it adaptive for accuracy deterioration. Firstly, abundant features were introduced to cover lots of information about the defects. Secondly, we constructed a series of SVMs with the random subspace of the features. Then, a Bayes classifier was trained as an evolutionary kernel to fuse the results from base SVMs. Finally, we proposed the method to update the Bayes evolutionary kernel. The proposed algorithm is experimentally compared with different algorithms, experimental results demonstrate that the proposed method can be updated with small sample and fit the changed model well. Robustness, low requirement for samples and adaptive is presented in the experiment.

Single cell model for simultaneous drug delivery and efflux.

PubMed

Yi, C; Saidel, G M; Gratzl, M

1999-01-01

Multidrug resistance (MDR) of some cancer cells is a major challenge for chemotherapy of systemic cancers to overcome. To experimentally uncover the cellular mechanisms leading to MDR, it is necessary to quantitatively assess both drug influx into, and efflux from, the cells exposed to drug treatment. By using a novel molecular microdelivery system to enforce continuous and adjustable drug influx into single cells by controlled diffusion through a gel plug in a micropipet tip, drug resistance studies can now be performed on the single cell level. Our dynamic model of this scheme incorporates drug delivery, diffusive mixing, and accumulation inside the cytoplasm, and efflux by both passive and active membrane transport. Model simulations using available experimental information on these processes can assist in the design of MDR related experiments on single cancer cells which are expected to lead to a quantitative evaluation of mechanisms. Simulations indicate that drug resistance of a cancer cell can be quantified better by its dynamic response than by steady-state analysis.

Establishment of an oral infection model resembling the periodontal pocket in a perfusion bioreactor system

PubMed Central

Bao, Kai; Papadimitropoulos, Adam; Akgül, Baki; Belibasakis, Georgios N; Bostanci, Nagihan

2015-01-01

Periodontal infection involves a complex interplay between oral biofilms, gingival tissues and cells of the immune system in a dynamic microenvironment. A humanized in vitro model that reduces the need for experimental animal models, while recapitulating key biological events in a periodontal pocket, would constitute a technical advancement in the study of periodontal disease. The aim of this study was to use a dynamic perfusion bioreactor in order to develop a gingival epithelial-fibroblast-monocyte organotypic co-culture on collagen sponges. An 11 species subgingival biofilm was used to challenge the generated tissue in the bioreactor for a period of 24 h. The histological and scanning electron microscopy analysis displayed an epithelial-like layer on the surface of the collagen sponge, supported by the underlying ingrowth of gingival fibroblasts, while monocytic cells were also found within the sponge mass. Bacterial quantification of the biofilm showed that in the presence of the organotypic tissue, the growth of selected biofilm species, especially Campylobacter rectus, Actinomyces oris, Streptococcus anginosus, Veillonella dispar, and Porphyromonas gingivalis, was suppressed, indicating a potential antimicrobial effect by the tissue. Multiplex immunoassay analysis of cytokine secretion showed that interleukin (IL)-1 β, IL-2, IL-4, and tumor necrosis factor (TNF)-α levels in cell culture supernatants were significantly up-regulated in presence of the biofilm, indicating a positive inflammatory response of the organotypic tissue to the biofilm challenge. In conclusion, this novel host-biofilm interaction organotypic model might resemble the periodontal pocket and have an important impact on the study of periodontal infections, by minimizing the need for the use of experimental animal models. PMID:25587671

An experimental model of allergic asthma in cats sensitized to house dust mite or bermuda grass allergen.

PubMed

Norris Reinero, Carol R; Decile, Kendra C; Berghaus, Roy D; Williams, Kurt J; Leutenegger, Christian M; Walby, William F; Schelegle, Edward S; Hyde, Dallas M; Gershwin, Laurel J

2004-10-01

Animal models are used to mimic human asthma, however, not all models replicate the major characteristics of the human disease. Spontaneous development of asthma with hallmark features similar to humans has been documented to occur with relative frequency in only one animal species, the cat. We hypothesized that we could develop an experimental model of feline asthma using clinically relevant aeroallergens identified from cases of naturally developing feline asthma, and characterize immunologic, physiologic, and pathologic changes over 1 year. House dust mite (HDMA) and Bermuda grass (BGA) allergen were selected by screening 10 privately owned pet cats with spontaneous asthma using a serum allergen-specific IgE ELISA. Parenteral sensitization and aerosol challenges were used to replicate the naturally developing disease in research cats. The asthmatic phenotype was characterized using intradermal skin testing, serum allergen-specific IgE ELISA, serum and bronchoalveolar lavage fluid (BALF) IgG and IgA ELISAs, airway hyperresponsiveness testing, BALF cytology, cytokine profiles using TaqMan PCR, and histopathologic evaluation. Sensitization with HDMA or BGA in cats led to allergen-specific IgE production, allergen-specific serum and BALF IgG and IgA production, airway hyperreactivity, airway eosinophilia, an acute T helper 2 cytokine profile in peripheral blood mononuclear cells and BALF cells, and histologic evidence of airway remodeling. Using clinically relevant aeroallergens to sensitize and challenge the cat provides an additional animal model to study the immunopathophysiologic mechanisms of allergic asthma. Chronic exposure to allergen in the cat leads to a variety of immunologic, physiologic, and pathologic changes that mimic the features seen in human asthma.

A case study to quantify prediction bounds caused by model-form uncertainty of a portal frame

NASA Astrophysics Data System (ADS)

Van Buren, Kendra L.; Hall, Thomas M.; Gonzales, Lindsey M.; Hemez, François M.; Anton, Steven R.

2015-01-01

Numerical simulations, irrespective of the discipline or application, are often plagued by arbitrary numerical and modeling choices. Arbitrary choices can originate from kinematic assumptions, for example the use of 1D beam, 2D shell, or 3D continuum elements, mesh discretization choices, boundary condition models, and the representation of contact and friction in the simulation. This work takes a step toward understanding the effect of arbitrary choices and model-form assumptions on the accuracy of numerical predictions. The application is the simulation of the first four resonant frequencies of a one-story aluminum portal frame structure under free-free boundary conditions. The main challenge of the portal frame structure resides in modeling the joint connections, for which different modeling assumptions are available. To study this model-form uncertainty, and compare it to other types of uncertainty, two finite element models are developed using solid elements, and with differing representations of the beam-to-column and column-to-base plate connections: (i) contact stiffness coefficients or (ii) tied nodes. Test-analysis correlation is performed to compare the lower and upper bounds of numerical predictions obtained from parametric studies of the joint modeling strategies to the range of experimentally obtained natural frequencies. The approach proposed is, first, to characterize the experimental variability of the joints by varying the bolt torque, method of bolt tightening, and the sequence in which the bolts are tightened. The second step is to convert what is learned from these experimental studies to models that "envelope" the range of observed bolt behavior. We show that this approach, that combines small-scale experiments, sensitivity analysis studies, and bounding-case models, successfully produces lower and upper bounds of resonant frequency predictions that match those measured experimentally on the frame structure. (Approved for unlimited, public release, LA-UR-13-27561).

Comparative safety, immunogenicity, and efficacy of several anti-H5N1 influenza experimental vaccines in a mouse and chicken models (Testing of killed and live H5 vaccine).

PubMed

Gambaryan, Alexandra S; Lomakina, Natalia F; Boravleva, Elizaveta Y; Kropotkina, Ekaterina A; Mashin, Vadim V; Krasilnikov, Igor V; Klimov, Alexander I; Rudenko, Larisa G

2012-05-01

Parallel testing of inactivated (split and whole virion) and live vaccine was conducted to compare the immunogenicity and protective efficacy against homologous and heterosubtypic challenge by H5N1 highly pathogenic avian influenza virus. Four experimental live vaccines based on two H5N1 influenza virus strains were tested; two of them had hemagglutinin (HA) of A/Vietnam/1203/04 strain lacking the polybasic HA cleavage site, and two others had hemagglutinins from attenuated H5N1 virus A/Chicken/Kurgan/3/05, with amino acid substitutions of Asp54/Asn and Lys222/Thr in HA1 and Val48/Ile and Lys131/Thr in HA2 while maintaining the polybasic HA cleavage site. The neuraminidase and non-glycoprotein genes of the experimental live vaccines were from H2N2 cold-adapted master strain A/Leningrad/134/17/57 (VN-Len and Ku-Len) or from the apathogenic H6N2 virus A/Gull/Moscow/3100/2006 (VN-Gull and Ku-Gull). Inactivated H5N1 and H1N1 and live H1N1 vaccine were used for comparison. All vaccines were applied in a single dose. Safety, immunogenicity, and protectivity against the challenge with HPAI H5N1 virus A/Chicken/Kurgan/3/05 were estimated. All experimental live H5 vaccines tested were apathogenic as determined by weight loss and conferred more than 90% protection against lethal challenge with A/Chicken/Kurgan/3/05 infection. Inactivated H1N1 vaccine in mice offered no protection against challenge with H5N1 virus, while live cold-adapted H1N1 vaccine reduced the mortality near to zero level. The high yield, safety, and protectivity of VN-Len and Ku-Len made them promising strains for the production of inactivated and live vaccines against H5N1 viruses. © 2011 Blackwell Publishing Ltd.

GABA abnormalities in schizophrenia: a methodological review of in vivo studies.

PubMed

Taylor, Stephan F; Tso, Ivy F

2015-09-01

Abnormalities of GABAergic interneurons are some of the most consistent findings from post-mortem studies of schizophrenia. However, linking these molecular deficits with in vivo observations in patients - a critical goal in order to evaluate interventions that would target GABAergic deficits - presents a challenge. Explanatory models have been developed based on animal work and the emerging experimental literature in schizophrenia patients. This literature includes: neuroimaging ligands to GABA receptors, magnetic resonance spectroscopy (MRS) of GABA concentration, transcranial magnetic stimulation of cortical inhibitory circuits and pharmacologic probes of GABA receptors to dynamically challenge the GABA system, usually in combination with neuroimaging studies. Pharmacologic challenges have elicited behavioral changes, and preliminary studies of therapeutic GABAergic interventions have been conducted. This article critically reviews the evidence for GABAergic dysfunction from each of these areas. These methods remain indirect measures of GABAergic function, and a broad array of dysfunction is linked with the putative GABAergic measures, including positive symptoms, cognition, emotion, motor processing and sensory processing, covering diverse brain areas. Measures of receptor binding have not shown replicable group differences in binding, and MRS assays of GABA concentration have yielded equivocal evidence of large-scale alteration in GABA concentration. Overall, the experimental base remains sparse, and much remains to be learned about the role of GABAergic interneurons in healthy brains. Challenges with pharmacologic and functional probes show promise, and may yet enable a better characterization of GABAergic deficits in schizophrenia. Copyright © 2014 Elsevier B.V. All rights reserved.

Rotary-Wing Relevant Compressor Aero Research and Technology Development Activities at Glenn Research Center

NASA Technical Reports Server (NTRS)

Welch, Gerard E.; Hathaway, Michael D.; Skoch, Gary J.; Snyder, Christopher A.

2012-01-01

Technical challenges of compressors for future rotorcraft engines are driven by engine-level and component-level requirements. Cycle analyses are used to highlight the engine-level challenges for 3000, 7500, and 12000 SHP-class engines, which include retention of performance and stability margin at low corrected flows, and matching compressor type, axial-flow or centrifugal, to the low corrected flows and high temperatures in the aft stages. At the component level: power-to-weight and efficiency requirements impel designs with lower inherent aerodynamic stability margin; and, optimum engine overall pressure ratios lead to small blade heights and the associated challenges of scale, particularly increased clearance-to-span ratios. The technical challenges associated with the aerodynamics of low corrected flows and stability management impel the compressor aero research and development efforts reviewed herein. These activities include development of simple models for clearance sensitivities to improve cycle calculations, full-annulus, unsteady Navier-Stokes simulations used to elucidate stall, its inception, and the physics of stall control by discrete tip-injection, development of an actuator-duct-based model for rapid simulation of nonaxisymmetric flow fields (e.g., due inlet circumferential distortion), advanced centrifugal compressor stage development and experimentation, and application of stall control in a T700 engine.

Modeling complexes of modeled proteins.

PubMed

Anishchenko, Ivan; Kundrotas, Petras J; Vakser, Ilya A

2017-03-01

Structural characterization of proteins is essential for understanding life processes at the molecular level. However, only a fraction of known proteins have experimentally determined structures. This fraction is even smaller for protein-protein complexes. Thus, structural modeling of protein-protein interactions (docking) primarily has to rely on modeled structures of the individual proteins, which typically are less accurate than the experimentally determined ones. Such "double" modeling is the Grand Challenge of structural reconstruction of the interactome. Yet it remains so far largely untested in a systematic way. We present a comprehensive validation of template-based and free docking on a set of 165 complexes, where each protein model has six levels of structural accuracy, from 1 to 6 Å C α RMSD. Many template-based docking predictions fall into acceptable quality category, according to the CAPRI criteria, even for highly inaccurate proteins (5-6 Å RMSD), although the number of such models (and, consequently, the docking success rate) drops significantly for models with RMSD > 4 Å. The results show that the existing docking methodologies can be successfully applied to protein models with a broad range of structural accuracy, and the template-based docking is much less sensitive to inaccuracies of protein models than the free docking. Proteins 2017; 85:470-478. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A Bayesian approach to estimating hidden variables as well as missing and wrong molecular interactions in ordinary differential equation-based mathematical models.

PubMed

Engelhardt, Benjamin; Kschischo, Maik; Fröhlich, Holger

2017-06-01

Ordinary differential equations (ODEs) are a popular approach to quantitatively model molecular networks based on biological knowledge. However, such knowledge is typically restricted. Wrongly modelled biological mechanisms as well as relevant external influence factors that are not included into the model are likely to manifest in major discrepancies between model predictions and experimental data. Finding the exact reasons for such observed discrepancies can be quite challenging in practice. In order to address this issue, we suggest a Bayesian approach to estimate hidden influences in ODE-based models. The method can distinguish between exogenous and endogenous hidden influences. Thus, we can detect wrongly specified as well as missed molecular interactions in the model. We demonstrate the performance of our Bayesian dynamic elastic-net with several ordinary differential equation models from the literature, such as human JAK-STAT signalling, information processing at the erythropoietin receptor, isomerization of liquid α -Pinene, G protein cycling in yeast and UV-B triggered signalling in plants. Moreover, we investigate a set of commonly known network motifs and a gene-regulatory network. Altogether our method supports the modeller in an algorithmic manner to identify possible sources of errors in ODE-based models on the basis of experimental data. © 2017 The Author(s).

Current advancements and challenges in soil-root interactions modelling

NASA Astrophysics Data System (ADS)

Schnepf, Andrea; Huber, Katrin; Abesha, Betiglu; Meunier, Felicien; Leitner, Daniel; Roose, Tiina; Javaux, Mathieu; Vanderborght, Jan; Vereecken, Harry

2015-04-01

Roots change their surrounding soil chemically, physically and biologically. This includes changes in soil moisture and solute concentration, the exudation of organic substances into the rhizosphere, increased growth of soil microorganisms, or changes in soil structure. The fate of water and solutes in the root zone is highly determined by these root-soil interactions. Mathematical models of soil-root systems in combination with non-invasive techniques able to characterize root systems are a promising tool to understand and predict the behaviour of water and solutes in the root zone. With respect to different fields of applications, predictive mathematical models can contribute to the solution of optimal control problems in plant recourse efficiency. This may result in significant gains in productivity, efficiency and environmental sustainability in various land use activities. Major challenges include the coupling of model parameters of the relevant processes with the surrounding environment such as temperature, nutrient concentration or soil water content. A further challenge is the mathematical description of the different spatial and temporal scales involved. This includes in particular the branched structures formed by root systems or the external mycelium of mycorrhizal fungi. Here, reducing complexity as well as bridging between spatial scales is required. Furthermore, the combination of experimental and mathematical techniques may advance the field enormously. Here, the use of root system, soil and rhizosphere models is presented through a number of modelling case studies, including image based modelling of phosphate uptake by a root with hairs, model-based optimization of root architecture for phosphate uptake from soil, upscaling of rhizosphere models, modelling root growth in structured soil, and the effect of root hydraulic architecture on plant water uptake efficiency and drought resistance.

Current Advancements and Challenges in Soil-Root Interactions Modelling

NASA Astrophysics Data System (ADS)

Schnepf, A.; Huber, K.; Abesha, B.; Meunier, F.; Leitner, D.; Roose, T.; Javaux, M.; Vanderborght, J.; Vereecken, H.

2014-12-01

Roots change their surrounding soil chemically, physically and biologically. This includes changes in soil moisture and solute concentration, the exudation of organic substances into the rhizosphere, increased growth of soil microorganisms, or changes in soil structure. The fate of water and solutes in the root zone is highly determined by these root-soil interactions. Mathematical models of soil-root systems in combination with non-invasive techniques able to characterize root systems are a promising tool to understand and predict the behaviour of water and solutes in the root zone. With respect to different fields of applications, predictive mathematical models can contribute to the solution of optimal control problems in plant recourse efficiency. This may result in significant gains in productivity, efficiency and environmental sustainability in various land use activities. Major challenges include the coupling of model parameters of the relevant processes with the surrounding environment such as temperature, nutrient concentration or soil water content. A further challenge is the mathematical description of the different spatial and temporal scales involved. This includes in particular the branched structures formed by root systems or the external mycelium of mycorrhizal fungi. Here, reducing complexity as well as bridging between spatial scales is required. Furthermore, the combination of experimental and mathematical techniques may advance the field enormously. Here, the use of root system, soil and rhizosphere models is presented through a number of modelling case studies, including image based modelling of phosphate uptake by a root with hairs, model-based optimization of root architecture for phosphate uptake from soil, upscaling of rhizosphere models, modelling root growth in structured soil, and the effect of root hydraulic architecture on plant water uptake efficiency and drought resistance.

An Approximate Markov Model for the Wright-Fisher Diffusion and Its Application to Time Series Data.

PubMed

Ferrer-Admetlla, Anna; Leuenberger, Christoph; Jensen, Jeffrey D; Wegmann, Daniel

2016-06-01

The joint and accurate inference of selection and demography from genetic data is considered a particularly challenging question in population genetics, since both process may lead to very similar patterns of genetic diversity. However, additional information for disentangling these effects may be obtained by observing changes in allele frequencies over multiple time points. Such data are common in experimental evolution studies, as well as in the comparison of ancient and contemporary samples. Leveraging this information, however, has been computationally challenging, particularly when considering multilocus data sets. To overcome these issues, we introduce a novel, discrete approximation for diffusion processes, termed mean transition time approximation, which preserves the long-term behavior of the underlying continuous diffusion process. We then derive this approximation for the particular case of inferring selection and demography from time series data under the classic Wright-Fisher model and demonstrate that our approximation is well suited to describe allele trajectories through time, even when only a few states are used. We then develop a Bayesian inference approach to jointly infer the population size and locus-specific selection coefficients with high accuracy and further extend this model to also infer the rates of sequencing errors and mutations. We finally apply our approach to recent experimental data on the evolution of drug resistance in influenza virus, identifying likely targets of selection and finding evidence for much larger viral population sizes than previously reported. Copyright © 2016 by the Genetics Society of America.

Comparison of the efficacy of a commercial inactivated influenza A/H1N1/pdm09 virus (pH1N1) vaccine and two experimental M2e-based vaccines against pH1N1 challenge in the growing pig model.

PubMed

Opriessnig, Tanja; Gauger, Phillip C; Gerber, Priscilla F; Castro, Alessandra M M G; Shen, Huigang; Murphy, Lita; Digard, Paul; Halbur, Patrick G; Xia, Ming; Jiang, Xi; Tan, Ming

2018-01-01

Swine influenza A viruses (IAV-S) found in North American pigs are diverse and the lack of cross-protection among heterologous strains is a concern. The objective of this study was to compare a commercial inactivated A/H1N1/pdm09 (pH1N1) vaccine and two novel subunit vaccines, using IAV M2 ectodomain (M2e) epitopes as antigens, in a growing pig model. Thirty-nine 2-week-old IAV negative pigs were randomly assigned to five groups and rooms. At 3 weeks of age and again at 5 weeks of age, pigs were vaccinated intranasally with an experimental subunit particle vaccine (NvParticle/M2e) or a subunit complex-based vaccine (NvComplex/M2e) or intramuscularly with a commercial inactivated vaccine (Inact/pH1N1). At 7 weeks of age, the pigs were challenged with pH1N1 virus or sham-inoculated. Necropsy was conducted 5 days post pH1N1 challenge (dpc). At the time of challenge one of the Inact/pH1N1 pigs had seroconverted based on IAV nucleoprotein-based ELISA, Inact/pH1N1 pigs had significantly higher pdm09H1N1 hemagglutination inhibition (HI) titers compared to all other groups, and M2e-specific IgG responses were detected in the NvParticle/M2e and the NvComplex/M2e pigs with significantly higher group means in the NvComplex/M2e group compared to SHAMVAC-NEG pigs. After challenge, nasal IAV RNA shedding was significantly reduced in Inact/pH1N1 pigs compared to all other pH1N1 infected groups and this group also had reduced IAV RNA in oral fluids. The macroscopic lung lesions were characterized by mild-to-severe, multifocal-to-diffuse, cranioventral dark purple consolidated areas typical of IAV infection and were similar for NvParticle/M2e, NvComplex/M2e and SHAMVAC-IAV pigs. Lesions were significantly less severe in the SHAMVAC-NEG and the Inact/pH1N1pigs. Under the conditions of this study, a commercial Inact/pH1N1 specific vaccine effectively protected pigs against homologous challenge as evidenced by reduced clinical signs, virus shedding in nasal secretions and oral fluids and reduced macroscopic and microscopic lesions whereas intranasal vaccination with experimental M2e epitope-based subunit vaccines did not. The results further highlight the importance using IAV-S type specific vaccines in pigs.

Non-lethal control of the cariogenic potential of an agent-based model for dental plaque.

PubMed

Head, David A; Marsh, Phil D; Devine, Deirdre A

2014-01-01

Dental caries or tooth decay is a prevalent global disease whose causative agent is the oral biofilm known as plaque. According to the ecological plaque hypothesis, this biofilm becomes pathogenic when external challenges drive it towards a state with a high proportion of acid-producing bacteria. Determining which factors control biofilm composition is therefore desirable when developing novel clinical treatments to combat caries, but is also challenging due to the system complexity and the existence of multiple bacterial species performing similar functions. Here we employ agent-based mathematical modelling to simulate a biofilm consisting of two competing, distinct types of bacterial populations, each parameterised by their nutrient uptake and aciduricity, periodically subjected to an acid challenge resulting from the metabolism of dietary carbohydrates. It was found that one population was progressively eliminated from the system to give either a benign or a pathogenic biofilm, with a tipping point between these two fates depending on a multiplicity of factors relating to microbial physiology and biofilm geometry. Parameter sensitivity was quantified by individually varying the model parameters against putative experimental measures, suggesting non-lethal interventions that can favourably modulate biofilm composition. We discuss how the same parameter sensitivity data can be used to guide the design of validation experiments, and argue for the benefits of in silico modelling in providing an additional predictive capability upstream from in vitro experiments.

Experimental search for high-temperature ferroelectric perovskites guided by two-step machine learning.

PubMed

Balachandran, Prasanna V; Kowalski, Benjamin; Sehirlioglu, Alp; Lookman, Turab

2018-04-26

Experimental search for high-temperature ferroelectric perovskites is a challenging task due to the vast chemical space and lack of predictive guidelines. Here, we demonstrate a two-step machine learning approach to guide experiments in search of xBi[Formula: see text]O 3 -(1 - x)PbTiO 3 -based perovskites with high ferroelectric Curie temperature. These involve classification learning to screen for compositions in the perovskite structures, and regression coupled to active learning to identify promising perovskites for synthesis and feedback. The problem is challenging because the search space is vast, spanning ~61,500 compositions and only 167 are experimentally studied. Furthermore, not every composition can be synthesized in the perovskite phase. In this work, we predict x, y, Me', and Me″ such that the resulting compositions have both high Curie temperature and form in the perovskite structure. Outcomes from both successful and failed experiments then iteratively refine the machine learning models via an active learning loop. Our approach finds six perovskites out of ten compositions synthesized, including three previously unexplored {Me'Me″} pairs, with 0.2Bi(Fe 0.12 Co 0.88 )O 3 -0.8PbTiO 3 showing the highest measured Curie temperature of 898 K among them.

Improving accuracy of electrochemical capacitance and solvation energetics in first-principles calculations

NASA Astrophysics Data System (ADS)

Sundararaman, Ravishankar; Letchworth-Weaver, Kendra; Schwarz, Kathleen A.

2018-04-01

Reliable first-principles calculations of electrochemical processes require accurate prediction of the interfacial capacitance, a challenge for current computationally efficient continuum solvation methodologies. We develop a model for the double layer of a metallic electrode that reproduces the features of the experimental capacitance of Ag(100) in a non-adsorbing, aqueous electrolyte, including a broad hump in the capacitance near the potential of zero charge and a dip in the capacitance under conditions of low ionic strength. Using this model, we identify the necessary characteristics of a solvation model suitable for first-principles electrochemistry of metal surfaces in non-adsorbing, aqueous electrolytes: dielectric and ionic nonlinearity, and a dielectric-only region at the interface. The dielectric nonlinearity, caused by the saturation of dipole rotational response in water, creates the capacitance hump, while ionic nonlinearity, caused by the compactness of the diffuse layer, generates the capacitance dip seen at low ionic strength. We show that none of the previously developed solvation models simultaneously meet all these criteria. We design the nonlinear electrochemical soft-sphere solvation model which both captures the capacitance features observed experimentally and serves as a general-purpose continuum solvation model.

Recent advances in modeling and simulation of the exposure and response of tungsten to fusion energy conditions

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

Marian, Jaime; Becquart, Charlotte S.; Domain, Christophe

2017-06-09

Under the anticipated operating conditions for demonstration magnetic fusion reactors beyond ITER, structural materials will be exposed to unprecedented conditions of irradiation, heat flux, and temperature. While such extreme environments remain inaccessible experimentally, computational modeling and simulation can provide qualitative and quantitative insights into materials response and complement the available experimental measurements with carefully validated predictions. For plasma facing components such as the first wall and the divertor, tungsten (W) has been selected as the best candidate material due to its superior high-temperature and irradiation properties. In this paper we provide a review of recent efforts in computational modeling ofmore » W both as a plasma-facing material exposed to He deposition as well as a bulk structural material subjected to fast neutron irradiation. We use a multiscale modeling approach –commonly used as the materials modeling paradigm– to define the outline of the paper and highlight recent advances using several classes of techniques and their interconnection. We highlight several of the most salient findings obtained via computational modeling and point out a number of remaining challenges and future research directions« less

A Progressive Damage Model for unidirectional Fibre Reinforced Composites with Application to Impact and Penetration Simulation

NASA Astrophysics Data System (ADS)

Kerschbaum, M.; Hopmann, C.

2016-06-01

The computationally efficient simulation of the progressive damage behaviour of continuous fibre reinforced plastics is still a challenging task with currently available computer aided engineering methods. This paper presents an original approach for an energy based continuum damage model which accounts for stress-/strain nonlinearities, transverse and shear stress interaction phenomena, quasi-plastic shear strain components, strain rate effects, regularised damage evolution and consideration of load reversal effects. The physically based modelling approach enables experimental determination of all parameters on ply level to avoid expensive inverse analysis procedures. The modelling strategy, implementation and verification of this model using commercially available explicit finite element software are detailed. The model is then applied to simulate the impact and penetration of carbon fibre reinforced cross-ply specimens with variation of the impact speed. The simulation results show that the presented approach enables a good representation of the force-/displacement curves and especially well agreement with the experimentally observed fracture patterns. In addition, the mesh dependency of the results were assessed for one impact case showing only very little change of the simulation results which emphasises the general applicability of the presented method.

The ability of four strains of Streptococcus uberis to induce clinical mastitis after intramammary inoculation in lactating cows.

PubMed

Notcovich, S; deNicolo, G; Williamson, N B; Grinberg, A; Lopez-Villalobos, N; Petrovski, K R

2016-07-01

To compare the ability of four strains of Streptococcus uberis at two doses to induce clinical mastitis in lactating dairy cows after intramammary inoculation in order to evaluate their usefulness for future experimental infection models. Four field strains of S. uberis (26LB, S418, and S523 and SR115) were obtained from cows with clinical mastitis in the Wairarapa and Waikato regions of New Zealand. Twenty-four crossbred lactating cows, with no history of mastitis and absence of major pathogens following culture of milk samples, were randomly allocated to four groups (one per strain) of six cows. Each cow was infused (Day 0) in one quarter with approximately 10(4) cfu and in the contralateral quarter with approximately 10(6) cfu of the same strain. The other two quarters remained unchallenged. All four quarters were then inspected for signs of clinical mastitis, by palpation and observation of the foremilk, twice daily from Days 0-9, and composite milk samples were collected from Days 0-8 for analysis of somatic cell counts (SCC). Quarters were treated with penicillin when clinical mastitis was observed. Duplicate milk samples were collected and cultured on presentation of each clinical case and on Day 4 from challenged quarters with no clinical signs. Clinical mastitis was diagnosed in 26/48 (54%) challenged quarters. Challenge with strain S418 resulted in more cases of mastitis (12/12 quarters) than strains SR115 (7/12), 26LB (6/12) or S523 (1/12), and the mean interval from challenge to first diagnosis of mastitis was shorter for S418 than the other strains (p<0.001). The proportion of quarters from which S. uberis could be isolated after challenge was less for strain 26LB (1/6) than SR115 (6/7) (p<0.05), and SCC following challenge was lower for strain S523 than the other strains (p<0.05). There were significant differences between the strains in the proportion of quarters developing clinical mastitis, the interval to mastitis onset, SCC following challenge and the proportion of clinical cases from which S. uberis could be isolated. These results illustrate the difference in the ability of S. uberis strains to cause mastitis and the severity of the infections caused. Experimental challenge models can be used to compare infectivity and pathogenicity of different strains of mastitis-causing bacteria, the efficacy of pharmaceutical products and host-responses in a cost-effective manner.

Effect of whole yeast cell product supplementation (CitriStim®) on immune responses and cecal microflora species in pullet and layer chickens during an experimental coccidial challenge.

PubMed

Markazi, Ashley D; Perez, Victor; Sifri, Mamduh; Shanmugasundaram, Revathi; Selvaraj, Ramesh K

2017-07-01

Three separate experiments were conducted to study the effects of whole yeast cell product supplementation in pullets and layer hens. Body weight gain, fecal and intestinal coccidial oocyst counts, cecal microflora species, cytokine mRNA amounts, and CD4+ and CD8+ T-cell populations in the cecal tonsils were analyzed following an experimental coccidial infection. In Experiment I, day-old Leghorn layer chicks were fed 3 experimental diets with 0, 0.1, or 0.2% whole yeast cell product (CitriStim®, ADM, Decatur, IL). At 21 d of age, birds were challenged with 1 × 105 live coccidial oocysts. Supplementation with whole yeast cell product decreased the fecal coccidial oocyst count at 7 (P = 0.05) and 8 (P < 0.01) d post-challenge. In Experiment II, 27-week old Leghorn layer hens were fed 3 experimental diets with 0, 0.05 or 0.1% whole yeast cell product and challenged with 1 × 105 live coccidial oocysts on d 25 of whole yeast cell product feeding. Supplementation with whole yeast cell product decreased the coccidial oocyst count in the intestinal content (P < 0.01) at 5, 13, and 38 d post-coccidial challenge. Supplementation with whole yeast cell product increased relative proportion of Lactobacillus (P < 0.01) in the cecal tonsils 13 d post-coccidial challenge. Supplementation with whole yeast cell product decreased CD8+ T cell percentages (P < 0.05) in the cecal tonsils at 5 d post-coccidial challenge. In Experiment III, 32-week-old Leghorn layer hens were fed 3 experimental diets with 0, 0.1, or 0.2% whole yeast cell product and challenged with 1 × 105 live coccidial oocysts on d 66 of whole yeast cell product feeding. At 5 d post-coccidial challenge, whole yeast cell product supplementation down-regulated (P = 0.01) IL-10 mRNA amount. It could be concluded that supplementing whole yeast cell product can help minimize coccidial infection in both growing pullets and layer chickens. © 2017 Poultry Science Association Inc.

Adaptive optimal input design and parametric estimation of nonlinear dynamical systems: application to neuronal modeling.

PubMed

Madi, Mahmoud K; Karameh, Fadi N

2018-05-11

Many physical models of biological processes including neural systems are characterized by parametric nonlinear dynamical relations between driving inputs, internal states, and measured outputs of the process. Fitting such models using experimental data (data assimilation) is a challenging task since the physical process often operates in a noisy, possibly non-stationary environment; moreover, conducting multiple experiments under controlled and repeatable conditions can be impractical, time consuming or costly. The accuracy of model identification, therefore, is dictated principally by the quality and dynamic richness of collected data over single or few experimental sessions. Accordingly, it is highly desirable to design efficient experiments that, by exciting the physical process with smart inputs, yields fast convergence and increased accuracy of the model. We herein introduce an adaptive framework in which optimal input design is integrated with Square root Cubature Kalman Filters (OID-SCKF) to develop an online estimation procedure that first, converges significantly quicker, thereby permitting model fitting over shorter time windows, and second, enhances model accuracy when only few process outputs are accessible. The methodology is demonstrated on common nonlinear models and on a four-area neural mass model with noisy and limited measurements. Estimation quality (speed and accuracy) is benchmarked against high-performance SCKF-based methods that commonly employ dynamically rich informed inputs for accurate model identification. For all the tested models, simulated single-trial and ensemble averages showed that OID-SCKF exhibited (i) faster convergence of parameter estimates and (ii) lower dependence on inter-trial noise variability with gains up to around 1000 msec in speed and 81% increase in variability for the neural mass models. In terms of accuracy, OID-SCKF estimation was superior, and exhibited considerably less variability across experiments, in identifying model parameters of (a) systems with challenging model inversion dynamics and (b) systems with fewer measurable outputs that directly relate to the underlying processes. Fast and accurate identification therefore carries particular promise for modeling of transient (short-lived) neuronal network dynamics using a spatially under-sampled set of noisy measurements, as is commonly encountered in neural engineering applications. © 2018 IOP Publishing Ltd.

A novel phenomenological model for dynamic behavior of magnetorheological elastomers in tension-compression mode

NASA Astrophysics Data System (ADS)

Vatandoost, Hossein; Norouzi, Mahmood; Masoud Sajjadi Alehashem, Seyed; Smoukov, Stoyan K.

2017-06-01

Tension-compression operation in MR elastomers (MREs) offers both the most compact design and superior stiffness in many vertical load-bearing applications, such as MRE bearing isolators in bridges and buildings, suspension systems and engine mounts in cars, and vibration control equipment. It suffers, however, from lack of good computational models to predict device performance, and as a result shear-mode MREs are widely used in the industry, despite their low stiffness and load-bearing capacity. We start with a comprehensive review of modeling of MREs and their dynamic characteristics, showing previous studies have mostly focused on dynamic behavior of MREs in shear mode, though the MRE strength and MR effect are greatly decreased at high strain amplitudes, due to increasing distance between the magnetic particles. Moreover, the characteristic parameters of the current models assume either frequency, or strain, or magnetic field are constant; hence, new model parameters must be recalculated for new loading conditions. This is an experimentally time consuming and computationally expensive task, and no models capture the full dynamic behavior of the MREs at all loading conditions. In this study, we present an experimental setup to test MREs in a coupled tension-compression mode, as well as a novel phenomenological model which fully predicts the stress-strain material behavior as a function of magnetic flux density, loading frequency and strain. We use a training set of experiments to find the experimentally derived model parameters, from which can predict by interpolation the MRE behavior in a relatively large continuous range of frequency, strain and magnetic field. We also challenge the model to make extrapolating predictions and compare to additional experiments outside the training experimental data set with good agreement. Further development of this model would allow design and control of engineering structures equipped with tension-compression MREs and all the advantages they offer.

Overview of the Aeroelastic Prediction Workshop

NASA Technical Reports Server (NTRS)

Heeg, Jennifer; Chwalowski, Pawel; Florance, Jennifer P.; Wieseman, Carol D.; Schuster, David M.; Perry, Raleigh B.

2013-01-01

The Aeroelastic Prediction Workshop brought together an international community of computational fluid dynamicists as a step in defining the state of the art in computational aeroelasticity. This workshop's technical focus was prediction of unsteady pressure distributions resulting from forced motion, benchmarking the results first using unforced system data. The most challenging aspects of the physics were identified as capturing oscillatory shock behavior, dynamic shock-induced separated flow and tunnel wall boundary layer influences. The majority of the participants used unsteady Reynolds-averaged Navier Stokes codes. These codes were exercised at transonic Mach numbers for three configurations and comparisons were made with existing experimental data. Substantial variations were observed among the computational solutions as well as differences relative to the experimental data. Contributing issues to these differences include wall effects and wall modeling, non-standardized convergence criteria, inclusion of static aeroelastic deflection, methodology for oscillatory solutions, post-processing methods. Contributing issues pertaining principally to the experimental data sets include the position of the model relative to the tunnel wall, splitter plate size, wind tunnel expansion slot configuration, spacing and location of pressure instrumentation, and data processing methods.

Histologic scoring of gastritis and gastric cancer in mouse models.

PubMed

Rogers, Arlin B

2012-01-01

Histopathology is a defining endpoint in mouse models of experimental gastritis and gastric adenocarcinoma. Presented here is an overview of the histology of gastritis and gastric cancer in mice experimentally infected with Helicobacter pylori or H. felis. A modular histopathologic scoring scheme is provided that incorporates relevant disease-associated changes. Whereas the guide uses Helicobacter infection as the prototype challenge, features may be applied to chemical and genetically engineered mouse models of stomach cancer as well. Specific criteria included in the combined gastric histologic activity index (HAI) include inflammation, epithelial defects, oxyntic atrophy, hyperplasia, pseudopyloric metaplasia, and dysplasia or neoplasia. Representative photomicrographs accompany descriptions for each lesion grade. Differentiation of genuine tumor invasion from pseudoinvasion is highlighted. A brief comparison of normal rodent versus human stomach anatomy and physiology is accompanied by an introduction to mouse-specific lesions including mucous metaplasia and eosinophilic droplets (hyalinosis). In conjunction with qualified pathology support, this guide is intended to assist research scientists, postdoctoral fellows, graduate students, and medical professionals from affiliated disciplines in the interpretation and histologic grading of chronic gastritis and gastric carcinoma in mouse models.

Ultrafast Three-Dimensional Integrated Imaging of Strain in Core/Shell Semiconductor/Metal Nanostructures

DOE PAGES

Cherukara, Mathew J.; Sasikumar, Kiran; DiChiara, Anthony; ...

2017-11-07

Visualizing the dynamical response of material heterointerfaces is increasingly important for the design of hybrid materials and structures with tailored properties for use in functional devices. In situ characterization of nanoscale heterointerfaces such as metal-semiconductor interfaces, which exhibit a complex interplay between lattice strain, electric potential, and heat transport at subnanosecond time scales, is particularly challenging. Here in this work, we use a laser pump/X-ray probe form of Bragg coherent diffraction imaging (BCDI) to visualize in three-dimension the deformation of the core of a model core/shell semiconductor-metal (ZnO/Ni) nanorod following laser heating of the shell. We observe a rich interplaymore » of radial, axial, and shear deformation modes acting at different time scales that are induced by the strain from the Ni shell. We construct experimentally informed models by directly importing the reconstructed crystal from the ultrafast experiment into a thermo-electromechanical continuum model. The model elucidates the origin of the deformation modes observed experimentally. Our integrated imaging approach represents an invaluable tool to probe strain dynamics across mixed interfaces under operando conditions.« less

Continued Development and Validation of Methods for Spheromak Simulation

NASA Astrophysics Data System (ADS)

Benedett, Thomas

2015-11-01

The HIT-SI experiment has demonstrated stable sustainment of spheromaks; determining how the underlying physics extrapolate to larger, higher-temperature regimes is of prime importance in determining the viability of the inductively-driven spheromak. It is thus prudent to develop and validate a computational model that can be used to study current results and provide an intermediate step between theory and future experiments. A zero-beta Hall-MHD model has shown good agreement with experimental data at 14.5 kHz injector operation. Experimental observations at higher frequency, where the best performance is achieved, indicate pressure effects are important and likely required to attain quantitative agreement with simulations. Efforts to extend the existing validation to high frequency (~ 36-68 kHz) using an extended MHD model implemented in the PSI-TET arbitrary-geometry 3D MHD code will be presented. Results from verification of the PSI-TET extended MHD model using the GEM magnetic reconnection challenge will also be presented along with investigation of injector configurations for future SIHI experiments using Taylor state equilibrium calculations. Work supported by DoE.

CalFitter: a web server for analysis of protein thermal denaturation data.

PubMed

Mazurenko, Stanislav; Stourac, Jan; Kunka, Antonin; Nedeljkovic, Sava; Bednar, David; Prokop, Zbynek; Damborsky, Jiri

2018-05-14

Despite significant advances in the understanding of protein structure-function relationships, revealing protein folding pathways still poses a challenge due to a limited number of relevant experimental tools. Widely-used experimental techniques, such as calorimetry or spectroscopy, critically depend on a proper data analysis. Currently, there are only separate data analysis tools available for each type of experiment with a limited model selection. To address this problem, we have developed the CalFitter web server to be a unified platform for comprehensive data fitting and analysis of protein thermal denaturation data. The server allows simultaneous global data fitting using any combination of input data types and offers 12 protein unfolding pathway models for selection, including irreversible transitions often missing from other tools. The data fitting produces optimal parameter values, their confidence intervals, and statistical information to define unfolding pathways. The server provides an interactive and easy-to-use interface that allows users to directly analyse input datasets and simulate modelled output based on the model parameters. CalFitter web server is available free at https://loschmidt.chemi.muni.cz/calfitter/.

Autophagy in Dictyostelium: Mechanisms, regulation and disease in a simple biomedical model.

PubMed

Mesquita, Ana; Cardenal-Muñoz, Elena; Dominguez, Eunice; Muñoz-Braceras, Sandra; Nuñez-Corcuera, Beatriz; Phillips, Ben A; Tábara, Luis C; Xiong, Qiuhong; Coria, Roberto; Eichinger, Ludwig; Golstein, Pierre; King, Jason S; Soldati, Thierry; Vincent, Olivier; Escalante, Ricardo

2017-01-02

Autophagy is a fast-moving field with an enormous impact on human health and disease. Understanding the complexity of the mechanism and regulation of this process often benefits from the use of simple experimental models such as the social amoeba Dictyostelium discoideum. Since the publication of the first review describing the potential of D. discoideum in autophagy, significant advances have been made that demonstrate both the experimental advantages and interest in using this model. Since our previous review, research in D. discoideum has shed light on the mechanisms that regulate autophagosome formation and contributed significantly to the study of autophagy-related pathologies. Here, we review these advances, as well as the current techniques to monitor autophagy in D. discoideum. The comprehensive bioinformatics search of autophagic proteins that was a substantial part of the previous review has not been revisited here except for those aspects that challenged previous predictions such as the composition of the Atg1 complex. In recent years our understanding of, and ability to investigate, autophagy in D. discoideum has evolved significantly and will surely enable and accelerate future research using this model.

Ultrafast Three-Dimensional Integrated Imaging of Strain in Core/Shell Semiconductor/Metal Nanostructures

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

Cherukara, Mathew J.; Sasikumar, Kiran; DiChiara, Anthony

Visualizing the dynamical response of material heterointerfaces is increasingly important for the design of hybrid materials and structures with tailored properties for use in functional devices. In situ characterization of nanoscale heterointerfaces such as metal-semiconductor interfaces, which exhibit a complex interplay between lattice strain, electric potential, and heat transport at subnanosecond time scales, is particularly challenging. Here in this work, we use a laser pump/X-ray probe form of Bragg coherent diffraction imaging (BCDI) to visualize in three-dimension the deformation of the core of a model core/shell semiconductor-metal (ZnO/Ni) nanorod following laser heating of the shell. We observe a rich interplaymore » of radial, axial, and shear deformation modes acting at different time scales that are induced by the strain from the Ni shell. We construct experimentally informed models by directly importing the reconstructed crystal from the ultrafast experiment into a thermo-electromechanical continuum model. The model elucidates the origin of the deformation modes observed experimentally. Our integrated imaging approach represents an invaluable tool to probe strain dynamics across mixed interfaces under operando conditions.« less

Ultrafast Three-Dimensional Integrated Imaging of Strain in Core/Shell Semiconductor/Metal Nanostructures.

PubMed

Cherukara, Mathew J; Sasikumar, Kiran; DiChiara, Anthony; Leake, Steven J; Cha, Wonsuk; Dufresne, Eric M; Peterka, Tom; McNulty, Ian; Walko, Donald A; Wen, Haidan; Sankaranarayanan, Subramanian K R S; Harder, Ross J

2017-12-13

Visualizing the dynamical response of material heterointerfaces is increasingly important for the design of hybrid materials and structures with tailored properties for use in functional devices. In situ characterization of nanoscale heterointerfaces such as metal-semiconductor interfaces, which exhibit a complex interplay between lattice strain, electric potential, and heat transport at subnanosecond time scales, is particularly challenging. In this work, we use a laser pump/X-ray probe form of Bragg coherent diffraction imaging (BCDI) to visualize in three-dimension the deformation of the core of a model core/shell semiconductor-metal (ZnO/Ni) nanorod following laser heating of the shell. We observe a rich interplay of radial, axial, and shear deformation modes acting at different time scales that are induced by the strain from the Ni shell. We construct experimentally informed models by directly importing the reconstructed crystal from the ultrafast experiment into a thermo-electromechanical continuum model. The model elucidates the origin of the deformation modes observed experimentally. Our integrated imaging approach represents an invaluable tool to probe strain dynamics across mixed interfaces under operando conditions.

Target Capturing Control for Space Robots with Unknown Mass Properties: A Self-Tuning Method Based on Gyros and Cameras.

PubMed

Li, Zhenyu; Wang, Bin; Liu, Hong

2016-08-30

Satellite capturing with free-floating space robots is still a challenging task due to the non-fixed base and unknown mass property issues. In this paper gyro and eye-in-hand camera data are adopted as an alternative choice for solving this problem. For this improved system, a new modeling approach that reduces the complexity of system control and identification is proposed. With the newly developed model, the space robot is equivalent to a ground-fixed manipulator system. Accordingly, a self-tuning control scheme is applied to handle such a control problem including unknown parameters. To determine the controller parameters, an estimator is designed based on the least-squares technique for identifying the unknown mass properties in real time. The proposed method is tested with a credible 3-dimensional ground verification experimental system, and the experimental results confirm the effectiveness of the proposed control scheme.

Target Capturing Control for Space Robots with Unknown Mass Properties: A Self-Tuning Method Based on Gyros and Cameras

PubMed Central

Li, Zhenyu; Wang, Bin; Liu, Hong

2016-01-01

Satellite capturing with free-floating space robots is still a challenging task due to the non-fixed base and unknown mass property issues. In this paper gyro and eye-in-hand camera data are adopted as an alternative choice for solving this problem. For this improved system, a new modeling approach that reduces the complexity of system control and identification is proposed. With the newly developed model, the space robot is equivalent to a ground-fixed manipulator system. Accordingly, a self-tuning control scheme is applied to handle such a control problem including unknown parameters. To determine the controller parameters, an estimator is designed based on the least-squares technique for identifying the unknown mass properties in real time. The proposed method is tested with a credible 3-dimensional ground verification experimental system, and the experimental results confirm the effectiveness of the proposed control scheme. PMID:27589748

Bioinformatics and molecular modeling in glycobiology

PubMed Central

Schloissnig, Siegfried

2010-01-01

The field of glycobiology is concerned with the study of the structure, properties, and biological functions of the family of biomolecules called carbohydrates. Bioinformatics for glycobiology is a particularly challenging field, because carbohydrates exhibit a high structural diversity and their chains are often branched. Significant improvements in experimental analytical methods over recent years have led to a tremendous increase in the amount of carbohydrate structure data generated. Consequently, the availability of databases and tools to store, retrieve and analyze these data in an efficient way is of fundamental importance to progress in glycobiology. In this review, the various graphical representations and sequence formats of carbohydrates are introduced, and an overview of newly developed databases, the latest developments in sequence alignment and data mining, and tools to support experimental glycan analysis are presented. Finally, the field of structural glycoinformatics and molecular modeling of carbohydrates, glycoproteins, and protein–carbohydrate interaction are reviewed. PMID:20364395

Anomalous Diffusion of Single Particles in Cytoplasm

PubMed Central

Regner, Benjamin M.; Vučinić, Dejan; Domnisoru, Cristina; Bartol, Thomas M.; Hetzer, Martin W.; Tartakovsky, Daniel M.; Sejnowski, Terrence J.

2013-01-01

The crowded intracellular environment poses a formidable challenge to experimental and theoretical analyses of intracellular transport mechanisms. Our measurements of single-particle trajectories in cytoplasm and their random-walk interpretations elucidate two of these mechanisms: molecular diffusion in crowded environments and cytoskeletal transport along microtubules. We employed acousto-optic deflector microscopy to map out the three-dimensional trajectories of microspheres migrating in the cytosolic fraction of a cellular extract. Classical Brownian motion (BM), continuous time random walk, and fractional BM were alternatively used to represent these trajectories. The comparison of the experimental and numerical data demonstrates that cytoskeletal transport along microtubules and diffusion in the cytosolic fraction exhibit anomalous (nonFickian) behavior and posses statistically distinct signatures. Among the three random-walk models used, continuous time random walk provides the best representation of diffusion, whereas microtubular transport is accurately modeled with fractional BM. PMID:23601312

Enhanced ICP for the Registration of Large-Scale 3D Environment Models: An Experimental Study

PubMed Central

Han, Jianda; Yin, Peng; He, Yuqing; Gu, Feng

2016-01-01

One of the main applications of mobile robots is the large-scale perception of the outdoor environment. One of the main challenges of this application is fusing environmental data obtained by multiple robots, especially heterogeneous robots. This paper proposes an enhanced iterative closest point (ICP) method for the fast and accurate registration of 3D environmental models. First, a hierarchical searching scheme is combined with the octree-based ICP algorithm. Second, an early-warning mechanism is used to perceive the local minimum problem. Third, a heuristic escape scheme based on sampled potential transformation vectors is used to avoid local minima and achieve optimal registration. Experiments involving one unmanned aerial vehicle and one unmanned surface vehicle were conducted to verify the proposed technique. The experimental results were compared with those of normal ICP registration algorithms to demonstrate the superior performance of the proposed method. PMID:26891298

Dependence of the Radiation Pressure on the Background Refractive Index

NASA Astrophysics Data System (ADS)

Webb, Kevin J.

2013-07-01

The 1978 experiments by Jones and Leslie showing that the radiation pressure on a mirror depends on the background medium refractive index have yet to be adequately explained using a force model and have provided a leading challenge to the Abraham form of the electromagnetic momentum. Those experimental results are predicted for the first time using a force representation that incorporates the Abraham momentum by utilizing the power calibration method employed in the Jones and Leslie experiments. With an extension of the same procedure, the polarization and angle independence of the experimental data are also explained by this model. Prospects are good for this general form of the electromagnetic force density to be effective in predicting other experiments with macroscopic materials. Furthermore, the rigorous representation of material dispersion makes the representation important for metamaterials that operate in the vicinity of homogenized material resonances.

Finite element simulation and experimental verification of ultrasonic non-destructive inspection of defects in additively manufactured materials

NASA Astrophysics Data System (ADS)

Taheri, H.; Koester, L.; Bigelow, T.; Bond, L. J.

2018-04-01

Industrial applications of additively manufactured components are increasing quickly. Adequate quality control of the parts is necessary in ensuring safety when using these materials. Base material properties, surface conditions, as well as location and size of defects are some of the main targets for nondestructive evaluation of additively manufactured parts, and the problem of adequate characterization is compounded given the challenges of complex part geometry. Numerical modeling can allow the interplay of the various factors to be studied, which can lead to improved measurement design. This paper presents a finite element simulation verified by experimental results of ultrasonic waves scattering from flat bottom holes (FBH) in additive manufacturing materials. A focused beam immersion ultrasound transducer was used for both the modeling and simulations in the additive manufactured samples. The samples were SS17 4 PH steel samples made by laser sintering in a powder bed.

A linear triple quantum dot system in isolated configuration

NASA Astrophysics Data System (ADS)

Flentje, Hanno; Bertrand, Benoit; Mortemousque, Pierre-André; Thiney, Vivien; Ludwig, Arne; Wieck, Andreas D.; Bäuerle, Christopher; Meunier, Tristan

2017-06-01

The scaling up of electron spin qubit based nanocircuits has remained challenging up till date and involves the development of efficient charge control strategies. Here, we report on the experimental realization of a linear triple quantum dot in a regime isolated from the reservoir. We show how this regime can be reached with a fixed number of electrons. Charge stability diagrams of the one, two, and three electron configurations where only electron exchange between the dots is allowed are observed. They are modeled with the established theory based on a capacitive model of the dot systems. The advantages of the isolated regime with respect to experimental realizations of quantum simulators and qubits are discussed. We envision that the results presented here will make more manipulation schemes for existing qubit implementations possible and will ultimately allow to increase the number of tunnel coupled quantum dots which can be simultaneously controlled.

Emergence of coherence and the dynamics of quantum phase transitions

PubMed Central

Braun, Simon; Friesdorf, Mathis; Hodgman, Sean S.; Schreiber, Michael; Ronzheimer, Jens Philipp; Riera, Arnau; del Rey, Marco; Bloch, Immanuel; Eisert, Jens

2015-01-01

The dynamics of quantum phase transitions pose one of the most challenging problems in modern many-body physics. Here, we study a prototypical example in a clean and well-controlled ultracold atom setup by observing the emergence of coherence when crossing the Mott insulator to superfluid quantum phase transition. In the 1D Bose–Hubbard model, we find perfect agreement between experimental observations and numerical simulations for the resulting coherence length. We, thereby, perform a largely certified analog quantum simulation of this strongly correlated system reaching beyond the regime of free quasiparticles. Experimentally, we additionally explore the emergence of coherence in higher dimensions, where no classical simulations are available, as well as for negative temperatures. For intermediate quench velocities, we observe a power-law behavior of the coherence length, reminiscent of the Kibble–Zurek mechanism. However, we find nonuniversal exponents that cannot be captured by this mechanism or any other known model. PMID:25775515

A computational modeling approach for the characterization of mechanical properties of 3D alginate tissue scaffolds.

PubMed

Nair, K; Yan, K C; Sun, W

2008-01-01

Scaffold guided tissue engineering is an innovative approach wherein cells are seeded onto biocompatible and biodegradable materials to form 3-dimensional (3D) constructs that, when implanted in the body facilitate the regeneration of tissue. Tissue scaffolds act as artificial extracellular matrix providing the environment conducive for tissue growth. Characterization of scaffold properties is necessary to understand better the underlying processes involved in controlling cell behavior and formation of functional tissue. We report a computational modeling approach to characterize mechanical properties of 3D gellike biomaterial, specifically, 3D alginate scaffold encapsulated with cells. Alginate inherent nonlinearity and variations arising from minute changes in its concentration and viscosity make experimental evaluation of its mechanical properties a challenging and time consuming task. We developed an in silico model to determine the stress-strain relationship of alginate based scaffolds from experimental data. In particular, we compared the Ogden hyperelastic model to other hyperelastic material models and determined that this model was the most suitable to characterize the nonlinear behavior of alginate. We further propose a mathematical model that represents the alginate material constants in Ogden model as a function of concentrations and viscosity. This study demonstrates the model capability to predict mechanical properties of 3D alginate scaffolds.

Toward Personalized Control of Human Gut Bacterial Communities.

PubMed

David, Lawrence A

2018-01-01

A key challenge in microbiology will be developing tools for manipulating human gut bacterial communities. Our ability to predict and control the dynamics of these communities is now in its infancy. To manage human gut microbiota, I am developing methods in three research domains. First, I am refining in vitro tools to experimentally study gut microbes at high throughput and in controlled settings. Second, I am adapting "big data" techniques to overcome statistical challenges confronting microbiota modeling. Third, I am testing study designs that can streamline human testing of microbiota manipulations. Assembling these methods creates new challenges, including training scientists who can work across disciplines such as engineering, ecology, and medicine. Nevertheless, I envision that overcoming these obstacles will enable my group to construct platforms that can personalize microbiota treatments, particularly ones based on diet. More broadly, I anticipate that such platforms will have applications across fields such as agriculture, biotechnology, and environmental management.

A Structured Career Intervention Program for Academically Challenged Students

ERIC Educational Resources Information Center

Salleh, Amla; Abdullah, Syed Mohamad; Mahmud, Zuria; Ghavifekr, Simin; Ishak, Noriah

2013-01-01

A study was carried out to test the effects of a 2-week structured intervention program on academically challenged students' career development. A quasi-experimental study was designed using pre-tests, post-tests, and a control group approach to examine the effects of the intervention program. Data were collected from both the experimental and…

Network based approaches reveal clustering in protein point patterns

NASA Astrophysics Data System (ADS)

Parker, Joshua; Barr, Valarie; Aldridge, Joshua; Samelson, Lawrence E.; Losert, Wolfgang

2014-03-01

Recent advances in super-resolution imaging have allowed for the sub-diffraction measurement of the spatial location of proteins on the surfaces of T-cells. The challenge is to connect these complex point patterns to the internal processes and interactions, both protein-protein and protein-membrane. We begin analyzing these patterns by forming a geometric network amongst the proteins and looking at network measures, such the degree distribution. This allows us to compare experimentally observed patterns to models. Specifically, we find that the experimental patterns differ from heterogeneous Poisson processes, highlighting an internal clustering structure. Further work will be to compare our results to simulated protein-protein interactions to determine clustering mechanisms.

Angular velocity estimation from measurement vectors of star tracker.

PubMed

Liu, Hai-bo; Yang, Jun-cai; Yi, Wen-jun; Wang, Jiong-qi; Yang, Jian-kun; Li, Xiu-jian; Tan, Ji-chun

2012-06-01

In most spacecraft, there is a need to know the craft's angular rate. Approaches with least squares and an adaptive Kalman filter are proposed for estimating the angular rate directly from the star tracker measurements. In these approaches, only knowledge of the vector measurements and sampling interval is required. The designed adaptive Kalman filter can filter out noise without information of the dynamic model and inertia dyadic. To verify the proposed estimation approaches, simulations based on the orbit data of the challenging minisatellite payload (CHAMP) satellite and experimental tests with night-sky observation are performed. Both the simulations and experimental testing results have demonstrated that the proposed approach performs well in terms of accuracy, robustness, and performance.

Gravity sensing, a largely misunderstood trigger of plant orientated growth.

PubMed

Lopez, David; Tocquard, Kévin; Venisse, Jean-Stéphane; Legué, Valerie; Roeckel-Drevet, Patricia

2014-01-01

Gravity is a crucial environmental factor regulating plant growth and development. Plants have the ability to sense a change in the direction of gravity, which leads to the re-orientation of their growth direction, so-called gravitropism. In general, plant stems grow upward (negative gravitropism), whereas roots grow downward (positive gravitropism). Models describing the gravitropic response following the tilting of plants are presented and highlight that gravitropic curvature involves both gravisensing and mechanosensing, thus allowing to revisit experimental data. We also discuss the challenge to set up experimental designs for discriminating between gravisensing and mechanosensing. We then present the cellular events and the molecular actors known to be specifically involved in gravity sensing.

Preclinical magnetic resonance imaging and systems biology in cancer research: current applications and challenges.

PubMed

Albanese, Chris; Rodriguez, Olga C; VanMeter, John; Fricke, Stanley T; Rood, Brian R; Lee, YiChien; Wang, Sean S; Madhavan, Subha; Gusev, Yuriy; Petricoin, Emanuel F; Wang, Yue

2013-02-01

Biologically accurate mouse models of human cancer have become important tools for the study of human disease. The anatomical location of various target organs, such as brain, pancreas, and prostate, makes determination of disease status difficult. Imaging modalities, such as magnetic resonance imaging, can greatly enhance diagnosis, and longitudinal imaging of tumor progression is an important source of experimental data. Even in models where the tumors arise in areas that permit visual determination of tumorigenesis, longitudinal anatomical and functional imaging can enhance the scope of studies by facilitating the assessment of biological alterations, (such as changes in angiogenesis, metabolism, cellular invasion) as well as tissue perfusion and diffusion. One of the challenges in preclinical imaging is the development of infrastructural platforms required for integrating in vivo imaging and therapeutic response data with ex vivo pathological and molecular data using a more systems-based multiscale modeling approach. Further challenges exist in integrating these data for computational modeling to better understand the pathobiology of cancer and to better affect its cure. We review the current applications of preclinical imaging and discuss the implications of applying functional imaging to visualize cancer progression and treatment. Finally, we provide new data from an ongoing preclinical drug study demonstrating how multiscale modeling can lead to a more comprehensive understanding of cancer biology and therapy. Copyright © 2013 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Collaborative simulations and experiments for a novel yield model of coal devolatilization in oxy-coal combustion conditions

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

Iavarone, Salvatore; Smith, Sean T.; Smith, Philip J.

Oxy-coal combustion is an emerging low-cost “clean coal” technology for emissions reduction and Carbon Capture and Sequestration (CCS). The use of Computational Fluid Dynamics (CFD) tools is crucial for the development of cost-effective oxy-fuel technologies and the minimization of environmental concerns at industrial scale. The coupling of detailed chemistry models and CFD simulations is still challenging, especially for large-scale plants, because of the high computational efforts required. The development of scale-bridging models is therefore necessary, to find a good compromise between computational efforts and the physical-chemical modeling precision. This paper presents a procedure for scale-bridging modeling of coal devolatilization, inmore » the presence of experimental error, that puts emphasis on the thermodynamic aspect of devolatilization, namely the final volatile yield of coal, rather than kinetics. The procedure consists of an engineering approach based on dataset consistency and Bayesian methodology including Gaussian-Process Regression (GPR). Experimental data from devolatilization tests carried out in an oxy-coal entrained flow reactor were considered and CFD simulations of the reactor were performed. Jointly evaluating experiments and simulations, a novel yield model was validated against the data via consistency analysis. In parallel, a Gaussian-Process Regression was performed, to improve the understanding of the uncertainty associated to the devolatilization, based on the experimental measurements. Potential model forms that could predict yield during devolatilization were obtained. The set of model forms obtained via GPR includes the yield model that was proven to be consistent with the data. Finally, the overall procedure has resulted in a novel yield model for coal devolatilization and in a valuable evaluation of uncertainty in the data, in the model form, and in the model parameters.« less

Collaborative simulations and experiments for a novel yield model of coal devolatilization in oxy-coal combustion conditions

DOE PAGES

Iavarone, Salvatore; Smith, Sean T.; Smith, Philip J.; ...

2017-06-03

Oxy-coal combustion is an emerging low-cost “clean coal” technology for emissions reduction and Carbon Capture and Sequestration (CCS). The use of Computational Fluid Dynamics (CFD) tools is crucial for the development of cost-effective oxy-fuel technologies and the minimization of environmental concerns at industrial scale. The coupling of detailed chemistry models and CFD simulations is still challenging, especially for large-scale plants, because of the high computational efforts required. The development of scale-bridging models is therefore necessary, to find a good compromise between computational efforts and the physical-chemical modeling precision. This paper presents a procedure for scale-bridging modeling of coal devolatilization, inmore » the presence of experimental error, that puts emphasis on the thermodynamic aspect of devolatilization, namely the final volatile yield of coal, rather than kinetics. The procedure consists of an engineering approach based on dataset consistency and Bayesian methodology including Gaussian-Process Regression (GPR). Experimental data from devolatilization tests carried out in an oxy-coal entrained flow reactor were considered and CFD simulations of the reactor were performed. Jointly evaluating experiments and simulations, a novel yield model was validated against the data via consistency analysis. In parallel, a Gaussian-Process Regression was performed, to improve the understanding of the uncertainty associated to the devolatilization, based on the experimental measurements. Potential model forms that could predict yield during devolatilization were obtained. The set of model forms obtained via GPR includes the yield model that was proven to be consistent with the data. Finally, the overall procedure has resulted in a novel yield model for coal devolatilization and in a valuable evaluation of uncertainty in the data, in the model form, and in the model parameters.« less

An efficient and stable hydrodynamic model with novel source term discretization schemes for overland flow and flood simulations

NASA Astrophysics Data System (ADS)

Xia, Xilin; Liang, Qiuhua; Ming, Xiaodong; Hou, Jingming

2017-05-01

Numerical models solving the full 2-D shallow water equations (SWEs) have been increasingly used to simulate overland flows and better understand the transient flow dynamics of flash floods in a catchment. However, there still exist key challenges that have not yet been resolved for the development of fully dynamic overland flow models, related to (1) the difficulty of maintaining numerical stability and accuracy in the limit of disappearing water depth and (2) inaccurate estimation of velocities and discharges on slopes as a result of strong nonlinearity of friction terms. This paper aims to tackle these key research challenges and present a new numerical scheme for accurately and efficiently modeling large-scale transient overland flows over complex terrains. The proposed scheme features a novel surface reconstruction method (SRM) to correctly compute slope source terms and maintain numerical stability at small water depth, and a new implicit discretization method to handle the highly nonlinear friction terms. The resulting shallow water overland flow model is first validated against analytical and experimental test cases and then applied to simulate a hypothetic rainfall event in the 42 km2 Haltwhistle Burn, UK.

Translational Rodent Models for Research on Parasitic Protozoa—A Review of Confounders and Possibilities

PubMed Central

Ehret, Totta; Torelli, Francesca; Klotz, Christian; Pedersen, Amy B.; Seeber, Frank

2017-01-01

Rodents, in particular Mus musculus, have a long and invaluable history as models for human diseases in biomedical research, although their translational value has been challenged in a number of cases. We provide some examples in which rodents have been suboptimal as models for human biology and discuss confounders which influence experiments and may explain some of the misleading results. Infections of rodents with protozoan parasites are no exception in requiring close consideration upon model choice. We focus on the significant differences between inbred, outbred and wild animals, and the importance of factors such as microbiota, which are gaining attention as crucial variables in infection experiments. Frequently, mouse or rat models are chosen for convenience, e.g., availability in the institution rather than on an unbiased evaluation of whether they provide the answer to a given question. Apart from a general discussion on translational success or failure, we provide examples where infections with single-celled parasites in a chosen lab rodent gave contradictory or misleading results, and when possible discuss the reason for this. We present emerging alternatives to traditional rodent models, such as humanized mice and organoid primary cell cultures. So-called recombinant inbred strains such as the Collaborative Cross collection are also a potential solution for certain challenges. In addition, we emphasize the advantages of using wild rodents for certain immunological, ecological, and/or behavioral questions. The experimental challenges (e.g., availability of species-specific reagents) that come with the use of such non-model systems are also discussed. Our intention is to foster critical judgment of both traditional and newly available translational rodent models for research on parasitic protozoa that can complement the existing mouse and rat models. PMID:28638807

Translational Rodent Models for Research on Parasitic Protozoa-A Review of Confounders and Possibilities.

PubMed

Ehret, Totta; Torelli, Francesca; Klotz, Christian; Pedersen, Amy B; Seeber, Frank

2017-01-01

Rodents, in particular Mus musculus , have a long and invaluable history as models for human diseases in biomedical research, although their translational value has been challenged in a number of cases. We provide some examples in which rodents have been suboptimal as models for human biology and discuss confounders which influence experiments and may explain some of the misleading results. Infections of rodents with protozoan parasites are no exception in requiring close consideration upon model choice. We focus on the significant differences between inbred, outbred and wild animals, and the importance of factors such as microbiota, which are gaining attention as crucial variables in infection experiments. Frequently, mouse or rat models are chosen for convenience, e.g., availability in the institution rather than on an unbiased evaluation of whether they provide the answer to a given question. Apart from a general discussion on translational success or failure, we provide examples where infections with single-celled parasites in a chosen lab rodent gave contradictory or misleading results, and when possible discuss the reason for this. We present emerging alternatives to traditional rodent models, such as humanized mice and organoid primary cell cultures. So-called recombinant inbred strains such as the Collaborative Cross collection are also a potential solution for certain challenges. In addition, we emphasize the advantages of using wild rodents for certain immunological, ecological, and/or behavioral questions. The experimental challenges (e.g., availability of species-specific reagents) that come with the use of such non-model systems are also discussed. Our intention is to foster critical judgment of both traditional and newly available translational rodent models for research on parasitic protozoa that can complement the existing mouse and rat models.

Analysis and experimental kinematics of a skid-steering wheeled robot based on a laser scanner sensor.

PubMed

Wang, Tianmiao; Wu, Yao; Liang, Jianhong; Han, Chenhao; Chen, Jiao; Zhao, Qiteng

2015-04-24

Skid-steering mobile robots are widely used because of their simple mechanism and robustness. However, due to the complex wheel-ground interactions and the kinematic constraints, it is a challenge to understand the kinematics and dynamics of such a robotic platform. In this paper, we develop an analysis and experimental kinematic scheme for a skid-steering wheeled vehicle based-on a laser scanner sensor. The kinematics model is established based on the boundedness of the instantaneous centers of rotation (ICR) of treads on the 2D motion plane. The kinematic parameters (the ICR coefficient , the path curvature variable and robot speed ), including the effect of vehicle dynamics, are introduced to describe the kinematics model. Then, an exact but costly dynamic model is used and the simulation of this model's stationary response for the vehicle shows a qualitative relationship for the specified parameters and . Moreover, the parameters of the kinematic model are determined based-on a laser scanner localization experimental analysis method with a skid-steering robotic platform, Pioneer P3-AT. The relationship between the ICR coefficient and two physical factors is studied, i.e., the radius of the path curvature and the robot speed . An empirical function-based relationship between the ICR coefficient of the robot and the path parameters is derived. To validate the obtained results, it is empirically demonstrated that the proposed kinematics model significantly improves the dead-reckoning performance of this skid-steering robot.

Computer-Aided Construction of Chemical Kinetic Models

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

Green, William H.

2014-12-31

The combustion chemistry of even simple fuels can be extremely complex, involving hundreds or thousands of kinetically significant species. The most reasonable way to deal with this complexity is to use a computer not only to numerically solve the kinetic model, but also to construct the kinetic model in the first place. Because these large models contain so many numerical parameters (e.g. rate coefficients, thermochemistry) one never has sufficient data to uniquely determine them all experimentally. Instead one must work in “predictive” mode, using theoretical rather than experimental values for many of the numbers in the model, and as appropriatemore » refining the most sensitive numbers through experiments. Predictive chemical kinetics is exactly what is needed for computer-aided design of combustion systems based on proposed alternative fuels, particularly for early assessment of the value and viability of proposed new fuels before those fuels are commercially available. This project was aimed at making accurate predictive chemical kinetics practical; this is a challenging goal which requires a range of science advances. The project spanned a wide range from quantum chemical calculations on individual molecules and elementary-step reactions, through the development of improved rate/thermo calculation procedures, the creation of algorithms and software for constructing and solving kinetic simulations, the invention of methods for model-reduction while maintaining error control, and finally comparisons with experiment. Many of the parameters in the models were derived from quantum chemistry calculations, and the models were compared with experimental data measured in our lab or in collaboration with others.« less

Modeling reacting gases and aftertreatment devices for internal combustion engines

NASA Astrophysics Data System (ADS)

Depcik, Christopher David

As more emphasis is placed worldwide on reducing greenhouse gas emissions, automobile manufacturers have to create more efficient engines. Simultaneously, legislative agencies want these engines to produce fewer problematic emissions such as nitrogen oxides and particulate matter. In response, newer combustion methods, like homogeneous charge compression ignition and fuel cells, are being researched alongside the old standard of efficiency, the compression ignition or diesel engine. These newer technologies present a number of benefits but still have significant challenges to overcome. As a result, renewed interest has risen in making diesel engines cleaner. The key to cleaning up the diesel engine is the placement of aftertreatment devices in the exhaust. These devices have shown great potential in reducing emission levels below regulatory levels while still allowing for increased fuel economy versus a gasoline engine. However, these devices are subject to many flow control issues. While experimental evaluation of these devices helps to understand these issues better, it is impossible to solve the problem through experimentation alone because of time and cost constraints. Because of this, accurate models are needed in conjunction with the experimental work. In this dissertation, the author examines the entire exhaust system including reacting gas dynamics and aftertreatment devices, and develops a complete numerical model for it. The author begins by analyzing the current one-dimensional gas-dynamics simulation models used for internal combustion engine simulations. It appears that more accurate and faster numerical method is available, in particular, those developed in aeronautical engineering, and the author successfully implements one for the exhaust system. The author then develops a comprehensive literature search to better understand the aftertreatment devices. A number of these devices require a secondary injection of fuel or reductant in the exhaust stream. Accordingly, the author develops a simple post-cylinder injection model which can be easily tuned to match experimental findings. In addition, the author creates a general catalyst model which can be used to model virtually all of the different aftertreatment devices. Extensive validation of this model with experimental data is presented along with all of the numerical algorithms needed to reproduce the model.

A proposed reductionist solution to address the methodological challenges of inconsistent reflexology maps and poor experimental controls in reflexology research: a discussion paper.

PubMed

Jones, Jenny; Thomson, Patricia; Lauder, William; Leslie, Stephen J

2013-03-01

Reflexology is a complex massage intervention, based on the concept that specific areas of the feet (reflex points) correspond to individual internal organs within the body. Reflexologists trained in the popular Ingham reflexology method claim that massage to these points, using massage techniques unique to reflexology, stimulates an increase in blood supply to the corresponding organ. Reflexology researchers face two key methodological challenges that need to be addressed if a specific treatment-related hemodynamic effect is to be scientifically demonstrated. The first is the problem of inconsistent reflexology foot maps; the second is the issue of poor experimental controls. This article proposes a potential experimental solution that we believe can address both methodological challenges and in doing so, allow any specific hemodynamic treatment effect unique to reflexology to experimentally reveal itself.

Unique attributes of cyanobacterial metabolism revealed by improved genome-scale metabolic modeling and essential gene analysis

DOE PAGES

Broddrick, Jared T.; Rubin, Benjamin E.; Welkie, David G.; ...

2016-12-20

The model cyanobacterium, Synechococcus elongatus PCC 7942, is a genetically tractable obligate phototroph that is being developed for the bioproduction of high-value chemicals. Genome-scale models (GEMs) have been successfully used to assess and engineer cellular metabolism; however, GEMs of phototrophic metabolism have been limited by the lack of experimental datasets for model validation and the challenges of incorporating photon uptake. In this paper, we develop a GEM of metabolism in S. elongatus using random barcode transposon site sequencing (RB-TnSeq) essential gene and physiological data specific to photoautotrophic metabolism. The model explicitly describes photon absorption and accounts for shading, resulting inmore » the characteristic linear growth curve of photoautotrophs. GEM predictions of gene essentiality were compared with data obtained from recent dense-transposon mutagenesis experiments. This dataset allowed major improvements to the accuracy of the model. Furthermore, discrepancies between GEM predictions and the in vivo dataset revealed biological characteristics, such as the importance of a truncated, linear TCA pathway, low flux toward amino acid synthesis from photorespiration, and knowledge gaps within nucleotide metabolism. Finally, coupling of strong experimental support and photoautotrophic modeling methods thus resulted in a highly accurate model of S. elongatus metabolism that highlights previously unknown areas of S. elongatus biology.« less

Unique attributes of cyanobacterial metabolism revealed by improved genome-scale metabolic modeling and essential gene analysis

PubMed Central

Broddrick, Jared T.; Rubin, Benjamin E.; Welkie, David G.; Du, Niu; Mih, Nathan; Diamond, Spencer; Lee, Jenny J.; Golden, Susan S.; Palsson, Bernhard O.

2016-01-01

The model cyanobacterium, Synechococcus elongatus PCC 7942, is a genetically tractable obligate phototroph that is being developed for the bioproduction of high-value chemicals. Genome-scale models (GEMs) have been successfully used to assess and engineer cellular metabolism; however, GEMs of phototrophic metabolism have been limited by the lack of experimental datasets for model validation and the challenges of incorporating photon uptake. Here, we develop a GEM of metabolism in S. elongatus using random barcode transposon site sequencing (RB-TnSeq) essential gene and physiological data specific to photoautotrophic metabolism. The model explicitly describes photon absorption and accounts for shading, resulting in the characteristic linear growth curve of photoautotrophs. GEM predictions of gene essentiality were compared with data obtained from recent dense-transposon mutagenesis experiments. This dataset allowed major improvements to the accuracy of the model. Furthermore, discrepancies between GEM predictions and the in vivo dataset revealed biological characteristics, such as the importance of a truncated, linear TCA pathway, low flux toward amino acid synthesis from photorespiration, and knowledge gaps within nucleotide metabolism. Coupling of strong experimental support and photoautotrophic modeling methods thus resulted in a highly accurate model of S. elongatus metabolism that highlights previously unknown areas of S. elongatus biology. PMID:27911809

Porcine experimental model for perforator flap raising in reconstructive microsurgery.

PubMed

González-García, José A; Chiesa-Estomba, Carlos M; Álvarez, Leire; Altuna, Xabier; García-Iza, Leire; Thomas, Izaskun; Sistiaga, Jon A; Larruscain, Ekhiñe

2018-07-01

Perforator free flap-based reconstruction of the head and neck is a challenging surgical procedure and needs a steep learning curve. A reproducible mammal large animal model with similarities to human anatomy is relevant for perforator flap raising and microanastomosis. The aim of this study was to assess the feasibility of a swine model for perforator-based free flaps in reconstructive microsurgery. Eleven procedures were performed under general anesthesia in a porcine model, elevating a skin flap vascularized by perforating musculocutaneous branches of the superior epigastric artery to evaluate the relevance of this model for head and neck reconstructive microsurgery. The anterior abdominal skin perforator-based free flap in a swine model irrigated by the superior epigastric artery was elevated in eleven procedures. In six of these procedures, we could perform an arterial and venous microanastomosis to the great vessels located in the base of the neck. The porcine experimental model of superior epigastric artery perforator-based free flap reconstruction offers relevant similarities to the human deep inferior epigastric artery perforator flap. We could demonstrate this model as acceptable for perforator free flap training due to the necessity of perforator and pedicle dissection and transfer to a distant area. Copyright © 2018 Elsevier Inc. All rights reserved.

Dynamic contraction behaviour of pneumatic artificial muscle

NASA Astrophysics Data System (ADS)

Doumit, Marc D.; Pardoel, Scott

2017-07-01

The development of a dynamic model for the Pneumatic Artificial Muscle (PAM) is an imperative undertaking for understanding and analyzing the behaviour of the PAM as a function of time. This paper proposes a Newtonian based dynamic PAM model that includes the modeling of the muscle geometry, force, inertia, fluid dynamic, static and dynamic friction, heat transfer and valve flow while ignoring the effect of bladder elasticity. This modeling contribution allows the designer to predict, analyze and optimize PAM performance prior to its development. Thus advancing successful implementations of PAM based powered exoskeletons and medical systems. To date, most muscle dynamic properties are determined experimentally, furthermore, no analytical models that can accurately predict the muscle's dynamic behaviour are found in the literature. Most developed analytical models adequately predict the muscle force in static cases but neglect the behaviour of the system in the transient response. This could be attributed to the highly challenging task of deriving such a dynamic model given the number of system elements that need to be identified and the system's highly non-linear properties. The proposed dynamic model in this paper is successfully simulated through MATLAB programing and validated the pressure, contraction distance and muscle temperature with experimental testing that is conducted with in-house built prototype PAM's.

Unique attributes of cyanobacterial metabolism revealed by improved genome-scale metabolic modeling and essential gene analysis

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

Broddrick, Jared T.; Rubin, Benjamin E.; Welkie, David G.

The model cyanobacterium, Synechococcus elongatus PCC 7942, is a genetically tractable obligate phototroph that is being developed for the bioproduction of high-value chemicals. Genome-scale models (GEMs) have been successfully used to assess and engineer cellular metabolism; however, GEMs of phototrophic metabolism have been limited by the lack of experimental datasets for model validation and the challenges of incorporating photon uptake. In this paper, we develop a GEM of metabolism in S. elongatus using random barcode transposon site sequencing (RB-TnSeq) essential gene and physiological data specific to photoautotrophic metabolism. The model explicitly describes photon absorption and accounts for shading, resulting inmore » the characteristic linear growth curve of photoautotrophs. GEM predictions of gene essentiality were compared with data obtained from recent dense-transposon mutagenesis experiments. This dataset allowed major improvements to the accuracy of the model. Furthermore, discrepancies between GEM predictions and the in vivo dataset revealed biological characteristics, such as the importance of a truncated, linear TCA pathway, low flux toward amino acid synthesis from photorespiration, and knowledge gaps within nucleotide metabolism. Finally, coupling of strong experimental support and photoautotrophic modeling methods thus resulted in a highly accurate model of S. elongatus metabolism that highlights previously unknown areas of S. elongatus biology.« less

Brain tumor segmentation from multimodal magnetic resonance images via sparse representation.

PubMed

Li, Yuhong; Jia, Fucang; Qin, Jing

2016-10-01

Accurately segmenting and quantifying brain gliomas from magnetic resonance (MR) images remains a challenging task because of the large spatial and structural variability among brain tumors. To develop a fully automatic and accurate brain tumor segmentation algorithm, we present a probabilistic model of multimodal MR brain tumor segmentation. This model combines sparse representation and the Markov random field (MRF) to solve the spatial and structural variability problem. We formulate the tumor segmentation problem as a multi-classification task by labeling each voxel as the maximum posterior probability. We estimate the maximum a posteriori (MAP) probability by introducing the sparse representation into a likelihood probability and a MRF into the prior probability. Considering the MAP as an NP-hard problem, we convert the maximum posterior probability estimation into a minimum energy optimization problem and employ graph cuts to find the solution to the MAP estimation. Our method is evaluated using the Brain Tumor Segmentation Challenge 2013 database (BRATS 2013) and obtained Dice coefficient metric values of 0.85, 0.75, and 0.69 on the high-grade Challenge data set, 0.73, 0.56, and 0.54 on the high-grade Challenge LeaderBoard data set, and 0.84, 0.54, and 0.57 on the low-grade Challenge data set for the complete, core, and enhancing regions. The experimental results show that the proposed algorithm is valid and ranks 2nd compared with the state-of-the-art tumor segmentation algorithms in the MICCAI BRATS 2013 challenge. Copyright © 2016 Elsevier B.V. All rights reserved.

Experimental extrinsic allergic alveolitis and pulmonary angiitis induced by intratracheal or intravenous challenge with Corynebacterium parvum in sensitized rats.

PubMed Central

Yi, E. S.; Lee, H.; Suh, Y. K.; Tang, W.; Qi, M.; Yin, S.; Remick, D. G.; Ulich, T. R.

1996-01-01

Extrinsic allergic alveolitis and pulmonary sarcoidosis are granulomatous diseases of the lung for which clinical presentation and anatomic site of granuloma formation differ. Extrinsic allergic alveolitis is caused by inhaled antigens, whereas the nature and source of the inciting antigen in sarcoidosis is unknown. To test the hypothesis that the route via which antigen is introduced to the lung contributes to the clinicopathological presentation of pulmonary granulomatous disease, rats immunized with intravenous (i.v.) Corynebacterium parvum were challenged after 2 weeks with either intratracheal (i.t.) or i.v. C. parvum. The granulomatous inflammation elicited by i.t. challenge predominantly involved alveolar spaces and histologically simulated extrinsic allergic alveolitis. In contrast, the inflammation induced by i.v. challenge was characterized by granulomatous angiitis and interstitial inflammation simulating sarcoidosis. Elevations of leukocyte counts and TNF levels in bronchoalveolar fluid, which reflect inflammation in the intra-alveolar compartment, were much more pronounced after i.t. than after i.v. challenge. Tumor necrosis factor, interleukin-6, CC chemokine, CXC chemokine, and adhesion molecule mRNA and protein expression occurred in each model. In conclusion, i.t. or i.v. challenge with C. parvum in sensitized rats caused pulmonary granulomatous inflammation that was histologically similar to human extrinsic allergic alveolitis and sarcoidosis, respectively. Although the soluble and cellular mediators of granulomatous inflammation were qualitatively similar in both disease models, the differing anatomic source of the same antigenic challenge was responsible for differing clinicopathological presentations. Images Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 11 Figure 13 Figure 12 Figure 14 PMID:8863677

The FLEXGene repository: exploiting the fruits of the genome projects by creating a needed resource to face the challenges of the post-genomic era.

PubMed

Brizuela, Leonardo; Richardson, Aaron; Marsischky, Gerald; Labaer, Joshua

2002-01-01

Thanks to the results of the multiple completed and ongoing genome sequencing projects and to the newly available recombination-based cloning techniques, it is now possible to build gene repositories with no precedent in their composition, formatting, and potential. This new type of gene repository is necessary to address the challenges imposed by the post-genomic era, i.e., experimentation on a genome-wide scale. We are building the FLEXGene (Full Length EXpression-ready) repository. This unique resource will contain clones representing the complete ORFeome of different organisms, including Homo sapiens as well as several pathogens and model organisms. It will consist of a comprehensive, characterized (sequence-verified), and arrayed gene repository. This resource will allow full exploitation of the genomic information by enabling genome-wide scale experimentation at the level of functional/phenotypic assays as well as at the level of protein expression, purification, and analysis. Here we describe the rationale and construction of this resource and focus on the data obtained from the Saccharomyces cerevisiae project.

Practical methods for generating alternating magnetic fields for biomedical research

NASA Astrophysics Data System (ADS)

Christiansen, Michael G.; Howe, Christina M.; Bono, David C.; Perreault, David J.; Anikeeva, Polina

2017-08-01

Alternating magnetic fields (AMFs) cause magnetic nanoparticles (MNPs) to dissipate heat while leaving surrounding tissue unharmed, a mechanism that serves as the basis for a variety of emerging biomedical technologies. Unfortunately, the challenges and costs of developing experimental setups commonly used to produce AMFs with suitable field amplitudes and frequencies present a barrier to researchers. This paper first presents a simple, cost-effective, and robust alternative for small AMF working volumes that uses soft ferromagnetic cores to focus the flux into a gap. As the experimental length scale increases to accommodate animal models (working volumes of 100s of cm3 or greater), poor thermal conductivity and volumetrically scaled core losses render that strategy ineffective. Comparatively feasible strategies for these larger volumes instead use low loss resonant tank circuits to generate circulating currents of 1 kA or greater in order to produce the comparable field amplitudes. These principles can be extended to the problem of identifying practical routes for scaling AMF setups to humans, an infrequently acknowledged challenge that influences the extent to which many applications of MNPs may ever become clinically relevant.

Experimental panic provocation in healthy man—a translational role in anti-panic drug development?

PubMed Central

Kellner, Michael

2011-01-01

Experimental neurochemical provocation of panic attacks in susceptible human subjects has considerably expanded our knowledge of the pathophysiology and psychopharmacology of panic disorder. Some panicogens also elicit short-lived panic-like states in healthy man. This offers the opportunity to assess the anti-panic action of drugs in proof-of-concept studies. However, from current data it is still unclear whether experimental panic in healthy man is a valid translational model. Most such studies in healthy volunteers have been performed using a cholecystokinin tetrapeptide (CCK-4) challenge. While CCK-4 panic was blocked by alprazolam pretreatment, escitalopram showed negative results in healthy man. Preliminary findings on novel investigational drugs and a few problematic results will be reviewed. Small sample sizes in many panic provocation studies, lack of dose-response aspects, and still-insufficient knowledge about the biological underpinning of experimental and spontaneous panic limit the interpretation of existing findings and should inspire further research. PMID:22275853

An Anisotropic Hardening Model for Springback Prediction

NASA Astrophysics Data System (ADS)

Zeng, Danielle; Xia, Z. Cedric

2005-08-01

As more Advanced High-Strength Steels (AHSS) are heavily used for automotive body structures and closures panels, accurate springback prediction for these components becomes more challenging because of their rapid hardening characteristics and ability to sustain even higher stresses. In this paper, a modified Mroz hardening model is proposed to capture realistic Bauschinger effect at reverse loading, such as when material passes through die radii or drawbead during sheet metal forming process. This model accounts for material anisotropic yield surface and nonlinear isotropic/kinematic hardening behavior. Material tension/compression test data are used to accurately represent Bauschinger effect. The effectiveness of the model is demonstrated by comparison of numerical and experimental springback results for a DP600 straight U-channel test.

Automatic Parameterization Strategy for Cardiac Electrophysiology Simulations

PubMed Central

Costa, Caroline Mendonca; Hoetzl, Elena; Rocha, Bernardo Martins; Prassl, Anton J; Plank, Gernot

2014-01-01

Driven by recent advances in medical imaging, image segmentation and numerical techniques, computer models of ventricular electrophysiology account for increasingly finer levels of anatomical and biophysical detail. However, considering the large number of model parameters involved parameterization poses a major challenge. A minimum requirement in combined experimental and modeling studies is to achieve good agreement in activation and repolarization sequences between model and experiment or patient data. In this study, we propose basic techniques which aid in determining bidomain parameters to match activation sequences. An iterative parameterization algorithm is implemented which determines appropriate bulk conductivities which yield prescribed velocities. In addition, a method is proposed for splitting the computed bulk conductivities into individual bidomain conductivities by prescribing anisotropy ratios. PMID:24729986

A Hierarchical multi-input and output Bi-GRU Model for Sentiment Analysis on Customer Reviews

NASA Astrophysics Data System (ADS)

Zhang, Liujie; Zhou, Yanquan; Duan, Xiuyu; Chen, Ruiqi

2018-03-01

Multi-label sentiment classification on customer reviews is a practical challenging task in Natural Language Processing. In this paper, we propose a hierarchical multi-input and output model based bi-directional recurrent neural network, which both considers the semantic and lexical information of emotional expression. Our model applies two independent Bi-GRU layer to generate part of speech and sentence representation. Then the lexical information is considered via attention over output of softmax activation on part of speech representation. In addition, we combine probability of auxiliary labels as feature with hidden layer to capturing crucial correlation between output labels. The experimental result shows that our model is computationally efficient and achieves breakthrough improvements on customer reviews dataset.

Measurement of the Equation of State of the Two-Dimensional Hubbard Model

NASA Astrophysics Data System (ADS)

Miller, Luke; Cocchi, Eugenio; Drewes, Jan; Koschorreck, Marco; Pertot, Daniel; Brennecke, Ferdinand; Koehl, Michael

2016-05-01

The subtle interplay between kinetic energy, interactions and dimensionality challenges our comprehension of strongly-correlated physics observed, for example, in the solid state. In this quest, the Hubbard model has emerged as a conceptually simple, yet rich model describing such physics. Here we present an experimental determination of the equation of state of the repulsive two-dimensional Hubbard model over a broad range of interactions, 0 <= U / t <= 20 , and temperatures, down to kB T / t = 0 . 63(2) using high-resolution imaging of ultracold fermionic atoms in optical lattices. We show density profiles, compressibilities and double occupancies over the whole doping range, and hence our results constitute benchmarks for state-of-the-art theoretical approaches.

Low Velocity Earth-Penetration Test and Analysis

NASA Technical Reports Server (NTRS)

Fasanella, Edwin L.; Jones, Yvonne; Knight, Norman F., Jr.; Kellas, Sotiris

2001-01-01

Modeling and simulation of structural impacts into soil continue to challenge analysts to develop accurate material models and detailed analytical simulations to predict the soil penetration event. This paper discusses finite element modeling of a series of penetrometer drop tests into soft clay. Parametric studies are performed with penetrometers of varying diameters, masses, and impact speeds to a maximum of 45 m/s. Parameters influencing the simulation such as the contact penalty factor and the material model representing the soil are also studied. An empirical relationship between key parameters is developed and is shown to correlate experimental and analytical results quite well. The results provide preliminary design guidelines for Earth impact that may be useful for future space exploration sample return missions.

Adaptive object tracking via both positive and negative models matching

NASA Astrophysics Data System (ADS)

Li, Shaomei; Gao, Chao; Wang, Yawen

2015-03-01

To improve tracking drift which often occurs in adaptive tracking, an algorithm based on the fusion of tracking and detection is proposed in this paper. Firstly, object tracking is posed as abinary classification problem and is modeled by partial least squares (PLS) analysis. Secondly, tracking object frame by frame via particle filtering. Thirdly, validating the tracking reliability based on both positive and negative models matching. Finally, relocating the object based on SIFT features matching and voting when drift occurs. Object appearance model is updated at the same time. The algorithm can not only sense tracking drift but also relocate the object whenever needed. Experimental results demonstrate that this algorithm outperforms state-of-the-art algorithms on many challenging sequences.

Applying the transtheoretical model to promote functional fitness of community older adults participating in elastic band exercises.

PubMed

Yang, Hui-Ju; Chen, Kuei-Min; Chen, Ming-De; Wu, Hui-Chuan; Chang, Wen-Jane; Wang, Yueh-Chin; Huang, Hsin-Ting

2015-10-01

The transtheoretical model was applied to promote behavioural change and test the effects of a group senior elastic band exercise programme on the functional fitness of community older adults in the contemplation and preparation stages of behavioural change. Forming regular exercise habits is challenging for older adults. The transtheoretical model emphasizes using different strategies in various stages to facilitate behavioural changes. Quasi-experimental design with pre-test and post-tests on two groups. Six senior activity centres were randomly assigned to either the experimental or control group. The data were collected during 2011. A total of 199 participants were recruited and 169 participants completed the study (experimental group n = 84, control group n = 85). The elastic band exercises were performed for 40 minutes, three times per week for 6 months. The functional fitness of the participants was evaluated at baseline and at the third and sixth month of the intervention. Statistical analyses included a two-way mixed design analysis of variance, one-way repeated measures analysis of variance and an analysis of covariance. All of the functional fitness indicators had significant changes at post-tests from pre-test in the experimental group. The experimental group had better performances than the control group in all of the functional fitness indicators after three months and 6 months of the senior elastic band exercises. The exercise programme provided older adults with appropriate strategies for maintaining functional fitness, which improved significantly after the participants exercising regularly for 6 months. © 2015 John Wiley & Sons Ltd.