Prediction of essential proteins based on gene expression programming.

PubMed

Zhong, Jiancheng; Wang, Jianxin; Peng, Wei; Zhang, Zhen; Pan, Yi

2013-01-01

Essential proteins are indispensable for cell survive. Identifying essential proteins is very important for improving our understanding the way of a cell working. There are various types of features related to the essentiality of proteins. Many methods have been proposed to combine some of them to predict essential proteins. However, it is still a big challenge for designing an effective method to predict them by integrating different features, and explaining how these selected features decide the essentiality of protein. Gene expression programming (GEP) is a learning algorithm and what it learns specifically is about relationships between variables in sets of data and then builds models to explain these relationships. In this work, we propose a GEP-based method to predict essential protein by combing some biological features and topological features. We carry out experiments on S. cerevisiae data. The experimental results show that the our method achieves better prediction performance than those methods using individual features. Moreover, our method outperforms some machine learning methods and performs as well as a method which is obtained by combining the outputs of eight machine learning methods. The accuracy of predicting essential proteins can been improved by using GEP method to combine some topological features and biological features.

Developing Predictive Toxicity Signatures Using In Vitro Data from the EPA ToxCast Program

EPA Science Inventory

A major focus in toxicology research is the development of in vitro methods to predict in vivo chemical toxicity. Numerous studies have evaluated the use of targeted biochemical, cell-based and genomic assay approaches. Each of these techniques is potentially helpful, but provide...

Epstein-Barr virus latency switch in human B-cells: a physico-chemical model.

PubMed

Werner, Maria; Ernberg, Ingemar; Zou, Jiezhi; Almqvist, Jenny; Aurell, Erik

2007-08-31

The Epstein-Barr virus is widespread in all human populations and is strongly associated with human disease, ranging from infectious mononucleosis to cancer. In infected cells the virus can adopt several different latency programs, affecting the cells' behaviour. Experimental results indicate that a specific genetic switch between viral latency programs, reprograms human B-cells between proliferative and resting states. Each of these two latency programs makes use of a different viral promoter, Cp and Qp, respectively. The hypothesis tested in this study is that this genetic switch is controlled by both human and viral transcription factors; Oct-2 and EBNA-1. We build a physico-chemical model to investigate quantitatively the dynamical properties of the promoter regulation and experimentally examine protein level variations between the two latency programs. Our experimental results display significant differences in EBNA-1 and Oct-2 levels between resting and proliferating programs. With the model we identify two stable latency programs, corresponding to a resting and proliferating cell. The two programs differ in robustness and transcriptional activity. The proliferating state is markedly more stable, with a very high transcriptional activity from its viral promoter. We predict the promoter activities to be mutually exclusive in the two different programs, and our relative promoter activities correlate well with experimental data. Transitions between programs can be induced, by affecting the protein levels of our transcription factors. Simulated time scales are in line with experimental results. We show that fundamental properties of the Epstein-Barr virus involvement in latent infection, with implications for tumor biology, can be modelled and understood mathematically. We conclude that EBNA-1 and Oct-2 regulation of Cp and Qp is sufficient to establish mutually exclusive expression patterns. Moreover, the modelled genetic control predict both mono- and bistable behavior and a considerable difference in transition dynamics, based on program stability and promoter activities. Both these phenomena we hope can be further investigated experimentally, to increase the understanding of this important switch. Our results also stress the importance of the little known regulation of human transcription factor Oct-2.

Dual role of starvation signaling in promoting growth and recovery

PubMed Central

Leshkowitz, Dena; Barkai, Naama

2017-01-01

Growing cells are subject to cycles of nutrient depletion and repletion. A shortage of nutrients activates a starvation program that promotes growth in limiting conditions. To examine whether nutrient-deprived cells prepare also for their subsequent recovery, we followed the transcription program activated in budding yeast transferred to low-phosphate media and defined its contribution to cell growth during phosphate limitation and upon recovery. An initial transcription wave was induced by moderate phosphate depletion that did not affect cell growth. A second transcription wave followed when phosphate became growth limiting. The starvation program contributed to growth only in the second, growth-limiting phase. Notably, the early response, activated at moderate depletion, promoted recovery from starvation by increasing phosphate influx upon transfer to rich medium. Our results suggest that cells subject to nutrient depletion prepare not only for growth in the limiting conditions but also for their predicted recovery once nutrients are replenished. PMID:29236696

The Significance of the PD-L1 Expression in Non-Small-Cell Lung Cancer: Trenchant Double Swords as Predictive and Prognostic Markers.

PubMed

Takada, Kazuki; Toyokawa, Gouji; Shoji, Fumihiro; Okamoto, Tatsuro; Maehara, Yoshihiko

2018-03-01

Lung cancer is the leading cause of death due to cancer worldwide. Surgery, chemotherapy, and radiotherapy have been the standard treatment for lung cancer, and targeted molecular therapy has greatly improved the clinical course of patients with non-small-cell lung cancer (NSCLC) harboring driver mutations, such as in epidermal growth factor receptor and anaplastic lymphoma kinase genes. Despite advances in such therapies, the prognosis of patients with NSCLC without driver oncogene mutations remains poor. Immunotherapy targeting programmed cell death-1 (PD-1) and programmed cell death-ligand 1 (PD-L1) has recently been shown to improve the survival in advanced NSCLC. The PD-L1 expression on the surface of tumor cells has emerged as a potential biomarker for predicting responses to immunotherapy and prognosis after surgery in NSCLC. However, the utility of PD-L1 expression as a predictive and prognostic biomarker remains controversial because of the existence of various PD-L1 antibodies, scoring systems, and positivity cutoffs. In this review, we summarize the data from representative clinical trials of PD-1/PD-L1 immune checkpoint inhibitors in NSCLC and previous reports on the association between PD-L1 expression and clinical outcomes in patients with NSCLC. Furthermore, we discuss the future perspectives of immunotherapy and immune checkpoint factors. Copyright © 2017 Elsevier Inc. All rights reserved.

Software Engineering Tools for Scientific Models

NASA Technical Reports Server (NTRS)

Abrams, Marc; Saboo, Pallabi; Sonsini, Mike

2013-01-01

Software tools were constructed to address issues the NASA Fortran development community faces, and they were tested on real models currently in use at NASA. These proof-of-concept tools address the High-End Computing Program and the Modeling, Analysis, and Prediction Program. Two examples are the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5) atmospheric model in Cell Fortran on the Cell Broadband Engine, and the Goddard Institute for Space Studies (GISS) coupled atmosphere- ocean model called ModelE, written in fixed format Fortran.

PSORTb 3.0: improved protein subcellular localization prediction with refined localization subcategories and predictive capabilities for all prokaryotes.

PubMed

Yu, Nancy Y; Wagner, James R; Laird, Matthew R; Melli, Gabor; Rey, Sébastien; Lo, Raymond; Dao, Phuong; Sahinalp, S Cenk; Ester, Martin; Foster, Leonard J; Brinkman, Fiona S L

2010-07-01

PSORTb has remained the most precise bacterial protein subcellular localization (SCL) predictor since it was first made available in 2003. However, the recall needs to be improved and no accurate SCL predictors yet make predictions for archaea, nor differentiate important localization subcategories, such as proteins targeted to a host cell or bacterial hyperstructures/organelles. Such improvements should preferably be encompassed in a freely available web-based predictor that can also be used as a standalone program. We developed PSORTb version 3.0 with improved recall, higher proteome-scale prediction coverage, and new refined localization subcategories. It is the first SCL predictor specifically geared for all prokaryotes, including archaea and bacteria with atypical membrane/cell wall topologies. It features an improved standalone program, with a new batch results delivery system complementing its web interface. We evaluated the most accurate SCL predictors using 5-fold cross validation plus we performed an independent proteomics analysis, showing that PSORTb 3.0 is the most accurate but can benefit from being complemented by Proteome Analyst predictions. http://www.psort.org/psortb (download open source software or use the web interface). psort-mail@sfu.ca Supplementary data are available at Bioinformatics online.

Classifying the Progression of Ductal Carcinoma from Single-Cell Sampled Data via Integer Linear Programming: A Case Study

PubMed Central

Catanzaro, Daniele; Schäffer, Alejandro A.; Schwartz, Russell

2016-01-01

Ductal Carcinoma In Situ (DCIS) is a precursor lesion of Invasive Ductal Carcinoma (IDC) of the breast. Investigating its temporal progression could provide fundamental new insights for the development of better diagnostic tools to predict which cases of DCIS will progress to IDC. We investigate the problem of reconstructing a plausible progression from single-cell sampled data of an individual with Synchronous DCIS and IDC. Specifically, by using a number of assumptions derived from the observation of cellular atypia occurring in IDC, we design a possible predictive model using integer linear programming (ILP). Computational experiments carried out on a preexisting data set of 13 patients with simultaneous DCIS and IDC show that the corresponding predicted progression models are classifiable into categories having specific evolutionary characteristics. The approach provides new insights into mechanisms of clonal progression in breast cancers and helps illustrate the power of the ILP approach for similar problems in reconstructing tumor evolution scenarios under complex sets of constraints. PMID:26353381

Classifying the Progression of Ductal Carcinoma from Single-Cell Sampled Data via Integer Linear Programming: A Case Study.

PubMed

Catanzaro, Daniele; Shackney, Stanley E; Schaffer, Alejandro A; Schwartz, Russell

2016-01-01

Ductal Carcinoma In Situ (DCIS) is a precursor lesion of Invasive Ductal Carcinoma (IDC) of the breast. Investigating its temporal progression could provide fundamental new insights for the development of better diagnostic tools to predict which cases of DCIS will progress to IDC. We investigate the problem of reconstructing a plausible progression from single-cell sampled data of an individual with synchronous DCIS and IDC. Specifically, by using a number of assumptions derived from the observation of cellular atypia occurring in IDC, we design a possible predictive model using integer linear programming (ILP). Computational experiments carried out on a preexisting data set of 13 patients with simultaneous DCIS and IDC show that the corresponding predicted progression models are classifiable into categories having specific evolutionary characteristics. The approach provides new insights into mechanisms of clonal progression in breast cancers and helps illustrate the power of the ILP approach for similar problems in reconstructing tumor evolution scenarios under complex sets of constraints.

Classification and disease prediction via mathematical programming

NASA Astrophysics Data System (ADS)

Lee, Eva K.; Wu, Tsung-Lin

2007-11-01

In this chapter, we present classification models based on mathematical programming approaches. We first provide an overview on various mathematical programming approaches, including linear programming, mixed integer programming, nonlinear programming and support vector machines. Next, we present our effort of novel optimization-based classification models that are general purpose and suitable for developing predictive rules for large heterogeneous biological and medical data sets. Our predictive model simultaneously incorporates (1) the ability to classify any number of distinct groups; (2) the ability to incorporate heterogeneous types of attributes as input; (3) a high-dimensional data transformation that eliminates noise and errors in biological data; (4) the ability to incorporate constraints to limit the rate of misclassification, and a reserved-judgment region that provides a safeguard against over-training (which tends to lead to high misclassification rates from the resulting predictive rule) and (5) successive multi-stage classification capability to handle data points placed in the reserved judgment region. To illustrate the power and flexibility of the classification model and solution engine, and its multigroup prediction capability, application of the predictive model to a broad class of biological and medical problems is described. Applications include: the differential diagnosis of the type of erythemato-squamous diseases; predicting presence/absence of heart disease; genomic analysis and prediction of aberrant CpG island meythlation in human cancer; discriminant analysis of motility and morphology data in human lung carcinoma; prediction of ultrasonic cell disruption for drug delivery; identification of tumor shape and volume in treatment of sarcoma; multistage discriminant analysis of biomarkers for prediction of early atherosclerois; fingerprinting of native and angiogenic microvascular networks for early diagnosis of diabetes, aging, macular degeneracy and tumor metastasis; prediction of protein localization sites; and pattern recognition of satellite images in classification of soil types. In all these applications, the predictive model yields correct classification rates ranging from 80% to 100%. This provides motivation for pursuing its use as a medical diagnostic, monitoring and decision-making tool.

Immunohistochemistry for predictive biomarkers in non-small cell lung cancer.

PubMed

Mino-Kenudson, Mari

2017-10-01

In the era of targeted therapy, predictive biomarker testing has become increasingly important for non-small cell lung cancer. Of multiple predictive biomarker testing methods, immunohistochemistry (IHC) is widely available and technically less challenging, can provide clinically meaningful results with a rapid turn-around-time and is more cost efficient than molecular platforms. In fact, several IHC assays for predictive biomarkers have already been implemented in routine pathology practice. In this review, we will discuss: (I) the details of anaplastic lymphoma kinase (ALK) and proto-oncogene tyrosine-protein kinase ROS (ROS1) IHC assays including the performance of multiple antibody clones, pros and cons of IHC platforms and various scoring systems to design an optimal algorithm for predictive biomarker testing; (II) issues associated with programmed death-ligand 1 (PD-L1) IHC assays; (III) appropriate pre-analytical tissue handling and selection of optimal tissue samples for predictive biomarker IHC.

Immunohistochemistry for predictive biomarkers in non-small cell lung cancer

PubMed Central

2017-01-01

In the era of targeted therapy, predictive biomarker testing has become increasingly important for non-small cell lung cancer. Of multiple predictive biomarker testing methods, immunohistochemistry (IHC) is widely available and technically less challenging, can provide clinically meaningful results with a rapid turn-around-time and is more cost efficient than molecular platforms. In fact, several IHC assays for predictive biomarkers have already been implemented in routine pathology practice. In this review, we will discuss: (I) the details of anaplastic lymphoma kinase (ALK) and proto-oncogene tyrosine-protein kinase ROS (ROS1) IHC assays including the performance of multiple antibody clones, pros and cons of IHC platforms and various scoring systems to design an optimal algorithm for predictive biomarker testing; (II) issues associated with programmed death-ligand 1 (PD-L1) IHC assays; (III) appropriate pre-analytical tissue handling and selection of optimal tissue samples for predictive biomarker IHC. PMID:29114473

A linear programming computational framework integrates phosphor-proteomics and prior knowledge to predict drug efficacy.

PubMed

Ji, Zhiwei; Wang, Bing; Yan, Ke; Dong, Ligang; Meng, Guanmin; Shi, Lei

2017-12-21

In recent years, the integration of 'omics' technologies, high performance computation, and mathematical modeling of biological processes marks that the systems biology has started to fundamentally impact the way of approaching drug discovery. The LINCS public data warehouse provides detailed information about cell responses with various genetic and environmental stressors. It can be greatly helpful in developing new drugs and therapeutics, as well as improving the situations of lacking effective drugs, drug resistance and relapse in cancer therapies, etc. In this study, we developed a Ternary status based Integer Linear Programming (TILP) method to infer cell-specific signaling pathway network and predict compounds' treatment efficacy. The novelty of our study is that phosphor-proteomic data and prior knowledge are combined for modeling and optimizing the signaling network. To test the power of our approach, a generic pathway network was constructed for a human breast cancer cell line MCF7; and the TILP model was used to infer MCF7-specific pathways with a set of phosphor-proteomic data collected from ten representative small molecule chemical compounds (most of them were studied in breast cancer treatment). Cross-validation indicated that the MCF7-specific pathway network inferred by TILP were reliable predicting a compound's efficacy. Finally, we applied TILP to re-optimize the inferred cell-specific pathways and predict the outcomes of five small compounds (carmustine, doxorubicin, GW-8510, daunorubicin, and verapamil), which were rarely used in clinic for breast cancer. In the simulation, the proposed approach facilitates us to identify a compound's treatment efficacy qualitatively and quantitatively, and the cross validation analysis indicated good accuracy in predicting effects of five compounds. In summary, the TILP model is useful for discovering new drugs for clinic use, and also elucidating the potential mechanisms of a compound to targets.

A synthetic genetic edge detection program.

PubMed

Tabor, Jeffrey J; Salis, Howard M; Simpson, Zachary Booth; Chevalier, Aaron A; Levskaya, Anselm; Marcotte, Edward M; Voigt, Christopher A; Ellington, Andrew D

2009-06-26

Edge detection is a signal processing algorithm common in artificial intelligence and image recognition programs. We have constructed a genetically encoded edge detection algorithm that programs an isogenic community of E. coli to sense an image of light, communicate to identify the light-dark edges, and visually present the result of the computation. The algorithm is implemented using multiple genetic circuits. An engineered light sensor enables cells to distinguish between light and dark regions. In the dark, cells produce a diffusible chemical signal that diffuses into light regions. Genetic logic gates are used so that only cells that sense light and the diffusible signal produce a positive output. A mathematical model constructed from first principles and parameterized with experimental measurements of the component circuits predicts the performance of the complete program. Quantitatively accurate models will facilitate the engineering of more complex biological behaviors and inform bottom-up studies of natural genetic regulatory networks.

A Synthetic Genetic Edge Detection Program

PubMed Central

Tabor, Jeffrey J.; Salis, Howard; Simpson, Zachary B.; Chevalier, Aaron A.; Levskaya, Anselm; Marcotte, Edward M.; Voigt, Christopher A.; Ellington, Andrew D.

2009-01-01

Summary Edge detection is a signal processing algorithm common in artificial intelligence and image recognition programs. We have constructed a genetically encoded edge detection algorithm that programs an isogenic community of E.coli to sense an image of light, communicate to identify the light-dark edges, and visually present the result of the computation. The algorithm is implemented using multiple genetic circuits. An engineered light sensor enables cells to distinguish between light and dark regions. In the dark, cells produce a diffusible chemical signal that diffuses into light regions. Genetic logic gates are used so that only cells that sense light and the diffusible signal produce a positive output. A mathematical model constructed from first principles and parameterized with experimental measurements of the component circuits predicts the performance of the complete program. Quantitatively accurate models will facilitate the engineering of more complex biological behaviors and inform bottom-up studies of natural genetic regulatory networks. PMID:19563759

Parametric analysis of ATM solar array.

NASA Technical Reports Server (NTRS)

Singh, B. K.; Adkisson, W. B.

1973-01-01

The paper discusses the methods used for the calculation of ATM solar array performance characteristics and provides the parametric analysis of solar panels used in SKYLAB. To predict the solar array performance under conditions other than test conditions, a mathematical model has been developed. Four computer programs have been used to convert the solar simulator test data to the parametric curves. The first performs module summations, the second determines average solar cell characteristics which will cause a mathematical model to generate a curve matching the test data, the third is a polynomial fit program which determines the polynomial equations for the solar cell characteristics versus temperature, and the fourth program uses the polynomial coefficients generated by the polynomial curve fit program to generate the parametric data.

FIESTA ROC: A new finite element analysis program for solar cell simulation

NASA Technical Reports Server (NTRS)

Clark, Ralph O.

1991-01-01

The Finite Element Semiconductor Three-dimensional Analyzer by Ralph O. Clark (FIESTA ROC) is a computational tool for investigating in detail the performance of arbitrary solar cell structures. As its name indicates, it uses the finite element technique to solve the fundamental semiconductor equations in the cell. It may be used for predicting the performance (thereby dictating the design parameters) of a proposed cell or for investigating the limiting factors in an established design.

Project STOP (Spectral Thermal Optimization Program)

NASA Technical Reports Server (NTRS)

Goldhammer, L. J.; Opjorden, R. W.; Goodelle, G. S.; Powe, J. S.

1977-01-01

The spectral thermal optimization of solar cell configurations for various solar panel applications is considered. The method of optimization depends upon varying the solar cell configuration's optical characteristics to minimize panel temperatures, maximize power output and decrease the power delta from beginning of life to end of life. Four areas of primary investigation are: (1) testing and evaluation of ultraviolet resistant coverslide adhesives, primarily FEP as an adhesive; (2) examination of solar cell absolute spectral response and corresponding cell manufacturing processes that affect it; (3) experimental work with solar cell manufacturing processes that vary cell reflectance (solar absorptance); and (4) experimental and theoretical studies with various coverslide filter designs, mainly a red rejection filter. The Hughes' solar array prediction program has been modified to aid in evaluating the effect of each of the above four areas on the output of a solar panel in orbit.

TRAIL-induced programmed necrosis as a novel approach to eliminate tumor cells

PubMed Central

2014-01-01

Background The cytokine TRAIL represents one of the most promising candidates for the apoptotic elimination of tumor cells, either alone or in combination therapies. However, its efficacy is often limited by intrinsic or acquired resistance of tumor cells to apoptosis. Programmed necrosis is an alternative, molecularly distinct mode of programmed cell death that is elicited by TRAIL under conditions when the classical apoptosis machinery fails or is actively inhibited. The potential of TRAIL-induced programmed necrosis in tumor therapy is, however, almost completely uncharacterized. We therefore investigated its impact on a panel of tumor cell lines of wide-ranging origin. Methods Cell death/viability was measured by flow cytometry/determination of intracellular ATP levels/crystal violet staining. Cell surface expression of TRAIL receptors was detected by flow cytometry, expression of proteins by Western blot. Ceramide levels were quantified by high-performance thin layer chromatography and densitometric analysis, clonogenic survival of cells was determined by crystal violet staining or by soft agarose cloning. Results TRAIL-induced programmed necrosis killed eight out of 14 tumor cell lines. Clonogenic survival was reduced in all sensitive and even one resistant cell lines tested. TRAIL synergized with chemotherapeutics in killing tumor cell lines by programmed necrosis, enhancing their effect in eight out of 10 tested tumor cell lines and in 41 out of 80 chemotherapeutic/TRAIL combinations. Susceptibility/resistance of the investigated tumor cell lines to programmed necrosis seems to primarily depend on expression of the pro-necrotic kinase RIPK3 rather than the related kinase RIPK1 or cell surface expression of TRAIL receptors. Furthermore, interference with production of the lipid ceramide protected all tested tumor cell lines. Conclusions Our study provides evidence that TRAIL-induced programmed necrosis represents a feasible approach for the elimination of tumor cells, and that this treatment may represent a promising new option for the future development of combination therapies. Our data also suggest that RIPK3 expression may serve as a potential predictive marker for the sensitivity of tumor cells to programmed necrosis and extend the previously established role of ceramide as a key mediator of death receptor-induced programmed necrosis (and thus as a potential target for future therapies) also to the tumor cell lines examined here. PMID:24507727

Reliability analysis and initial requirements for FC systems and stacks

NASA Astrophysics Data System (ADS)

Åström, K.; Fontell, E.; Virtanen, S.

In the year 2000 Wärtsilä Corporation started an R&D program to develop SOFC systems for CHP applications. The program aims to bring to the market highly efficient, clean and cost competitive fuel cell systems with rated power output in the range of 50-250 kW for distributed generation and marine applications. In the program Wärtsilä focuses on system integration and development. System reliability and availability are key issues determining the competitiveness of the SOFC technology. In Wärtsilä, methods have been implemented for analysing the system in respect to reliability and safety as well as for defining reliability requirements for system components. A fault tree representation is used as the basis for reliability prediction analysis. A dynamic simulation technique has been developed to allow for non-static properties in the fault tree logic modelling. Special emphasis has been placed on reliability analysis of the fuel cell stacks in the system. A method for assessing reliability and critical failure predictability requirements for fuel cell stacks in a system consisting of several stacks has been developed. The method is based on a qualitative model of the stack configuration where each stack can be in a functional, partially failed or critically failed state, each of the states having different failure rates and effects on the system behaviour. The main purpose of the method is to understand the effect of stack reliability, critical failure predictability and operating strategy on the system reliability and availability. An example configuration, consisting of 5 × 5 stacks (series of 5 sets of 5 parallel stacks) is analysed in respect to stack reliability requirements as a function of predictability of critical failures and Weibull shape factor of failure rate distributions.

Safety hazards associated with the charging of lithium/sulfur dioxide cells

NASA Technical Reports Server (NTRS)

Frank, H.; Halpert, G.; Lawson, D. D.; Barnes, J. A.; Bis, R. F.

1986-01-01

A continuing research program to assess the responses of spirally wound, lithium/sulfur dioxide cells to charging as functions of charging current, temperature, and cell condition prior to charging is described. Partially discharged cells that are charged at currents greater than one ampere explode with the time to explosion inversely proportional to the charging current. Cells charged at currents of less than one ampere may fail in one of several modes. The data allows an empirical prediction of when certain cells will fail given a constant charging current.

Current status of one- and two-dimensional numerical models: Successes and limitations

NASA Technical Reports Server (NTRS)

Schwartz, R. J.; Gray, J. L.; Lundstrom, M. S.

1985-01-01

The capabilities of one and two-dimensional numerical solar cell modeling programs (SCAP1D and SCAP2D) are described. The occasions when a two-dimensional model is required are discussed. The application of the models to design, analysis, and prediction are presented along with a discussion of problem areas for solar cell modeling.

Comparative modeling of InP solar cell structures

NASA Technical Reports Server (NTRS)

Jain, R. K.; Weinberg, I.; Flood, D. J.

1991-01-01

The comparative modeling of p(+)n and n(+)p indium phosphide solar cell structures is studied using a numerical program PC-1D. The optimal design study has predicted that the p(+)n structure offers improved cell efficiencies as compared to n(+)p structure, due to higher open-circuit voltage. The various cell material and process parameters to achieve the maximum cell efficiencies are reported. The effect of some of the cell parameters on InP cell I-V characteristics was studied. The available radiation resistance data on n(+)p and p(+)p InP solar cells are also critically discussed.

Aging and immortality: quasi-programmed senescence and its pharmacologic inhibition.

PubMed

Blagosklonny, Mikhail V

2006-09-01

While ruling out programmed aging, evolutionary theory predicts a quasi-program for aging, a continuation of the developmental program that is not turned off, is constantly on, becoming hyper-functional and damaging, causing diseases of aging. Could it be switched off pharmacologically? This would require identification of a molecular target involved in cell senescence, organism aging and diseases of aging. Notably, cell senescence is associated with activation of the TOR (target of rapamycin) nutrient- and mitogen-sensing pathway, which promotes cell growth, even though cell cycle is blocked. Is TOR involved in organism aging? In fact, in yeast (where the cell is the organism), caloric restriction, rapamycin and mutations that inhibit TOR all slow down aging. In animals from worms to mammals caloric restrictions, life-extending agents, and numerous mutations that increase longevity all converge on the TOR pathway. And, in humans, cell hypertrophy, hyper-function and hyperplasia, typically associated with activation of TOR, contribute to diseases of aging. Theoretical and clinical considerations suggest that rapamycin may be effective against atherosclerosis, hypertension and hyper-coagulation (thus, preventing myocardial infarction and stroke), osteoporosis, cancer, autoimmune diseases and arthritis, obesity, diabetes, macula-degeneration, Alzheimer's and Parkinson's diseases. Finally, I discuss that extended life span will reveal new causes for aging (e.g., ROS, 'wear and tear', Hayflick limit, stem cell exhaustion) that play a limited role now, when quasi-programmed senescence kills us first.

Safety testing of lithium cells

NASA Technical Reports Server (NTRS)

Liberto, Nick

1991-01-01

Safety testing is intended to simulate, under laboratory conditions and controls, situations that will subject a cell to externally induced stress. The stresses can occur at any time during the useful life of the cell, from the time of manufacture until it is expended during mission deployment. Abuse testing can be divided into three major categories: Electrical, Mechanical, and Thermal. Although electrical abuses are generally found to occur during handling or deployment, Mechanical and Thermal stresses can be induced during transportation and storage. Therefore, it would be prudent to include predicted environmental exposure as part of the test plan. In the selection of a test program. specific test requirements should be tailored to meet the predicted mission requirements.

Safety testing of lithium cells

NASA Astrophysics Data System (ADS)

Liberto, Nick

1991-05-01

Safety testing is intended to simulate, under laboratory conditions and controls, situations that will subject a cell to externally induced stress. The stresses can occur at any time during the useful life of the cell, from the time of manufacture until it is expended during mission deployment. Abuse testing can be divided into three major categories: Electrical, Mechanical, and Thermal. Although electrical abuses are generally found to occur during handling or deployment, Mechanical and Thermal stresses can be induced during transportation and storage. Therefore, it would be prudent to include predicted environmental exposure as part of the test plan. In the selection of a test program. specific test requirements should be tailored to meet the predicted mission requirements.

Geary autocorrelation and DCCA coefficient: Application to predict apoptosis protein subcellular localization via PSSM

NASA Astrophysics Data System (ADS)

Liang, Yunyun; Liu, Sanyang; Zhang, Shengli

2017-02-01

Apoptosis is a fundamental process controlling normal tissue homeostasis by regulating a balance between cell proliferation and death. Predicting subcellular location of apoptosis proteins is very helpful for understanding its mechanism of programmed cell death. Prediction of apoptosis protein subcellular location is still a challenging and complicated task, and existing methods mainly based on protein primary sequences. In this paper, we propose a new position-specific scoring matrix (PSSM)-based model by using Geary autocorrelation function and detrended cross-correlation coefficient (DCCA coefficient). Then a 270-dimensional (270D) feature vector is constructed on three widely used datasets: ZD98, ZW225 and CL317, and support vector machine is adopted as classifier. The overall prediction accuracies are significantly improved by rigorous jackknife test. The results show that our model offers a reliable and effective PSSM-based tool for prediction of apoptosis protein subcellular localization.

The physics of cellular synthesis, growth and division

NASA Technical Reports Server (NTRS)

Pollard, E. C.

1974-01-01

Three areas of research in NASA'S University Program are described. Primitive terrestrial living cells were studied as a guide to the kind of cells to look for in extraterrestrial life. Experiments in zero gravity conditions are described with emphasis upon effects on small organisms. The effects of ionizing radiation on cells are studied so that it will be possible to predict dosages which can be tolerated by humans with no permanent damage.

Clinical Utility of Urinary Cytology to Detect BK Viral Nephropathy.

PubMed

Nankivell, Brian J; Renthawa, Jasveen; Jeoffreys, Neisha; Kable, Kathy; O'Connell, Philip J; Chapman, Jeremy R; Wong, Germaine; Sharma, Raghwa N

2015-08-01

Reactivation of BK polyoma virus can result in destructive viral allograft nephropathy (BKVAN) with limited treatment options. Screening programs using surrogate markers of viral replication are important preventive strategies, guiding immunosuppression reduction. We prospectively evaluated the diagnostic test performance of urinary decoy cells and urinary SV40T immunochemistry of exfoliated cells, to screen for BKVAN, (defined by reference histology with SV40 immunohistochemistry, n = 704 samples), compared with quantitative viremia, from 211 kidney and 141 kidney-pancreas transplant recipients. The disease prevalence of BKVAN was 2.6%. Decoy cells occurred in 95 of 704 (13.5%) samples, with a sensitivity of 66.7%, specificity of 88.6%, positive predictive value (PPV) of 11.7%, and negative predictive value of 98.5% to predict histologically proven BKVAN. Quantification of decoy cells improved the PPV to 32.1% (10 ≥ cells threshold). Immunohistochemical staining of urinary exfoliated cells for SV40T improved sensitivity to 85.7%, detecting atypical or degenerate infected cells (specificity of 92.3% and PPV of 33.3%), but was hampered by technical failures. Viremia occurred in 90 of 704 (12.8%) with sensitivity of 96.3%, specificity of 90.3%, PPV of 31.5%, and negative predictive value of 99.8%. The receiver-operator curve performance of quantitative viremia surpassed decoy cells (area under the curve of 0.95 and 0.79, respectively, P = 0.0018 for differences). Combining decoy cell and BK viremia in a diagnostic matrix improved prediction of BKVAN and diagnostic risk stratification, especially for high-level positive results. Although quantified decoy cells are acceptable surrogate markers of BK viral replication with unexceptional test performances, quantitative viremia displayed superior test characteristics and is suggested as the screening test of choice.

DNA context represents transcription regulation of the gene in mouse embryonic stem cells

NASA Astrophysics Data System (ADS)

Ha, Misook; Hong, Soondo

2016-04-01

Understanding gene regulatory information in DNA remains a significant challenge in biomedical research. This study presents a computational approach to infer gene regulatory programs from primary DNA sequences. Using DNA around transcription start sites as attributes, our model predicts gene regulation in the gene. We find that H3K27ac around TSS is an informative descriptor of the transcription program in mouse embryonic stem cells. We build a computational model inferring the cell-type-specific H3K27ac signatures in the DNA around TSS. A comparison of embryonic stem cell and liver cell-specific H3K27ac signatures in DNA shows that the H3K27ac signatures in DNA around TSS efficiently distinguish the cell-type specific H3K27ac peaks and the gene regulation. The arrangement of the H3K27ac signatures inferred from the DNA represents the transcription regulation of the gene in mESC. We show that the DNA around transcription start sites is associated with the gene regulatory program by specific interaction with H3K27ac.

DNA context represents transcription regulation of the gene in mouse embryonic stem cells.

PubMed

Ha, Misook; Hong, Soondo

2016-04-14

Understanding gene regulatory information in DNA remains a significant challenge in biomedical research. This study presents a computational approach to infer gene regulatory programs from primary DNA sequences. Using DNA around transcription start sites as attributes, our model predicts gene regulation in the gene. We find that H3K27ac around TSS is an informative descriptor of the transcription program in mouse embryonic stem cells. We build a computational model inferring the cell-type-specific H3K27ac signatures in the DNA around TSS. A comparison of embryonic stem cell and liver cell-specific H3K27ac signatures in DNA shows that the H3K27ac signatures in DNA around TSS efficiently distinguish the cell-type specific H3K27ac peaks and the gene regulation. The arrangement of the H3K27ac signatures inferred from the DNA represents the transcription regulation of the gene in mESC. We show that the DNA around transcription start sites is associated with the gene regulatory program by specific interaction with H3K27ac.

Potential biomarker panels in overall breast cancer management: advancements by multilevel diagnostics.

PubMed

Girotra, Shantanu; Yeghiazaryan, Kristina; Golubnitschaja, Olga

2016-09-01

Breast cancer (BC) prevalence has reached an epidemic scale with half a million deaths annually. Current deficits in BC management include predictive and preventive approaches, optimized screening programs, individualized patient profiling, highly sensitive detection technologies for more precise diagnostics and therapy monitoring, individualized prediction and effective treatment of BC metastatic disease. To advance BC management, paradigm shift from delayed to predictive, preventive and personalized medical services is essential. Corresponding step forwards requires innovative multilevel diagnostics procuring specific panels of validated biomarkers. Here, we discuss current instrumental advancements including genomics, proteomics, epigenetics, miRNA, metabolomics, circulating tumor cells and cancer stem cells with a focus on biomarker discovery and multilevel diagnostic panels. A list of the recommended biomarker candidates is provided.

Evaluation program for secondary spacecraft cells: Cycle life test

NASA Technical Reports Server (NTRS)

Harkness, J. D.

1979-01-01

The service life and storage stability for several storage batteries were determined. The batteries included silver-zinc batteries, nickel-cadmium batteries, and silver-cadmium batteries. The cell performance characteristics and limitations are to be used by spacecraft power systems planners and designers. A statistical analysis of the life cycle prediction and cause of failure versus test conditions is presented.

Long non-coding RNA HOTTIP promotes prostate cancer cells proliferation and migration by sponging miR-216a-5p.

PubMed

Yang, Bin; Gao, Ge; Wang, Zhixin; Sun, Daju; Wei, Xin; Ma, Yanan; Ding, Youpeng

2018-06-08

Long non-coding RNAs (lncRNAs) are a class of ncRNAs with > 200 nucleotides in length that regulate gene expression. The HOXA transcript at the distal tip (HOTTIP) lncRNA plays an important role in carcinogenesis, however, the underlying role of HOTTIP in prostate cancer (PCa) remain unknown. The aim of the present study was to evaluate the expression and function of HOTTIP in PCa. In the present study, we analyzed HOTTIP expression levels of 86 PCa patients in tumor and adjacent normal tissue by real-time quantitative PCR. Knockdown or overexpression of HOTTIP was performed to explore its roles in cell proliferation, migration, invasion, and cell cycle. Furthermore, bioinformatics online programs predicted and luciferase reporter assay were used to validate the association of HOTTIP and miR-216a-5p in PCa cells. Our results found that HOTTIP was up-regulated in human primary PCa tissues with lymph node metastasis. Knockdown of HOTTIP inhibited PCa cell proliferation, migration and invasion. Overexpression of HOTTIP promoted cell proliferation, migration and invasion of PCa cells. Bioinformatics online programs predicted that HOTTIP sponge miR-216a-5p at 3'-UTR with complementary binding sites, which was validated using luciferase reporter assay. HOTTIP could negatively regulate the expression of miR-216a-5p in PCa cells. Above all, knockdown of HOTTIP could represent a rational therapeutic strategy for PCa. ©2018 The Author(s).

Musashi2 sustains the mixed-lineage leukemia–driven stem cell regulatory program

PubMed Central

Park, Sun-Mi; Gönen, Mithat; Vu, Ly; Minuesa, Gerard; Tivnan, Patrick; Barlowe, Trevor S.; Taggart, James; Lu, Yuheng; Deering, Raquel P.; Hacohen, Nir; Figueroa, Maria E.; Paietta, Elisabeth; Fernandez, Hugo F.; Tallman, Martin S.; Melnick, Ari; Levine, Ross; Leslie, Christina; Lengner, Christopher J.; Kharas, Michael G.

2015-01-01

Leukemia stem cells (LSCs) are found in most aggressive myeloid diseases and contribute to therapeutic resistance. Leukemia cells exhibit a dysregulated developmental program as the result of genetic and epigenetic alterations. Overexpression of the RNA-binding protein Musashi2 (MSI2) has been previously shown to predict poor survival in leukemia. Here, we demonstrated that conditional deletion of Msi2 in the hematopoietic compartment results in delayed leukemogenesis, reduced disease burden, and a loss of LSC function in a murine leukemia model. Gene expression profiling of these Msi2-deficient animals revealed a loss of the hematopoietic/leukemic stem cell self-renewal program and an increase in the differentiation program. In acute myeloid leukemia patients, the presence of a gene signature that was similar to that observed in Msi2-deficent murine LSCs correlated with improved survival. We determined that MSI2 directly maintains the mixed-lineage leukemia (MLL) self-renewal program by interacting with and retaining efficient translation of Hoxa9, Myc, and Ikzf2 mRNAs. Moreover, depletion of MLL target Ikzf2 in LSCs reduced colony formation, decreased proliferation, and increased apoptosis. Our data provide evidence that MSI2 controls efficient translation of the oncogenic LSC self-renewal program and suggest MSI2 as a potential therapeutic target for myeloid leukemia. PMID:25664853

Argonne National Laboratory Li-alloy/FeS cell testing and R and D programs

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

Gay, E.C.

1982-01-01

Groups of 12 or more identical Li-alloy/FeS cells fabricated by Eagle-Picher Industries, Inc. and Gould Inc. were operated at Argonne National Laboratory (ANL) in the status cell test program to obtain data for statistical analysis of cell cycle life and failure modes. The cells were full-size electric vehicle battery cells (150 to 350 Ah capacity) and they were cycled at the 4-h discharge rate and 8-h charge rate. The end of life was defined as a 20% loss of capacity or a decrease in the coulombic efficiency to less than 95%. Seventy-four cells (six groups of identical cells) were cycle-lifemore » tested and the results were analyzed statistically. The ultimate goal of this analysis was to predict cell and battery reliability. Testing of groups of identical cells also provided a means of identifying common failure modes which were eliminated by cell design changes. Mean time to failure (MTTF) for the cells based on the Weibull distribution is presented.« less

A gene expression biomarker accurately predicts estrogen ...

EPA Pesticide Factsheets

The EPA’s vision for the Endocrine Disruptor Screening Program (EDSP) in the 21st Century (EDSP21) includes utilization of high-throughput screening (HTS) assays coupled with computational modeling to prioritize chemicals with the goal of eventually replacing current Tier 1 screening tests. The ToxCast program currently includes 18 HTS in vitro assays that evaluate the ability of chemicals to modulate estrogen receptor α (ERα), an important endocrine target. We propose microarray-based gene expression profiling as a complementary approach to predict ERα modulation and have developed computational methods to identify ERα modulators in an existing database of whole-genome microarray data. The ERα biomarker consisted of 46 ERα-regulated genes with consistent expression patterns across 7 known ER agonists and 3 known ER antagonists. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression data sets from experiments in MCF-7 cells. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% or 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) OECD ER reference chemicals including “very weak” agonists and replicated predictions based on 18 in vitro ER-associated HTS assays. For 114 chemicals present in both the HTS data and the MCF-7 c

High speed turboprop aeroacoustic study (counterrotation). Volume 2: Computer programs

NASA Technical Reports Server (NTRS)

Whitfield, C. E.; Mani, R.; Gliebe, P. R.

1990-01-01

The isolated counterrotating high speed turboprop noise prediction program developed and funded by GE Aircraft Engines was compared with model data taken in the GE Aircraft Engines Cell 41 anechoic facility, the Boeing Transonic Wind Tunnel, and in the NASA-Lewis 8 x 6 and 9 x 15 wind tunnels. The predictions show good agreement with measured data under both low and high speed simulated flight conditions. The installation effect model developed for single rotation, high speed turboprops was extended to include counter rotation. The additional effect of mounting a pylon upstream of the forward rotor was included in the flow field modeling. A nontraditional mechanism concerning the acoustic radiation from a propeller at angle of attack was investigated. Predictions made using this approach show results that are in much closer agreement with measurement over a range of operating conditions than those obtained via traditional fluctuating force methods. The isolated rotors and installation effects models were combined into a single prediction program. The results were compared with data taken during the flight test of the B727/UDF (trademark) engine demonstrator aircraft.

High speed turboprop aeroacoustic study (counterrotation). Volume 2: Computer programs

NASA Astrophysics Data System (ADS)

Whitfield, C. E.; Mani, R.; Gliebe, P. R.

1990-07-01

The isolated counterrotating high speed turboprop noise prediction program developed and funded by GE Aircraft Engines was compared with model data taken in the GE Aircraft Engines Cell 41 anechoic facility, the Boeing Transonic Wind Tunnel, and in the NASA-Lewis 8 x 6 and 9 x 15 wind tunnels. The predictions show good agreement with measured data under both low and high speed simulated flight conditions. The installation effect model developed for single rotation, high speed turboprops was extended to include counter rotation. The additional effect of mounting a pylon upstream of the forward rotor was included in the flow field modeling. A nontraditional mechanism concerning the acoustic radiation from a propeller at angle of attack was investigated. Predictions made using this approach show results that are in much closer agreement with measurement over a range of operating conditions than those obtained via traditional fluctuating force methods. The isolated rotors and installation effects models were combined into a single prediction program. The results were compared with data taken during the flight test of the B727/UDF (trademark) engine demonstrator aircraft.

Vacuolar and cytoskeletal dynamics during elicitor-induced programmed cell death in tobacco BY-2 cells.

PubMed

Higaki, Takumi; Kadota, Yasuhiro; Goh, Tatsuaki; Hayashi, Teruyuki; Kutsuna, Natsumaro; Sano, Toshio; Hasezawa, Seiichiro; Kuchitsu, Kazuyuki

2008-09-01

Responses of plant cells to environmental stresses often involve morphological changes, differentiation and redistribution of various organelles and cytoskeletal network. Tobacco BY-2 cells provide excellent model system for in vivo imaging of these intracellular events. Treatment of the cell cycle-synchronized BY-2 cells with a proteinaceous oomycete elicitor, cryptogein, induces highly synchronous programmed cell death (PCD) and provide a model system to characterize vacuolar and cytoskeletal dynamics during the PCD. Sequential observation revealed dynamic reorganization of the vacuole and actin microfilaments during the execution of the PCD. We further characterized the effects cryptogein on mitotic microtubule organization in cell cycle-synchronized cells. Cryptogein treatment at S phase inhibited formation of the preprophase band, a cortical microtubule band that predicts the cell division site. Cortical microtubules kept their random orientation till their disruption that gradually occurred during the execution of the PCD twelve hours after the cryptogein treatment. Possible molecular mechanisms and physiological roles of the dynamic behavior of the organelles and cytoskeletal network in the pathogenic signal-induced PCD are discussed.

Advances in the Treatment of Non-small Cell Lung Cancer: Focus on Nivolumab, Pembrolizumab, and Atezolizumab.

PubMed

Leventakos, Konstantinos; Mansfield, Aaron S

2016-10-01

Immunotherapy is revolutionizing the treatment of non-small cell lung cancer (NSCLC). Immune checkpoint inhibitors, including programmed cell death protein 1 (PD-1) and programmed cell death ligand 1 (PD-L1) monoclonal antibodies, are being introduced to routine clinical practice. This review summarizes clinical trials of nivolumab, pembrolizumab, and atezolizumab in patients with NSCLC. These agents have efficacy against NSCLC and a unique toxicity profile. The role of PD-L1 as a predictive biomarker is still unclear, partially because of the nuances of PD-L1 testing. These novel therapies also challenge our existing methodologies of radiologic assessment and efficacy analysis. This new era of immunotherapy has ushered in as much hope for patients as questions from physicians that need to be answered to clarify the optimal use of these agents.

SONOS Nonvolatile Memory Cell Programming Characteristics

NASA Technical Reports Server (NTRS)

MacLeod, Todd C.; Phillips, Thomas A.; Ho, Fat D.

2010-01-01

Silicon-oxide-nitride-oxide-silicon (SONOS) nonvolatile memory is gaining favor over conventional EEPROM FLASH memory technology. This paper characterizes the SONOS write operation using a nonquasi-static MOSFET model. This includes floating gate charge and voltage characteristics as well as tunneling current, voltage threshold and drain current characterization. The characterization of the SONOS memory cell predicted by the model closely agrees with experimental data obtained from actual SONOS memory cells. The tunnel current, drain current, threshold voltage and read drain current all closely agreed with empirical data.

Epigenetic Networks Regulate the Transcriptional Program in Memory and Terminally Differentiated CD8+ T Cells.

PubMed

Rodriguez, Ramon M; Suarez-Alvarez, Beatriz; Lavín, José L; Mosén-Ansorena, David; Baragaño Raneros, Aroa; Márquez-Kisinousky, Leonardo; Aransay, Ana M; Lopez-Larrea, Carlos

2017-01-15

Epigenetic mechanisms play a critical role during differentiation of T cells by contributing to the formation of stable and heritable transcriptional patterns. To better understand the mechanisms of memory maintenance in CD8 + T cells, we performed genome-wide analysis of DNA methylation, histone marking (acetylated lysine 9 in histone H3 and trimethylated lysine 9 in histone), and gene-expression profiles in naive, effector memory (EM), and terminally differentiated EM (TEMRA) cells. Our results indicate that DNA demethylation and histone acetylation are coordinated to generate the transcriptional program associated with memory cells. Conversely, EM and TEMRA cells share a very similar epigenetic landscape. Nonetheless, the TEMRA transcriptional program predicts an innate immunity phenotype associated with genes never reported in these cells, including several mediators of NK cell activation (VAV3 and LYN) and a large array of NK receptors (e.g., KIR2DL3, KIR2DL4, KIR2DL1, KIR3DL1, KIR2DS5). In addition, we identified up to 161 genes that encode transcriptional regulators, some of unknown function in CD8 + T cells, and that were differentially expressed in the course of differentiation. Overall, these results provide new insights into the regulatory networks involved in memory CD8 + T cell maintenance and T cell terminal differentiation. Copyright © 2017 by The American Association of Immunologists, Inc.

Progress of Ongoing NASA Lithium-Ion Cell Verification Testing for Aerospace Applications

NASA Technical Reports Server (NTRS)

McKissock, Barbara I.; Manzo, Michelle A.; Miller, Thomas B.; Reid, Concha M.; Bennett, William R.; Gemeiner, Russel

2008-01-01

A Lithium-ion Verification and Validation Program with the purpose to assess the capabilities of current aerospace lithium-ion (Li-ion) battery cells to perform in a low-earth-orbit (LEO) regime was initiated in 2002. This program involves extensive characterization and LEO life testing at ten different combinations of depth-of-discharge, temperature, and end-of-charge voltage. The test conditions selected for the life tests are defined as part of a statistically designed test matrix developed to determine the effects of operating conditions on performance and life of Li-ion cells. Results will be used to model and predict cell performance and degradation as a function of test operating conditions. Testing is being performed at the Naval Surface Warfare Center/Crane Division in Crane, Indiana. Testing was initiated in September 2004 with 40 Ah cells from Saft and 30 Ah cells from Lithion. The test program has been expanded with the addition of modules composed of 18650 cells from ABSL Power Solutions in April 2006 and the addition of 50 Ah cells from Mine Safety Appliances Co. (MSA) in June 2006. Preliminary results showing the average voltage and average available discharge capacity for the Saft and Lithion packs at the test conditions versus cycles are presented.

An Update on the Lithium-Ion Cell Low-Earth-Orbit Verification Test Program

NASA Technical Reports Server (NTRS)

Reid, Concha M.; Manzo, Michelle A.; Miller, Thomas B.; McKissock, Barbara I.; Bennett, William

2007-01-01

A Lithium-Ion Cell Low-Earth-Orbit Verification Test Program is being conducted by NASA Glenn Research Center to assess the performance of lithium-ion (Li-ion) cells over a wide range of low-Earth-orbit (LEO) conditions. The data generated will be used to build an empirical model for Li-ion batteries. The goal of the modeling will be to develop a tool to predict the performance and cycle life of Li-ion batteries operating at a specified set of mission conditions. Using this tool, mission planners will be able to design operation points of the battery system while factoring in mission requirements and the expected life and performance of the batteries. Test conditions for the program were selected via a statistical design of experiments to span a range of feasible operational conditions for LEO aerospace applications. The variables under evaluation are temperature, depth-of-discharge (DOD), and end-of-charge voltage (EOCV). The baseline matrix was formed by generating combinations from a set of three values for each variable. Temperature values are 10 C, 20 C and 30 C. Depth-of-discharge values are 20%, 30% and 40%. EOCV values are 3.85 V, 3.95 V, and 4.05 V. Test conditions for individual cells may vary slightly from the baseline test matrix depending upon the cell manufacturer s recommended operating conditions. Cells from each vendor are being evaluated at each of ten sets of test conditions. Cells from four cell manufacturers are undergoing life cycle tests. Life cycling on the first sets of cells began in September 2004. These cells consist of Saft 40 ampere-hour (Ah) cells and Lith ion 30 Ah cells. These cells have achieved over 10,000 cycles each, equivalent to about 20 months in LEO. In the past year, the test program has expanded to include the evaluation of Mine Safety Appliances (MSA) 50 Ah cells and ABSL battery modules. The MSA cells will begin life cycling in October 2006. The ABSL battery modules consist of commercial Sony hard carbon 18650 lithium-ion cells configured in series and parallel combinations to create nominal 14.4 volt, 3 Ah packs (4s-2p). These modules have accumulated approximately 3000 cycles. Results on the performance of the cells and modules will be presented in this paper. The life prediction and performance model for Li-ion cells in LEO will be built by analyzing the data statistically and performing regression analysis. Cells are being cycled to failure so that differences in performance trends that occur at different stages in the life of the cell can be observed and accurately modeled. Cell testing is being performed at the Naval Surface Warfare Center in Crane, IN.

Describing Myxococcus xanthus Aggregation Using Ostwald Ripening Equations for Thin Liquid Films

PubMed Central

Bahar, Fatmagül; Pratt-Szeliga, Philip C.; Angus, Stuart; Guo, Jiaye; Welch, Roy D.

2014-01-01

When starved, a swarm of millions of Myxococcus xanthus cells coordinate their movement from outward swarming to inward coalescence. The cells then execute a synchronous program of multicellular development, arranging themselves into dome shaped aggregates. Over the course of development, about half of the initial aggregates disappear, while others persist and mature into fruiting bodies. This work seeks to develop a quantitative model for aggregation that accurately simulates which will disappear and which will persist. We analyzed time-lapse movies of M. xanthus development, modeled aggregation using the equations that describe Ostwald ripening of droplets in thin liquid films, and predicted the disappearance and persistence of aggregates with an average accuracy of 85%. We then experimentally validated a prediction that is fundamental to this model by tracking individual fluorescent cells as they moved between aggregates and demonstrating that cell movement towards and away from aggregates correlates with aggregate disappearance. Describing development through this model may limit the number and type of molecular genetic signals needed to complete M. xanthus development, and it provides numerous additional testable predictions. PMID:25231319

Indium phosphide solar cell research in the US: Comparison with nonphotovoltaic sources

NASA Technical Reports Server (NTRS)

Weinberg, I.; Swartz, C. K.; Hart, R. E., Jr.

1989-01-01

Highlights of the InP solar cell research program are presented. Homojunction cells with AMO efficiences approaching 19 percent were demonstrated while 17 percent was achieved for indium tin oxide (ITO)/InP cells. The superior radiation resistance of these latter two cell configurations over both Si and GaAs were demonstrated. InP cells on board the LIPS III satellite show no degradation after more than a year in orbit. Computer modeling calculations were directed toward radiation damage predictions and the specification of concentrator cell parameters. Computed array specific powers, for a specific orbit, are used to compare the performance of an InP solar cell array to solar dynamic and nuclear systems.

Season of conception in rural Gambia affects DNA methylation at putative human metastable epialleles

USDA-ARS?s Scientific Manuscript database

Throughout most of the mammalian genome, genetically regulated developmental programming establishes diverse yet predictable epigenetic states across differentiated cells and tissues. At metastable epialleles (MEs), conversely, epigenotype is established stochastically in the early embryo then maint...

Determining Regulatory Networks Governing the Differentiation of Embryonic Stem Cells to Pancreatic Lineage

NASA Astrophysics Data System (ADS)

Banerjee, Ipsita

2009-03-01

Knowledge of pathways governing cellular differentiation to specific phenotype will enable generation of desired cell fates by careful alteration of the governing network by adequate manipulation of the cellular environment. With this aim, we have developed a novel method to reconstruct the underlying regulatory architecture of a differentiating cell population from discrete temporal gene expression data. We utilize an inherent feature of biological networks, that of sparsity, in formulating the network reconstruction problem as a bi-level mixed-integer programming problem. The formulation optimizes the network topology at the upper level and the network connectivity strength at the lower level. The method is first validated by in-silico data, before applying it to the complex system of embryonic stem (ES) cell differentiation. This formulation enables efficient identification of the underlying network topology which could accurately predict steps necessary for directing differentiation to subsequent stages. Concurrent experimental verification demonstrated excellent agreement with model prediction.

Evaluation program for secondary spacecraft cells

NASA Technical Reports Server (NTRS)

Christy, D. E.; Harkness, J. D.

1973-01-01

A life cycle test of secondary electric batteries for spacecraft applications was conducted. A sample number of nickel cadmium batteries were subjected to general performance tests to determine the limit of their actual capabilities. Weaknesses discovered in cell design are reported and aid in research and development efforts toward improving the reliability of spacecraft batteries. A statistical analysis of the life cycle prediction and cause of failure versus test conditions is provided.

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

Thrall, Brian D.; Minard, Kevin R.; Teeguarden, Justin G.

A Cooperative Research and Development Agreement (CRADA) was sponsored by Battelle Memorial Institute (Battelle, Columbus), to initiate a collaborative research program across multiple Department of Energy (DOE) National Laboratories aimed at developing a suite of new capabilities for predictive toxicology. Predicting the potential toxicity of emerging classes of engineered nanomaterials was chosen as one of two focusing problems for this program. PNNL’s focus toward this broader goal was to refine and apply experimental and computational tools needed to provide quantitative understanding of nanoparticle dosimetry for in vitro cell culture systems, which is necessary for comparative risk estimates for different nanomaterialsmore » or biological systems. Research conducted using lung epithelial and macrophage cell models successfully adapted magnetic particle detection and fluorescent microscopy technologies to quantify uptake of various forms of engineered nanoparticles, and provided experimental constraints and test datasets for benchmark comparison against results obtained using an in vitro computational dosimetry model, termed the ISSD model. The experimental and computational approaches developed were used to demonstrate how cell dosimetry is applied to aid in interpretation of genomic studies of nanoparticle-mediated biological responses in model cell culture systems. The combined experimental and theoretical approach provides a highly quantitative framework for evaluating relationships between biocompatibility of nanoparticles and their physical form in a controlled manner.« less

Screening for Cryptococcal Antigenaemia in Patients Accessing an Antiretroviral Treatment Program in South Africa

PubMed Central

Jarvis, Joseph N; Lawn, Stephen D; Vogt, Monica; Bangani, Nonzwakazi; Wood, Robin; Harrison, Thomas S

2009-01-01

Background Cryptococcal meningitis is a leading cause of death in AIDS patients and contributes substantially to the high early mortality in antiretroviral treatment (ART) programs in low-resource settings. Screening for cryptococcal antigen (CRAG) in patients enrolling in ART programs may identify those at risk of cryptococcal meningitis and permit targeted use of pre-emptive therapy. Methods In this retrospective study, CRAG was measured in stored plasma samples obtained from patients as they enrolled in a well characterised ART cohort in South Africa. The predictive value of screening for CRAG prior to ART for development of microbiologically confirmed cryptococcal meningitis or death during the first year of follow-up was determined. Results Of 707 participants with a baseline median CD4 count of 97 (IQR 46-157) cells/μL, 46 (7%) had a positive CRAG. Antigenaemia was 100% sensitive for predicting development of cryptococcal meningitis during the first year of ART and in multivariate analysis was an independent predictor of mortality (AHR 3.2, 95%CI 1.5-6.6). Most (92%) cases of cryptococcal meningitis developed in patients with a CD4 count ≤100 cells/μL. In this sub-set of patients, a CRAG titre ≥1 in 8 was 100% sensitive and 96% specific for predicting incident cryptococcal meningitis during the first year of ART in those with no previous history of the disease. Conclusions CRAG screening prior to commencing ART in patients with a CD4 count ≤100 cells/μL is highly effective at identifying those at risk of cryptococcal meningitis and death and might permit implementation of a targeted pre-emptive treatment strategy. PMID:19222372

MuPeXI: prediction of neo-epitopes from tumor sequencing data.

PubMed

Bjerregaard, Anne-Mette; Nielsen, Morten; Hadrup, Sine Reker; Szallasi, Zoltan; Eklund, Aron Charles

2017-09-01

Personalization of immunotherapies such as cancer vaccines and adoptive T cell therapy depends on identification of patient-specific neo-epitopes that can be specifically targeted. MuPeXI, the mutant peptide extractor and informer, is a program to identify tumor-specific peptides and assess their potential to be neo-epitopes. The program input is a file with somatic mutation calls, a list of HLA types, and optionally a gene expression profile. The output is a table with all tumor-specific peptides derived from nucleotide substitutions, insertions, and deletions, along with comprehensive annotation, including HLA binding and similarity to normal peptides. The peptides are sorted according to a priority score which is intended to roughly predict immunogenicity. We applied MuPeXI to three tumors for which predicted MHC-binding peptides had been screened for T cell reactivity, and found that MuPeXI was able to prioritize immunogenic peptides with an area under the curve of 0.63. Compared to other available tools, MuPeXI provides more information and is easier to use. MuPeXI is available as stand-alone software and as a web server at http://www.cbs.dtu.dk/services/MuPeXI .

Immunoinformatics Features Linked to Leishmania Vaccine Development: Data Integration of Experimental and In Silico Studies

PubMed Central

Brito, Rory C. F.; Guimarães, Frederico G.; Velloso, João P. L.; Corrêa-Oliveira, Rodrigo; Ruiz, Jeronimo C.; Reis, Alexandre B.; Resende, Daniela M.

2017-01-01

Leishmaniasis is a wide-spectrum disease caused by parasites from Leishmania genus. There is no human vaccine available and it is considered by many studies as apotential effective tool for disease control. To discover novel antigens, computational programs have been used in reverse vaccinology strategies. In this work, we developed a validation antigen approach that integrates prediction of B and T cell epitopes, analysis of Protein-Protein Interaction (PPI) networks and metabolic pathways. We selected twenty candidate proteins from Leishmania tested in murine model, with experimental outcome published in the literature. The predictions for CD4+ and CD8+ T cell epitopes were correlated with protection in experimental outcomes. We also mapped immunogenic proteins on PPI networks in order to find Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with them. Our results suggest that non-protective antigens have lowest frequency of predicted T CD4+ and T CD8+ epitopes, compared with protective ones. T CD4+ and T CD8+ cells are more related to leishmaniasis protection in experimental outcomes than B cell predicted epitopes. Considering KEGG analysis, the proteins considered protective are connected to nodes with few pathways, including those associated with ribosome biosynthesis and purine metabolism. PMID:28208616

Immunoinformatics Features Linked to Leishmania Vaccine Development: Data Integration of Experimental and In Silico Studies.

PubMed

Brito, Rory C F; Guimarães, Frederico G; Velloso, João P L; Corrêa-Oliveira, Rodrigo; Ruiz, Jeronimo C; Reis, Alexandre B; Resende, Daniela M

2017-02-10

Leishmaniasis is a wide-spectrum disease caused by parasites from Leishmania genus. There is no human vaccine available and it is considered by many studies as apotential effective tool for disease control. To discover novel antigens, computational programs have been used in reverse vaccinology strategies. In this work, we developed a validation antigen approach that integrates prediction of B and T cell epitopes, analysis of Protein-Protein Interaction (PPI) networks and metabolic pathways. We selected twenty candidate proteins from Leishmania tested in murine model, with experimental outcome published in the literature. The predictions for CD4⁺ and CD8⁺ T cell epitopes were correlated with protection in experimental outcomes. We also mapped immunogenic proteins on PPI networks in order to find Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with them. Our results suggest that non-protective antigens have lowest frequency of predicted T CD4⁺ and T CD8⁺ epitopes, compared with protective ones. T CD4⁺ and T CD8⁺ cells are more related to leishmaniasis protection in experimental outcomes than B cell predicted epitopes. Considering KEGG analysis, the proteins considered protective are connected to nodes with few pathways, including those associated with ribosome biosynthesis and purine metabolism.

Synthetic mixed-signal computation in living cells

PubMed Central

Rubens, Jacob R.; Selvaggio, Gianluca; Lu, Timothy K.

2016-01-01

Living cells implement complex computations on the continuous environmental signals that they encounter. These computations involve both analogue- and digital-like processing of signals to give rise to complex developmental programs, context-dependent behaviours and homeostatic activities. In contrast to natural biological systems, synthetic biological systems have largely focused on either digital or analogue computation separately. Here we integrate analogue and digital computation to implement complex hybrid synthetic genetic programs in living cells. We present a framework for building comparator gene circuits to digitize analogue inputs based on different thresholds. We then demonstrate that comparators can be predictably composed together to build band-pass filters, ternary logic systems and multi-level analogue-to-digital converters. In addition, we interface these analogue-to-digital circuits with other digital gene circuits to enable concentration-dependent logic. We expect that this hybrid computational paradigm will enable new industrial, diagnostic and therapeutic applications with engineered cells. PMID:27255669

Atezolizumab: feasible second-line therapy for patients with non-small cell lung cancer? A review of efficacy, safety and place in therapy.

PubMed

Jean, Fanny; Tomasini, Pascale; Barlesi, Fabrice

2017-12-01

Advanced non-small cell lung cancer (NSCLC) prognosis is still poor and has recently been reformed by the development of immune checkpoint inhibitors and the approval of anti-PD-1 (programmed cell-death 1) treatments such as nivolumab and pembrolizumab in second line. More recently, atezolizumab (MDPL 3280A), a programmed cell-death-ligand 1 (PD-L1) inhibitor, was also studied in this setting. Here, we report a review of the literature assessing the efficacy, safety, and place of atezolizumab in the second-line treatment of advanced NSCLC. We performed a literature search of PubMed, American Society of Clinical Oncology, European Society of Medical Oncology and World Conference on Lung Cancer meetings. Atezolizumab showed a good tolerance profile and efficacy in comparison with docetaxel for second-line treatment of advanced NSCLC. Potential predictive biomarkers also have to be assessed.

Atezolizumab: feasible second-line therapy for patients with non-small cell lung cancer? A review of efficacy, safety and place in therapy

PubMed Central

Jean, Fanny; Tomasini, Pascale; Barlesi, Fabrice

2017-01-01

Advanced non-small cell lung cancer (NSCLC) prognosis is still poor and has recently been reformed by the development of immune checkpoint inhibitors and the approval of anti-PD-1 (programmed cell-death 1) treatments such as nivolumab and pembrolizumab in second line. More recently, atezolizumab (MDPL 3280A), a programmed cell-death-ligand 1 (PD-L1) inhibitor, was also studied in this setting. Here, we report a review of the literature assessing the efficacy, safety, and place of atezolizumab in the second-line treatment of advanced NSCLC. We performed a literature search of PubMed, American Society of Clinical Oncology, European Society of Medical Oncology and World Conference on Lung Cancer meetings. Atezolizumab showed a good tolerance profile and efficacy in comparison with docetaxel for second-line treatment of advanced NSCLC. Potential predictive biomarkers also have to be assessed. PMID:29449897

Programming stress-induced altruistic death in engineered bacteria

PubMed Central

Tanouchi, Yu; Pai, Anand; Buchler, Nicolas E; You, Lingchong

2012-01-01

Programmed death is often associated with a bacterial stress response. This behavior appears paradoxical, as it offers no benefit to the individual. This paradox can be explained if the death is ‘altruistic': the killing of some cells can benefit the survivors through release of ‘public goods'. However, the conditions where bacterial programmed death becomes advantageous have not been unambiguously demonstrated experimentally. Here, we determined such conditions by engineering tunable, stress-induced altruistic death in the bacterium Escherichia coli. Using a mathematical model, we predicted the existence of an optimal programmed death rate that maximizes population growth under stress. We further predicted that altruistic death could generate the ‘Eagle effect', a counter-intuitive phenomenon where bacteria appear to grow better when treated with higher antibiotic concentrations. In support of these modeling insights, we experimentally demonstrated both the optimality in programmed death rate and the Eagle effect using our engineered system. Our findings fill a critical conceptual gap in the analysis of the evolution of bacterial programmed death, and have implications for a design of antibiotic treatment. PMID:23169002

Energy-conserving programming of VVI pacemakers: a telemetry-supported, long-term, follow-up study.

PubMed

Klein, H H; Knake, W

1990-06-01

Thirty patients with VVI pacemakers (Quantum 253-09, 253-19, Intermedics Inc., Freeport, TX) were observed for a mean of 65 months. Within 12 months after implantation, optimized output programming was performed in 29 patients. This included a decrease in pulse amplitude (22 patients), pulse width (4 patients), and/or pacing rate (11 patients). After 65 months postimplantation, telemetered battery voltage and battery impedance were compared with the predicted values expected when the pulse generator constantly stimulates at nominal program conditions (heart rate 72.3 beats/min, pulse amplitude 5.4 V, pulse width 0.61 ms). Instead of an expected cell voltage of 2.6 V and a cell impedance of 10 k omega mean telemetered values amounted to 2.78 V and 1.4 k omega, respectively. These data correspond to a battery age of 12-15 months at nominal program conditions. This long-term follow-up study suggests that adequate programming will extend battery longevity and thus pulse generator survival in many patients.

Modeling Reproductive Toxicity for Chemical Prioritization into an Integrated Testing Strategy

EPA Science Inventory

The EPA ToxCast research program uses a high-throughput screening (HTS) approach for predicting the toxicity of large numbers of chemicals. Phase-I tested 309 well-characterized chemicals in over 500 assays of different molecular targets, cellular responses and cell-states. Of th...

Prediction of energy balance and utilization for solar electric cars

NASA Astrophysics Data System (ADS)

Cheng, K.; Guo, L. M.; Wang, Y. K.; Zafar, M. T.

2017-11-01

Solar irradiation and ambient temperature are characterized by region, season and time-domain, which directly affects the performance of solar energy based car system. In this paper, the model of solar electric cars used was based in Xi’an. Firstly, the meteorological data are modelled to simulate the change of solar irradiation and ambient temperature, and then the temperature change of solar cell is calculated using the thermal equilibrium relation. The above work is based on the driving resistance and solar cell power generation model, which is simulated under the varying radiation conditions in a day. The daily power generation and solar electric car cruise mileage can be predicted by calculating solar cell efficiency and power. The above theoretical approach and research results can be used in the future for solar electric car program design and optimization for the future developments.

A mathematical model of electrolyte and fluid transport across corneal endothelium.

PubMed

Fischbarg, J; Diecke, F P J

2005-01-01

To predict the behavior of a transporting epithelium by intuitive means can be complex and frustrating. As the number of parameters to be considered increases beyond a few, the task can be termed impossible. The alternative is to model epithelial behavior by mathematical means. For that to be feasible, it has been presumed that a large amount of experimental information is required, so as to be able to use known values for the majority of kinetic parameters. However, in the present case, we are modeling corneal endothelial behavior beginning with experimental values for only five of eleven parameters. The remaining parameter values are calculated assuming cellular steady state and using algebraic software. With that as base, as in preceding treatments but with a distribution of channels/transporters suited to the endothelium, temporal cell and tissue behavior are computed by a program written in Basic that monitors changes in chemical and electrical driving forces across cell membranes and the paracellular pathway. We find that the program reproduces quite well the behaviors experimentally observed for the translayer electrical potential difference and rate of fluid transport, (a) in the steady state, (b) after perturbations by changes in ambient conditions HCO3-, Na+, and Cl- concentrations), and (c) after challenge by inhibitors (ouabain, DIDS, Na+- and Cl(-)-channel inhibitors). In addition, we have used the program to compare predictions of translayer fluid transport by two competing theories, electro-osmosis and local osmosis. Only predictions using electro-osmosis fit all the experimental data.

Programmed Cell Death Ligand 1 Expression in Primary Central Nervous System Lymphomas: A Clinicopathological Study.

PubMed

Hayano, Azusa; Komohara, Yoshihiro; Takashima, Yasuo; Takeya, Hiroto; Homma, Jumpei; Fukai, Junya; Iwadate, Yasuo; Kajiwara, Koji; Ishizawa, Shin; Hondoh, Hiroaki; Yamanaka, Ryuya

2017-10-01

Programmed cell death ligand 1 (PD-L1)/programmed cell death 1 (PD-1) have been shown to predict response to PD-L1/PD-1-targeted therapy. We analyzed PD-L1 expression in primary central nervous system lymphomas (PCNSLs). PD-L1 protein and mRNA expression were evaluated in 64 PCNSL tissue samples. IFN-γ, IL-10, CD4, and CD8 mRNA expression was also evaluated. PD-L1 protein was detected in tumor cells in 2 (4.1%) cases and in tumor microenvironments in 25 (52%) cases. PD-L1 mRNA positively correlated with IFN-γ (p=0.0024) and CD4 (p=0.0005) mRNA expression. IFN-γ mRNA positively correlated with CD8 mRNA expression (p=0.0001). Furthermore, tumor cell PD-L1 expression correlated positively with overall survival (p=0.0177), whereas microenvironmental PD-L1 expression exhibited an insignificant negative trend with overall survival (p=0.188). PD-L1 was expressed on both tumor and/or tumor-infiltrating immune cells in PCNSL. The biological roles of this marker warrant further investigation. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

The effects of simulated hypogravity on murine bone marrow cells

NASA Technical Reports Server (NTRS)

Lawless, Desales

1989-01-01

Mouse bone marrow cells grown in complete medium at unit gravity were compared with a similar population cultured in conditions that mimic some aspects of microgravity. After the cells adjusted to the conditions that simulated microgravity, they proliferated as fetal or oncogenic populations; their numbers doubled in twelve hour periods. Differentiated subpopulations were depleted from the heterogeneous mixture with time and the undifferentiated hematopoietic stem cells increased in numbers. The cells in the control groups in unit gravity and those in the bioreactors in conditions of microgravity were monitored under a number of parameters. Each were phenotyped as to cell surface antigens using a panel of monoclonal antibodies and flow cytometry. Other parameters compared included: pH, glucose uptake, oxygen consumption and carbon-dioxide production. Nuclear DNA was monitored by flow cytometry. Functional responses were studied by mitogenic stimulation by various lectins. The importance of these findings should have relevance to the space program. Cells should behave predictably in zero gravity; specific populations can be eliminated from diverse populations and other populations isolated. The availability of stem cell populations will enhance both bone marrow and gene transplant programs. Stem cells will permit developmental biologists study the paths of hematopoiesis.

Computer Simulation of Embryonic Systems: What can a ...

EPA Pesticide Factsheets

(1) Standard practice for assessing developmental toxicity is the observation of apical endpoints (intrauterine death, fetal growth retardation, structural malformations) in pregnant rats/rabbits following exposure during organogenesis. EPA’s computational toxicology research program (ToxCast) generated vast in vitro cellular and molecular effects data on >1858 chemicals in >600 high-throughput screening (HTS) assays. The diversity of assays has been increased for developmental toxicity with several HTS platforms, including the devTOX-quickPredict assay from Stemina Biomarker Discovery utilizing the human embryonic stem cell line (H9). Translating these HTS data into higher order-predictions of developmental toxicity is a significant challenge. Here, we address the application of computational systems models that recapitulate the kinematics of dynamical cell signaling networks (e.g., SHH, FGF, BMP, retinoids) in a CompuCell3D.org modeling environment. Examples include angiogenesis (angiodysplasia) and dysmorphogenesis. Being numerically responsive to perturbation, these models are amenable to data integration for systems Toxicology and Adverse Outcome Pathways (AOPs). The AOP simulation outputs predict potential phenotypes based on the in vitro HTS data ToxCast. A heuristic computational intelligence framework that recapitulates the kinematics of dynamical cell signaling networks in the embryo, together with the in vitro profiling data, produce quantitative pr

Computational Modeling and Simulation of Developmental ...

EPA Pesticide Factsheets

Standard practice for assessing developmental toxicity is the observation of apical endpoints (intrauterine death, fetal growth retardation, structural malformations) in pregnant rats/rabbits following exposure during organogenesis. EPA’s computational toxicology research program (ToxCast) generated vast in vitro cellular and molecular effects data on >1858 chemicals in >600 high-throughput screening (HTS) assays. The diversity of assays has been increased for developmental toxicity with several HTS platforms, including the devTOX-quickPredict assay from Stemina Biomarker Discovery utilizing the human embryonic stem cell line (H9). Translating these HTS data into higher order-predictions of developmental toxicity is a significant challenge. Here, we address the application of computational systems models that recapitulate the kinematics of dynamical cell signaling networks (e.g., SHH, FGF, BMP, retinoids) in a CompuCell3D.org modeling environment. Examples include angiogenesis (angiodysplasia) and dysmorphogenesis. Being numerically responsive to perturbation, these models are amenable to data integration for systems Toxicology and Adverse Outcome Pathways (AOPs). The AOP simulation outputs predict potential phenotypes based on the in vitro HTS data ToxCast. A heuristic computational intelligence framework that recapitulates the kinematics of dynamical cell signaling networks in the embryo, together with the in vitro profiling data, produce quantitative predic

Immunotherapy: a new treatment paradigm in bladder cancer

PubMed Central

Davarpanah, Nicole N.; Yuno, Akira; Trepel, Jane B.; Apolo, Andrea B.

2017-01-01

Purpose of review T-cell checkpoint blockade has become a dynamic immunotherapy for bladder cancer. In 2016, atezolizumab, an immune checkpoint inhibitor, became the first new drug approved in metastatic urothelial carcinoma (mUC) in over 30 years. In 2017, nivolumab was also approved for the same indication. This overview of checkpoint inhibitors in clinical trials focuses on novel immunotherapy combinations, predictive biomarkers including mutational load and neoantigen identification, and an evaluation of the future of bladder cancer immunotherapy. Recent findings Programed cell death protein 1/programed death-ligand 1 (PD-1/PD-L1) checkpoint inhibitors have achieved durable clinical responses in a subset of previously treated and treatment-naïve patients with mUC. The combination of PD-1 and cytotoxic T-lymphocyte antigen 4 (CTLA-4) has successfully improved response rates in multiple malignancies, and combination studies are underway in many tumor types, including bladder cancer, combining T-cell checkpoint blockade with other checkpoint agents and immunomodulatory therapies. Strong tumor responses to checkpoint blockade have been reported to be positively associated with expression of PD-L1 on tumor and tumor-infiltrating immune cells and with increased mutation-associated neoantigen load, which may lead to the development of predictive biomarkers. Summary Recent clinical evidence suggests that mUC is susceptible to T-cell checkpoint blockade. A global effort is underway to achieve higher response rates and more durable remissions, accelerate the development of immunotherapies, employ combination therapies, and test novel immune targets. PMID:28306559

Endothelial necrosis at 1h post-burn predicts progression of tissue injury

PubMed Central

Hirth, Douglas; McClain, Steve A.; Singer, Adam J.; Clark, Richard A.F.

2013-01-01

Burn injury progression has not been well characterized at the cellular level. To define burn injury progression in terms of cell death, histopathologic spatiotemporal relationships of cellular necrosis and apoptosis were investigated in a validated porcine model of vertical burn injury progression. Cell necrosis was identified by High Mobility Group Box 1 protein and apoptosis by Caspase 3a staining of tissue samples taken 1h, 24h and 7 days post-burn. Level of endothelial cell necrosis at 1h was predictive of level of apoptosis at 24h (Pearson's r=0.87) and of level of tissue necrosis at 7 days (Pearson's r=0.87). Furthermore, endothelial cell necrosis was deeper than interstitial cell necrosis at 1h (p<0.001). Endothelial cell necrosis at 1h divided the zone of injury progression (Jackson's zone of stasis) into an upper subzone with necrotic endothelial cells and initially viable adnexal and interstitial cells at 1h that progressed to necrosis by 24h, and a lower zone with initially viable endothelial cells at 1h, but necrosis and apoptosis of all cell types by 24h. Importantly, this spatiotemporal series of events and rapid progression resembles myocardial infarction and stroke, and implicates mechanisms of these injuries, ischemia, ischemia reperfusion, and programmed cell death, in burn progression. PMID:23627744

A genomic lifespan program that reorganises the young adult brain is targeted in schizophrenia.

PubMed

Skene, Nathan G; Roy, Marcia; Grant, Seth Gn

2017-09-12

The genetic mechanisms regulating the brain and behaviour across the lifespan are poorly understood. We found that lifespan transcriptome trajectories describe a calendar of gene regulatory events in the brain of humans and mice. Transcriptome trajectories defined a sequence of gene expression changes in neuronal, glial and endothelial cell-types, which enabled prediction of age from tissue samples. A major lifespan landmark was the peak change in trajectories occurring in humans at 26 years and in mice at 5 months of age. This species-conserved peak was delayed in females and marked a reorganization of expression of synaptic and schizophrenia-susceptibility genes. The lifespan calendar predicted the characteristic age of onset in young adults and sex differences in schizophrenia. We propose a genomic program generates a lifespan calendar of gene regulation that times age-dependent molecular organization of the brain and mutations that interrupt the program in young adults cause schizophrenia.

The Use of Dried Blood Spots: A Potential Tool for the Introduction of a Neonatal Screening Program for Sickle Cell Anemia in Zambia.

PubMed

Chindima, Nanjela; Nkhoma, Panji; Sinkala, Musalula; Zulu, Mildred; Kafita, Doris; Simakando, Marah; Mwaba, Florence; Mantina, Hamakwa; Mutale, Mubanga

2018-01-01

Sickle cell disease is a group of hemoglobin (Hb) disorders resulting from the inheritance of the sickle β-globin gene. It is the most common pathological Hb mutation worldwide with 75% being born in Sub-Saharan Africa. This study aims to determine if dried blood spots (DBSs) can be used for diagnosis of sickle cell in newborns. In Zambia, there is no neonatal screening program for sickle cell anemia (SCA), yet it has been proved that early diagnosis by newborn screening (NBS) using DBSs and access to comprehensive care results in survival to adulthood of over 96% of sickle cell patients. A cross-sectional study was carried out at the University Teaching Hospital to determine whether DBSs can be used to diagnose sickle cell using Hb electrophoresis. Results from DBSs stored for 2 weeks were then compared to those obtained using freshly collected whole blood. To evaluate performance characteristics, the following values were used: true positive, false positive, true negative, and false negative. Ninety-seven participants were included in this study. DBSs had a sensitivity of 100%, a specificity of 94.7%, positive predictive value of 96.7%, negative predictive value of 100%, overall efficiency of 97.9%, and a Kappa r 2 , P < 0.0001 in comparison to fresh whole blood which we used as the gold standard. The use of DBSs can be recommended for NBS of SCA in Zambia due to its high sensitivity, specificity, and stability of hemoglobin.

Computer simulation of thermal modeling of primary lithium cells

NASA Technical Reports Server (NTRS)

Young, I. Cho; Frank, Harvey; Halpert, Gersid

1987-01-01

The objective was to gain a better understanding of the safety problem of primary Li-SOCl2 and Li-SO2 cells by carrying out detailed thermal modeling work. In particular, the transient heat generation rates during moderate and extermely high discharge rate tests of Li-SOCl2 cells were predicted and compared with those from the electrochemical heating. The difference between the two may be attributed to the lithium corrosion and other chemical reactions. The present program was also tested for charging of Li-SO2. In addition, the present methodology should be applicable to other primary cylindrical cells as well as rechargeable battery analyses with minor modifications.

The CF Canada-Sick Kids Program in individual CF therapy: A resource for the advancement of personalized medicine in CF.

PubMed

Eckford, Paul D W; McCormack, Jacqueline; Munsie, Lise; He, Gengming; Stanojevic, Sanja; Pereira, Sergio L; Ho, Karen; Avolio, Julie; Bartlett, Claire; Yang, Jin Ye; Wong, Amy P; Wellhauser, Leigh; Huan, Ling Jun; Jiang, Jia Xin; Ouyang, Hong; Du, Kai; Klingel, Michelle; Kyriakopoulou, Lianna; Gonska, Tanja; Moraes, Theo J; Strug, Lisa J; Rossant, Janet; Ratjen, Felix; Bear, Christine E

2018-04-20

Therapies targeting certain CFTR mutants have been approved, yet variations in clinical response highlight the need for in-vitro and genetic tools that predict patient-specific clinical outcomes. Toward this goal, the CF Canada-Sick Kids Program in Individual CF Therapy (CFIT) is generating a "first of its kind", comprehensive resource containing patient-specific cell cultures and data from 100 CF individuals that will enable modeling of therapeutic responses. The CFIT program is generating: 1) nasal cells from drug naïve patients suitable for culture and the study of drug responses in vitro, 2) matched gene expression data obtained by sequencing the RNA from the primary nasal tissue, 3) whole genome sequencing of blood derived DNA from each of the 100 participants, 4) induced pluripotent stem cells (iPSCs) generated from each participant's blood sample, 5) CRISPR-edited isogenic control iPSC lines and 6) prospective clinical data from patients treated with CF modulators. To date, we have recruited 57 of 100 individuals to CFIT, most of whom are homozygous for F508del (to assess in-vitro: in-vivo correlations with respect to ORKAMBI response) or heterozygous for F508del and a minimal function mutation. In addition, several donors are homozygous for rare nonsense and missense mutations. Nasal epithelial cell cultures and matched iPSC lines are available for many of these donors. This accessible resource will enable development of tools that predict individual outcomes to current and emerging modulators targeting F508del-CFTR and facilitate therapy discovery for rare CF causing mutations. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

T-cell diversification reflects antigen selection in the blood of patients on immune checkpoint inhibition and may be exploited as liquid biopsy biomarker.

PubMed

Akyüz, Nuray; Brandt, Anna; Stein, Alexander; Schliffke, Simon; Mährle, Thorben; Quidde, Julia; Goekkurt, Eray; Loges, Sonja; Haalck, Thomas; Ford, Christopher Thomas; Asemissen, Anne Marie; Thiele, Benjamin; Radloff, Janina; Thenhausen, Toni; Krohn-Grimberghe, Artus; Bokemeyer, Carsten; Binder, Mascha

2017-06-01

Cancer immunotherapy with antibodies targeting immune checkpoints, such as programmed cell death protein 1 (PD-1), shows encouraging results, but reliable biomarkers predicting response to this costly and potentially toxic treatment approach are still lacking. To explore an immune signature predictive for response, we performed liquid biopsy immunoprofiling in 18 cancer patients undergoing PD-1 inhibition before and shortly after initiation of treatment by multicolor flow cytometry and next-generation T- and B-cell immunosequencing (TCRß/IGH). Findings were correlated with clinical outcomes. We found almost complete saturation of surface PD-1 on all T-cell subsets after the first dose of the antibody. Both T- and B-cell compartments quantitatively expanded during treatment. These expansions were mainly driven by an increase in the activated T-cell compartments, as well as of naïve B- and plasma cells. Deep immunosequencing revealed a clear diversification pattern of the clonal T-cell space indicative of antigenic selection in 47% of patients, while the remaining patients showed stable repertoires. 43% of the patients with a diversification pattern showed disease control in response to the PD-1 inhibitor. No disease stabilizations were observed without clonal T-cell space diversification. Our data show for the first time a clear impact of PD-1 targeting not only on circulating T-cells, but also on B-lineage cells, shedding light on the complexity of the anti-tumor immune response. Liquid biopsy T-cell next-generation immunosequencing should be prospectively evaluated as part of a composite response prediction biomarker panel in the context of clinical studies. © 2016 UICC.

An Effective Model of the Retinoic Acid Induced HL-60 Differentiation Program.

PubMed

Tasseff, Ryan; Jensen, Holly A; Congleton, Johanna; Dai, David; Rogers, Katharine V; Sagar, Adithya; Bunaciu, Rodica P; Yen, Andrew; Varner, Jeffrey D

2017-10-30

In this study, we present an effective model All-Trans Retinoic Acid (ATRA)-induced differentiation of HL-60 cells. The model describes reinforcing feedback between an ATRA-inducible signalsome complex involving many proteins including Vav1, a guanine nucleotide exchange factor, and the activation of the mitogen activated protein kinase (MAPK) cascade. We decomposed the effective model into three modules; a signal initiation module that sensed and transformed an ATRA signal into program activation signals; a signal integration module that controlled the expression of upstream transcription factors; and a phenotype module which encoded the expression of functional differentiation markers from the ATRA-inducible transcription factors. We identified an ensemble of effective model parameters using measurements taken from ATRA-induced HL-60 cells. Using these parameters, model analysis predicted that MAPK activation was bistable as a function of ATRA exposure. Conformational experiments supported ATRA-induced bistability. Additionally, the model captured intermediate and phenotypic gene expression data. Knockout analysis suggested Gfi-1 and PPARg were critical to the ATRAinduced differentiation program. These findings, combined with other literature evidence, suggested that reinforcing feedback is central to hyperactive signaling in a diversity of cell fate programs.

Dissecting engineered cell types and enhancing cell fate conversion via CellNet

PubMed Central

Morris, Samantha A.; Cahan, Patrick; Li, Hu; Zhao, Anna M.; San Roman, Adrianna K.; Shivdasani, Ramesh A.; Collins, James J.; Daley, George Q.

2014-01-01

SUMMARY Engineering clinically relevant cells in vitro holds promise for regenerative medicine, but most protocols fail to faithfully recapitulate target cell properties. To address this, we developed CellNet, a network biology platform that determines whether engineered cells are equivalent to their target tissues, diagnoses aberrant gene regulatory networks, and prioritizes candidate transcriptional regulators to enhance engineered conversions. Using CellNet, we improved B cell to macrophage conversion, transcriptionally and functionally, by knocking down predicted B cell regulators. Analyzing conversion of fibroblasts to induced hepatocytes (iHeps), CellNet revealed an unexpected intestinal program regulated by the master regulator Cdx2. We observed long-term functional engraftment of mouse colon by iHeps, thereby establishing their broader potential as endoderm progenitors and demonstrating direct conversion of fibroblasts into intestinal epithelium. Our studies illustrate how CellNet can be employed to improve direct conversion and to uncover unappreciated properties of engineered cells. PMID:25126792

Application of finite element substructuring to composite micromechanics. M.S. Thesis - Akron Univ., May 1984

NASA Technical Reports Server (NTRS)

Caruso, J. J.

1984-01-01

Finite element substructuring is used to predict unidirectional fiber composite hygral (moisture), thermal, and mechanical properties. COSMIC NASTRAN and MSC/NASTRAN are used to perform the finite element analysis. The results obtained from the finite element model are compared with those obtained from the simplified composite micromechanics equations. A unidirectional composite structure made of boron/HM-epoxy, S-glass/IMHS-epoxy and AS/IMHS-epoxy are studied. The finite element analysis is performed using three dimensional isoparametric brick elements and two distinct models. The first model consists of a single cell (one fiber surrounded by matrix) to form a square. The second model uses the single cell and substructuring to form a nine cell square array. To compare computer time and results with the nine cell superelement model, another nine cell model is constructed using conventional mesh generation techniques. An independent computer program consisting of the simplified micromechanics equation is developed to predict the hygral, thermal, and mechanical properties for this comparison. The results indicate that advanced techniques can be used advantageously for fiber composite micromechanics.

Functional analysis of rare variants in mismatch repair proteins augments results from computation-based predictive methods

PubMed Central

Arora, Sanjeevani; Huwe, Peter J.; Sikder, Rahmat; Shah, Manali; Browne, Amanda J.; Lesh, Randy; Nicolas, Emmanuelle; Deshpande, Sanat; Hall, Michael J.; Dunbrack, Roland L.; Golemis, Erica A.

2017-01-01

ABSTRACT The cancer-predisposing Lynch Syndrome (LS) arises from germline mutations in DNA mismatch repair (MMR) genes, predominantly MLH1, MSH2, MSH6, and PMS2. A major challenge for clinical diagnosis of LS is the frequent identification of variants of uncertain significance (VUS) in these genes, as it is often difficult to determine variant pathogenicity, particularly for missense variants. Generic programs such as SIFT and PolyPhen-2, and MMR gene-specific programs such as PON-MMR and MAPP-MMR, are often used to predict deleterious or neutral effects of VUS in MMR genes. We evaluated the performance of multiple predictive programs in the context of functional biologic data for 15 VUS in MLH1, MSH2, and PMS2. Using cell line models, we characterized VUS predicted to range from neutral to pathogenic on mRNA and protein expression, basal cellular viability, viability following treatment with a panel of DNA-damaging agents, and functionality in DNA damage response (DDR) signaling, benchmarking to wild-type MMR proteins. Our results suggest that the MMR gene-specific classifiers do not always align with the experimental phenotypes related to DDR. Our study highlights the importance of complementary experimental and computational assessment to develop future predictors for the assessment of VUS. PMID:28494185

Modeling of SONOS Memory Cell Erase Cycle

NASA Technical Reports Server (NTRS)

Phillips, Thomas A.; MacLeod, Todd C.; Ho, Fat H.

2011-01-01

Utilization of Silicon-Oxide-Nitride-Oxide-Silicon (SONOS) nonvolatile semiconductor memories as a flash memory has many advantages. These electrically erasable programmable read-only memories (EEPROMs) utilize low programming voltages, have a high erase/write cycle lifetime, are radiation hardened, and are compatible with high-density scaled CMOS for low power, portable electronics. In this paper, the SONOS memory cell erase cycle was investigated using a nonquasi-static (NQS) MOSFET model. Comparisons were made between the model predictions and experimental data.

(Toxicological Sciences) High-throughput H295R steroidogenesis assay: utility as an alternative and a statistical approach to characterize effects on steroidogenesis

EPA Science Inventory

The U.S. Environmental Protection Agency Endocrine Disruptor Screening Program and the Organization for Economic Co-operation and Development (OECD) have used the human adrenocarcinoma (H295R) cell-based assay to predict chemical perturbation of androgen and estrogen production. ...

Transcriptional Network Analysis in Muscle Reveals AP-1 as a Partner of PGC-1α in the Regulation of the Hypoxic Gene Program

PubMed Central

Baresic, Mario; Salatino, Silvia; Kupr, Barbara

2014-01-01

Skeletal muscle tissue shows an extraordinary cellular plasticity, but the underlying molecular mechanisms are still poorly understood. Here, we use a combination of experimental and computational approaches to unravel the complex transcriptional network of muscle cell plasticity centered on the peroxisome proliferator-activated receptor γ coactivator 1α (PGC-1α), a regulatory nexus in endurance training adaptation. By integrating data on genome-wide binding of PGC-1α and gene expression upon PGC-1α overexpression with comprehensive computational prediction of transcription factor binding sites (TFBSs), we uncover a hitherto-underestimated number of transcription factor partners involved in mediating PGC-1α action. In particular, principal component analysis of TFBSs at PGC-1α binding regions predicts that, besides the well-known role of the estrogen-related receptor α (ERRα), the activator protein 1 complex (AP-1) plays a major role in regulating the PGC-1α-controlled gene program of the hypoxia response. Our findings thus reveal the complex transcriptional network of muscle cell plasticity controlled by PGC-1α. PMID:24912679

Stochastic-Strength-Based Damage Simulation of Ceramic Matrix Composite Laminates

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.; Mital, Subodh K.; Murthy, Pappu L. N.; Bednarcyk, Brett A.; Pineda, Evan J.; Bhatt, Ramakrishna T.; Arnold, Steven M.

2016-01-01

The Finite Element Analysis-Micromechanics Analysis Code/Ceramics Analysis and Reliability Evaluation of Structures (FEAMAC/CARES) program was used to characterize and predict the progressive damage response of silicon-carbide-fiber-reinforced reaction-bonded silicon nitride matrix (SiC/RBSN) composite laminate tensile specimens. Studied were unidirectional laminates [0] (sub 8), [10] (sub 8), [45] (sub 8), and [90] (sub 8); cross-ply laminates [0 (sub 2) divided by 90 (sub 2),]s; angled-ply laminates [plus 45 (sub 2) divided by -45 (sub 2), ]s; doubled-edge-notched [0] (sub 8), laminates; and central-hole laminates. Results correlated well with the experimental data. This work was performed as a validation and benchmarking exercise of the FEAMAC/CARES program. FEAMAC/CARES simulates stochastic-based discrete-event progressive damage of ceramic matrix composite and polymer matrix composite material structures. It couples three software programs: (1) the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC), (2) the Ceramics Analysis and Reliability Evaluation of Structures Life Prediction Program (CARES/Life), and (3) the Abaqus finite element analysis program. MAC/GMC contributes multiscale modeling capabilities and micromechanics relations to determine stresses and deformations at the microscale of the composite material repeating-unit-cell (RUC). CARES/Life contributes statistical multiaxial failure criteria that can be applied to the individual brittle-material constituents of the RUC, and Abaqus is used to model the overall composite structure. For each FEAMAC/CARES simulation trial, the stochastic nature of brittle material strength results in random, discrete damage events that incrementally progress until ultimate structural failure.

Regenerative toxicology: the role of stem cells in the development of chronic toxicities.

PubMed

Canovas-Jorda, David; Louisse, Jochem; Pistollato, Francesca; Zagoura, Dimitra; Bremer, Susanne

2014-01-01

Human stem cell lines and their derivatives, as alternatives to the use of animal cells or cancer cell lines, have been widely discussed as cellular models in predictive toxicology. However, the role of stem cells in the development of long-term toxicities and carcinogenesis has not received great attention so far, despite growing evidence indicating the relationship of stem cell damage to adverse effects later in life. However, testing this in vitro is a scientific/technical challenge in particular due to the complex interplay of factors existing under physiological conditions. Current major research programs in stem cell toxicity are not aiming to demonstrate that stem cells can be targeted by toxicants. Therefore, this knowledge gap needs to be addressed in additional research activities developing technical solutions and defining appropriate experimental designs. The current review describes selected examples of the role of stem cells in the development of long-term toxicities in the brain, heart or liver and in the development of cancer. The presented examples illustrate the need to analyze the contribution of stem cells to chronic toxicity in order to make a final conclusion whether stem cell toxicities are an underestimated risk in mechanism-based safety assessments. This requires the development of predictive in vitro models allowing the assessment of adverse effects to stem cells on chronic toxicity and carcinogenicity.

Prediction of apoptosis protein locations with genetic algorithms and support vector machines through a new mode of pseudo amino acid composition.

PubMed

Kandaswamy, Krishna Kumar; Pugalenthi, Ganesan; Möller, Steffen; Hartmann, Enno; Kalies, Kai-Uwe; Suganthan, P N; Martinetz, Thomas

2010-12-01

Apoptosis is an essential process for controlling tissue homeostasis by regulating a physiological balance between cell proliferation and cell death. The subcellular locations of proteins performing the cell death are determined by mostly independent cellular mechanisms. The regular bioinformatics tools to predict the subcellular locations of such apoptotic proteins do often fail. This work proposes a model for the sorting of proteins that are involved in apoptosis, allowing us to both the prediction of their subcellular locations as well as the molecular properties that contributed to it. We report a novel hybrid Genetic Algorithm (GA)/Support Vector Machine (SVM) approach to predict apoptotic protein sequences using 119 sequence derived properties like frequency of amino acid groups, secondary structure, and physicochemical properties. GA is used for selecting a near-optimal subset of informative features that is most relevant for the classification. Jackknife cross-validation is applied to test the predictive capability of the proposed method on 317 apoptosis proteins. Our method achieved 85.80% accuracy using all 119 features and 89.91% accuracy for 25 features selected by GA. Our models were examined by a test dataset of 98 apoptosis proteins and obtained an overall accuracy of 90.34%. The results show that the proposed approach is promising; it is able to select small subsets of features and still improves the classification accuracy. Our model can contribute to the understanding of programmed cell death and drug discovery. The software and dataset are available at http://www.inb.uni-luebeck.de/tools-demos/apoptosis/GASVM.

Dynamic Finite Element Predictions for Mars Sample Return Cellular Impact Test #4

NASA Technical Reports Server (NTRS)

Fasanella, Edwin L.; Billings, Marcus D.

2001-01-01

The nonlinear finite element program MSC.Dytran was used to predict the impact pulse for (he drop test of an energy absorbing cellular structure. This pre-test simulation was performed to aid in the design of an energy absorbing concept for a highly reliable passive Earth Entry Vehicle (EEV) that will directly impact the Earth without a parachute. In addition, a goal of the simulation was to bound the acceleration pulse produced and delivered to the simulated space cargo container. EEV's are designed to return materials from asteroids, comets, or planets for laboratory analysis on Earth. The EEV concept uses an energy absorbing cellular structure designed to contain and limit the acceleration of space exploration samples during Earth impact. The spherical shaped cellular structure is composed of solid hexagonal and pentagonal foam-filled cells with hybrid graphite-epoxy/Kevlar cell walls. Space samples fit inside a smaller sphere at the enter of the EEV's cellular structure. The material models and failure criteria were varied to determine their effect on the resulting acceleration pulse. Pre-test analytical predictions using MSC.Dytran were compared with the test results obtained from impact test #4 using bungee accelerator located at the NASA Langley Research Center Impact Dynamics Research Facility. The material model used to represent the foam and the proper failure criteria for the cell walls were critical in predicting the impact loads of the cellular structure. It was determined that a FOAMI model for the foam and a 20% failure strain criteria for the cell walls gave an accurate prediction of the acceleration pulse for drop test #4.

The Association of CD81 Polymorphisms with Alloimmunization in Sickle Cell Disease

PubMed Central

Tatari-Calderone, Zohreh; Tamouza, Ryad; Le Bouder, Gama P.; Dewan, Ramita; Luban, Naomi L. C.; Lasserre, Jacqueline; Maury, Jacqueline; Lionnet, François; Krishnamoorthy, Rajagopal; Girot, Robert

2013-01-01

The goal of the present work was to identify the candidate genetic markers predictive of alloimmunization in sickle cell disease (SCD). Red blood cell (RBC) transfusion is indicated for acute treatment, prevention, and abrogation of some complications of SCD. A well-known consequence of multiple RBC transfusions is alloimmunization. Given that a subset of SCD patients develop multiple RBC allo-/autoantibodies, while others do not in a similar multiple transfusional setting, we investigated a possible genetic basis for alloimmunization. Biomarker(s) which predicts (predict) susceptibility to alloimmunization could identify patients at risk before the onset of a transfusion program and thus may have important implications for clinical management. In addition, such markers could shed light on the mechanism(s) underlying alloimmunization. We genotyped 27 single nucleotide polymorphisms (SNPs) in the CD81, CHRNA10, and ARHG genes in two groups of SCD patients. One group (35) of patients developed alloantibodies, and another (40) had no alloantibodies despite having received multiple transfusions. Two SNPs in the CD81 gene, that encodes molecule involved in the signal modulation of B lymphocytes, show a strong association with alloimmunization. If confirmed in prospective studies with larger cohorts, the two SNPs identified in this retrospective study could serve as predictive biomarkers for alloimmunization. PMID:23762099

High speed turboprop aeroacoustic study (counterrotation). Volume 1: Model development

NASA Technical Reports Server (NTRS)

Whitfield, C. E.; Mani, R.; Gliebe, P. R.

1990-01-01

The isolated counterrotating high speed turboprop noise prediction program was compared with model data taken in the GE Aircraft Engines Cell 41 anechoic facility, the Boeing Transonic Wind Tunnel, and in NASA-Lewis' 8x6 and 9x15 wind tunnels. The predictions show good agreement with measured data under both low and high speed simulated flight conditions. The installation effect model developed for single rotation, high speed turboprops was extended to include counterotation. The additional effect of mounting a pylon upstream of the forward rotor was included in the flow field modeling. A nontraditional mechanism concerning the acoustic radiation from a propeller at angle of attach was investigated. Predictions made using this approach show results that are in much closer agreement with measurement over a range of operating conditions than those obtained via traditional fluctuating force methods. The isolated rotors and installation effects models were combines into a single prediction program, results of which were compared with data taken during the flight test of the B727/UDF engine demonstrator aircraft. Satisfactory comparisons between prediction and measured data for the demonstrator airplane, together with the identification of a nontraditional radiation mechanism for propellers at angle of attack are achieved.

High speed turboprop aeroacoustic study (counterrotation). Volume 1: Model development

NASA Astrophysics Data System (ADS)

Whitfield, C. E.; Mani, R.; Gliebe, P. R.

1990-07-01

The isolated counterrotating high speed turboprop noise prediction program was compared with model data taken in the GE Aircraft Engines Cell 41 anechoic facility, the Boeing Transonic Wind Tunnel, and in NASA-Lewis' 8x6 and 9x15 wind tunnels. The predictions show good agreement with measured data under both low and high speed simulated flight conditions. The installation effect model developed for single rotation, high speed turboprops was extended to include counterotation. The additional effect of mounting a pylon upstream of the forward rotor was included in the flow field modeling. A nontraditional mechanism concerning the acoustic radiation from a propeller at angle of attach was investigated. Predictions made using this approach show results that are in much closer agreement with measurement over a range of operating conditions than those obtained via traditional fluctuating force methods. The isolated rotors and installation effects models were combines into a single prediction program, results of which were compared with data taken during the flight test of the B727/UDF engine demonstrator aircraft. Satisfactory comparisons between prediction and measured data for the demonstrator airplane, together with the identification of a nontraditional radiation mechanism for propellers at angle of attack are achieved.

An Improved Method for TAL Effectors DNA-Binding Sites Prediction Reveals Functional Convergence in TAL Repertoires of Xanthomonas oryzae Strains

PubMed Central

Pérez-Quintero, Alvaro L.; Rodriguez-R, Luis M.; Dereeper, Alexis; López, Camilo; Koebnik, Ralf; Szurek, Boris; Cunnac, Sebastien

2013-01-01

Transcription Activators-Like Effectors (TALEs) belong to a family of virulence proteins from the Xanthomonas genus of bacterial plant pathogens that are translocated into the plant cell. In the nucleus, TALEs act as transcription factors inducing the expression of susceptibility genes. A code for TALE-DNA binding specificity and high-resolution three-dimensional structures of TALE-DNA complexes were recently reported. Accurate prediction of TAL Effector Binding Elements (EBEs) is essential to elucidate the biological functions of the many sequenced TALEs as well as for robust design of artificial TALE DNA-binding domains in biotechnological applications. In this work a program with improved EBE prediction performances was developed using an updated specificity matrix and a position weight correction function to account for the matching pattern observed in a validation set of TALE-DNA interactions. To gain a systems perspective on the large TALE repertoires from X. oryzae strains, this program was used to predict rice gene targets for 99 sequenced family members. Integrating predictions and available expression data in a TALE-gene network revealed multiple candidate transcriptional targets for many TALEs as well as several possible instances of functional convergence among TALEs. PMID:23869221

Toward computer simulation of high-LET in vitro survival curves.

PubMed

Heuskin, A-C; Michiels, C; Lucas, S

2013-09-21

We developed a Monte Carlo based computer program called MCSC (Monte Carlo Survival Curve) able to predict the survival fraction of cells irradiated in vitro with a broad beam of high linear energy transfer particles. Three types of cell responses are studied: the usual high dose response, the bystander effect and the low-dose hypersensitivity (HRS). The program models the broad beam irradiation and double strand break distribution following Poisson statistics. The progression of cells through the cell cycle is taken into account while the repair takes place. Input parameters are experimentally determined for A549 lung carcinoma cells irradiated with 10 and 20 keV µm(-1) protons, 115 keV µm(-1) alpha particles and for EAhy926 endothelial cells exposed to 115 keV µm(-1) alpha particles. Results of simulations are presented and compared with experimental survival curves obtained for A549 and EAhy296 cells. Results are in good agreement with experimental data for both cell lines and all irradiation protocols. The benefits of MCSC are several: the gain of time that would have been spent performing time-consuming clonogenic assays, the capacity to estimate survival fraction of cell lines not forming colonies and possibly the evaluation of radiosensitivity parameters of given individuals.

PD-L1 is upregulated by radiochemotherapy in rectal adenocarcinoma patients and associated with a favourable prognosis.

PubMed

Hecht, Markus; Büttner-Herold, Maike; Erlenbach-Wünsch, Katharina; Haderlein, Marlen; Croner, Roland; Grützmann, Robert; Hartmann, Arndt; Fietkau, Rainer; Distel, Luitpold V

2016-09-01

The influence of neoadjuvant radiochemotherapy (RCT) on programmed death-ligand 1 (PD-L1) expression, a predictive marker for programmed cell death protein 1 (PD-1) inhibitor therapy, was studied on tumour and inflammatory cells in rectal adenocarcinoma patients along with its prognostic value. PD-L1 immunohistochemistry was performed on tissue microarrays of 103 pre-RCT biopsies and 159 post-RCT surgical specimens (central tumour, invasive front and normal tissue) of 199 patients. In 63 patients, both samples were available. Proportion and maximum intensity of PD-L1-positive (PD-L1+) cells were evaluated. RCT increased the proportion of PD-L1-expressing cancer cells from 2.1% to 7.8% in the central tumour (p < 0.001) or 9.3% in the invasive front (p < 0.001). Cancer cell PD-L1 on its own could not predict prognosis. High PD-L1 expression on pre-RCT inflammatory cells (maximum intensity: p = 0.048) and post-RCT invasive front inflammatory cells (p = 0.010) correlated with improved no evidence of disease survival. In multivariate analysis, the combination of low PD-L1 in cancer and inflammatory cells was an independent negative prognostic marker for overall survival (OS) pre-RCT (Cox's proportional hazard ratio 0.438, p = 0.045) and in the invasive front post-RCT (Cox's proportional hazard ratio 0.257, p = 0.030). Neoadjuvant RCT is associated with an increased PD-L1 expression in rectal adenocarcinoma patients, which should prompt clinical trials combining radiotherapy and PD-1/PD-L1 pathway blockade. Combined low PD-L1 expression on tumour and inflammatory cells is an independent negative prognostic marker for OS in RCT of rectal adenocarcinoma. Copyright © 2016 Elsevier Ltd. All rights reserved.

Response to anti-programmed cell death protein-1 antibodies in men treated for platinum refractory germ cell cancer relapsed after high-dose chemotherapy and stem cell transplantation.

PubMed

Zschäbitz, Stefanie; Lasitschka, Felix; Hadaschik, Boris; Hofheinz, Ralf-Dieter; Jentsch-Ullrich, Kathleen; Grüner, Marcus; Jäger, Dirk; Grüllich, Carsten

2017-05-01

Treatment options for patients with platinum refractory metastatic germ cell tumours (GCT) relapsing after high-dose chemotherapy and autologous stem cell transplantation are limited and survival is poor. Antibodies directed against programmed cell death protein-1 (PD-1) and programmed cell death ligand-1 (PD-L1) are currently assessed within clinical trials. We present updated data on our experience with checkpoint inhibitors as a compassionate use off-label treatment attempt for highly-pretreated patients with GCT and provide an overview of the current literature on PD-L1 expression in this rare tumour entity. We analysed all patients with platinum refractory GCT treated with checkpoint inhibitors at our institutions between 2015 and 2017. Data were retrieved retrospectively from the patient charts. Seven patients were treated with nivolumab or pembrolizumab. Four patients received single-dose treatment and died shortly afterwards due to tumour progression; the remaining three patients received treatment for at least 6 months. No significant treatment toxicity was observed. Long-term tumour response was achieved in two of the three patients, both of them highly positive for PD-L1 staining. We consider checkpoint inhibition to be efficient in carefully selected patients with platinum refractory GCT. However, predictive markers associated with tumour response are not yet known and larger prospective clinical trials are warranted. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluation of In Vitro Biotransformation Using HepaRG Cells to Improve High-Throughput Chemical Hazard Prediction: A Toxicogenomics Analysis (SOT)

EPA Science Inventory

The US EPA’s ToxCast program has generated a wealth of data in >600 in vitro assayson a library of 1060 environmentally relevant chemicals and failed pharmaceuticals to facilitate hazard identification. An inherent criticism of many in vitro-based strategies is the inability of a...

A method to identify and analyze biological programs through automated reasoning

PubMed Central

Yordanov, Boyan; Dunn, Sara-Jane; Kugler, Hillel; Smith, Austin; Martello, Graziano; Emmott, Stephen

2016-01-01

Predictive biology is elusive because rigorous, data-constrained, mechanistic models of complex biological systems are difficult to derive and validate. Current approaches tend to construct and examine static interaction network models, which are descriptively rich, but often lack explanatory and predictive power, or dynamic models that can be simulated to reproduce known behavior. However, in such approaches implicit assumptions are introduced as typically only one mechanism is considered, and exhaustively investigating all scenarios is impractical using simulation. To address these limitations, we present a methodology based on automated formal reasoning, which permits the synthesis and analysis of the complete set of logical models consistent with experimental observations. We test hypotheses against all candidate models, and remove the need for simulation by characterizing and simultaneously analyzing all mechanistic explanations of observed behavior. Our methodology transforms knowledge of complex biological processes from sets of possible interactions and experimental observations to precise, predictive biological programs governing cell function. PMID:27668090

Characterization testing of MEASAT GaAs/Ge solar cell assemblies

NASA Technical Reports Server (NTRS)

Brown, Mike R.; Garcia, Curtis A.; Goodelle, George S.; Powe, Joseph S.; Schwartz, Joel A.

1996-01-01

The first commercial communications satellite with gallium-arsenide on germanium (GaAs/Ge) solar arrays is scheduled for launch in December 1995. The spacecraft, named MEASAT, was built by Hughes Space and Communications Company. The solar cell assemblies consisted of large area GaAs/Ge cells supplied by Spectrolab Inc. with infrared reflecting (IRR) coverglass supplied by Pilkington Space Technology. A comprehensive characterization program was performed on the GaAs/Ge solar cell assemblies used on the MEASAT array. This program served two functions; first to establish the database needed to accurately predict on-orbit performance under a variety of conditions; and second, to demonstrate the ability of the solar cell assemblies to withstand all mission environments while still providing the required power at end-of-life. Characterization testing included measurement of electrical performance parameters as a function of radiation exposure, temperature, and angle of incident light; reverse bias stability; optical and thermal properties; mechanical strength tests, panel fabrication, humidity and thermal cycling environmental tests. The results provided a complete database enabling the design of the MEASAT solar array, and demonstrated that the GaAs/Ge cells meet the spacecraft requirements at end-of-life.

Characterization testing of MEASAT GaAs/Ge solar cell assemblies

NASA Technical Reports Server (NTRS)

Brown, Mike R.; Garcia, Curtis A.; Goodelle, George S.; Powe, Joseph S.; Schwartz, Joel A.

1995-01-01

The first commercial communications satellite with gallium-arsenide on germanium (GaAs/Ge) solar arrays is scheduled for launch in December 1995. The spacecraft, named MEASAT, was built by hughes Space and Telecommunications company for Binariang Satellite Systems of Malaysia. The solar cell assemblies consisted of large area GaAs/Ge cells supplied by Spectrolab Inc. with infrared reflecting (IRR) coverglass supplied by Pilkington Space Technology. A comprehensive characterization program was performed on the GaAs/Ge solar cell assemblies used on the MEASAT array. This program served two functions; first to establish the database needed to accurately predict on-orbit performance under a variety of conditions; and second, to demonstrate the ability of the solar cell assemblies to withstand all mission environments while still providing the required power at end-of-life. characterization testing included measurement of electrical performance parameters as a function of radiation exposure, temperature, and angle of incident light; reverse bias stability; optical and thermal properties; mechanical strength tests, panel fabrication, humidity and thermal cycling environmental tests. The results provided a complete database enabling the design of the MEASAT solar array, and demonstrated that the GaAs/Ge cells meet the spacecraft requirements at end-of-life.

Use of Cell Viability Assay Data Improves the Prediction Accuracy of Conventional Quantitative Structure–Activity Relationship Models of Animal Carcinogenicity

PubMed Central

Zhu, Hao; Rusyn, Ivan; Richard, Ann; Tropsha, Alexander

2008-01-01

Background To develop efficient approaches for rapid evaluation of chemical toxicity and human health risk of environmental compounds, the National Toxicology Program (NTP) in collaboration with the National Center for Chemical Genomics has initiated a project on high-throughput screening (HTS) of environmental chemicals. The first HTS results for a set of 1,408 compounds tested for their effects on cell viability in six different cell lines have recently become available via PubChem. Objectives We have explored these data in terms of their utility for predicting adverse health effects of the environmental agents. Methods and results Initially, the classification k nearest neighbor (kNN) quantitative structure–activity relationship (QSAR) modeling method was applied to the HTS data only, for a curated data set of 384 compounds. The resulting models had prediction accuracies for training, test (containing 275 compounds together), and external validation (109 compounds) sets as high as 89%, 71%, and 74%, respectively. We then asked if HTS results could be of value in predicting rodent carcinogenicity. We identified 383 compounds for which data were available from both the Berkeley Carcinogenic Potency Database and NTP–HTS studies. We found that compounds classified by HTS as “actives” in at least one cell line were likely to be rodent carcinogens (sensitivity 77%); however, HTS “inactives” were far less informative (specificity 46%). Using chemical descriptors only, kNN QSAR modeling resulted in 62.3% prediction accuracy for rodent carcinogenicity applied to this data set. Importantly, the prediction accuracy of the model was significantly improved (72.7%) when chemical descriptors were augmented by HTS data, which were regarded as biological descriptors. Conclusions Our studies suggest that combining NTP–HTS profiles with conventional chemical descriptors could considerably improve the predictive power of computational approaches in toxicology. PMID:18414635

Numerical studies of unsteady two dimensional subsonic flows using the ICE method. Ph.D. Thesis - Toledo Univ.

NASA Technical Reports Server (NTRS)

Wieber, P. R.

1973-01-01

A numerical program was developed to compute transient compressible and incompressible laminar flows in two dimensions with multicomponent mixing and chemical reaction. The algorithm used the Los Alamos Scientific Laboratory ICE (Implicit Continuous-Fluid Eulerian) method as its base. The program can compute both high and low speed compressible flows. The numerical program incorporating the stabilization techniques was quite successful in treating both old and new problems. Detailed calculations of coaxial flow very close to the entry plane were possible. The program treated complex flows such as the formation and downstream growth of a recirculation cell. An implicit solution of the species equation predicted mixing and reaction rates which compared favorably with the literature.

Integrative Genomic Analyses Yields Cell Cycle Regulatory Programs with Prognostic Value

PubMed Central

Cheng, Chao; Lou, Shaoke; Andrews, Erik H.; Ung, Matthew H.; Varn, Frederick S.

2016-01-01

Liposarcoma is the second most common form of sarcoma, which has been categorized into four molecular subtypes, which are associated with differential prognosis of patients. However, the transcriptional regulatory programs associated with distinct histological and molecular subtypes of liposarcoma have not been investigated. This study uses integrative analyses to systematically define the transcriptional regulatory programs associated with liposarcoma. Likewise, computational methods are used to identify regulatory programs associated with different liposarcoma subtypes as well as programs that are predictive of prognosis. Further analysis of curated gene sets was used to identify prognostic gene signatures. The integration of data from a variety sources including gene expression profiles, transcription factor (TF) binding data from ChIP-seq experiments, curated gene sets, and clinical information of patients indicated discrete regulatory programs (e.g., controlled by E2F1 and E2F4) with significantly different regulatory activity in one or multiple subtypes of liposarcoma with respect to normal adipose tissue. These programs were also shown to be prognostic, wherein liposarcoma patients with higher E2F4 or E2F1 activity associated with unfavorable prognosis. A total of 259 gene sets were significantly associated with patient survival in liposarcoma, among which >50% are involved in cell cycle and proliferation. PMID:26856934

Predictive Value of Soluble Programmed Death-1 for Severe Sepsis and Septic Shock During the First Week in an Intensive Care Unit.

PubMed

Zhao, Yongzhen; Jia, Yumei; Li, Chunsheng; Shao, Rui; Fang, Yingying

2018-04-26

Programmed death-1 (PD-1)/programmed death ligand-1 (PD-L1) exists in both membrane-bound and soluble forms. In this study, we evaluated the predictive value of soluble PD-1 (sPD-1) for severity and 28-day mortality in patients with severe sepsis and septic shock during the first week in an intensive care unit (ICU). In this prospective cohort study, patients were classified into the severe sepsis group or the septic shock group according to the severity of their condition on ICU admission. All patients were also separated into the survivor or nonsurvivor groups according to their 28-day outcomes. Peripheral blood sPD-1 and soluble PD-L1 (sPD-L1) levels, PD-1 expression on CD4 and CD8 T cells, and PD-L1 expression on monocytes were measured and compared between the groups on days 1 and 7 after ICU admission. In all, 45 healthy volunteers and 112 patients were recruited. Serum sPD-1 levels were positively correlated with the severity of sepsis, sPD-L1 levels, PD-1 expression on CD4 or CD8 T cells, and PD-L1 expression on monocytes. The sPD-1 was an independent predictive factor for 28-day mortality both on day 1 and day 7. The area under the curve (AUC) of the sPD-1 on day 7 (0.871) was higher than that on day 1 (0.785) (P < 0.05), and better than the AUC of the percentages of PD-L1 on monocytes (0.770) on day 7 (P < 0.05). Serum sPD-1 shows valuable predictive ability for the severity and 28-day mortality of severe sepsis and septic shock during the first week of ICU treatment.

Proposed comprehensive ototoxicity monitoring program for VA healthcare (COMP-VA)

PubMed Central

Konrad-Martin, Dawn; Reavis, Kelly M.; McMillan, Garnett; Helt, Wendy J.; Dille, Marilyn

2015-01-01

Prevention and rehabilitation of hearing loss and tinnitus, the two most commonly awarded service-connected disabilities, are high priority initiatives in the Department of Veterans Affairs (VA). At least 4,000 Veterans, most with significant hearing loss, will receive cisplatin this year, with more than half sustaining permanent hearing shift and nearly 40% developing new tinnitus. With improved survivability following cancer treatment, Veterans treated with cisplatin are approached with the dual goals of effective treatment and preserved quality of life. This article describes COMP-VA, a comprehensive ototoxicity monitoring program developed for VA patients receiving cisplatin. The program includes an individualized pretreatment prediction model that identifies the likelihood of hearing shift given cisplatin dose and patient factors. It supports both manual and automated hearing testing with a newly developed portable audiometer capable of performing the recommended procedures on the chemotherapy unit during treatment. It also includes objective methods for identifying outer hair cell changes and predicting audiogram changes using distortion-product otoacoustic emissions. We describe this program of evidence-based ototoxicity monitoring protocols using a case example to give the reader an understanding of how this program would be applied, along with a plan for future work to accomplish the final stages of program development. PMID:24805896

Demonstration of transparent solar array module design

NASA Technical Reports Server (NTRS)

Pack, G. J.

1984-01-01

This report discusses the design, development, fabrication and testing of IR transparent solar array modules. Three modules, consisting of a baseline design using back surface reflector cells, and two modules using gridded back contact, IR transparent cells, were subjected to vacuum thermal balance testing to verify analytical predictions of lower operating emperature and increased efficiency. As a result of this test program, LMSC has verified that a significant degree of IR transparency can be designed into a flexible solar array. Test data correlates with both steady state and transient thermal analysis.

Development and test fuel cell powered on-site integrated total energy systems. Phase 3: Full-scale power plant development

NASA Technical Reports Server (NTRS)

Kaufman, A.

1982-01-01

The on-site system application analysis is summarized. Preparations were completed for the first test of a full-sized single cell. Emphasis of the methanol fuel processor development program shifted toward the use of commercial shell-and-tube heat exchangers. An improved method for predicting the carbon-monoxide tolerance of anode catalysts is described. Other stack support areas reported include improved ABA bipolar plate bonding technology, improved electrical measurement techniques for specification-testing of stack components, and anodic corrosion behavior of carbon materials.

CD3+/CD8+ T-cell density and tumoral PD-L1 predict survival irrespective of rituximab treatment in Chinese diffuse large B-cell lymphoma patients.

PubMed

Shi, Yunfei; Deng, Lijuan; Song, Yuqin; Lin, Dongmei; Lai, Yumei; Zhou, LiXin; Yang, Lei; Li, Xianghong

2018-05-10

To investigate the prognostic value of tumor-infiltrating T-cell density and programmed cell death ligand-1 (PD-L1) expression in diffuse large B cell lymphoma (DLBCL). One-hundred-twenty-five Chinese DLBCL patients were enrolled in our study and provided samples; 76 of all cases were treated with rituximab (R). Tumor tissues were immunostained and analyzed for CD3+ and CD8+ tumor-infiltrating T-cell density, tumoral PD-L1, and microenvironmental PD-L1 (mPD-L1). The density of CD3 was rated as high in 33.6% cases, while 64.0% of DLBCLs were classified as high CD8 density. Of all cases, 16.8% were PD-L1+. Of the remaining PD-L1-DLBCLs, 29.8% positively expressed mPD-L1. Both CD3 high density and CD8 high density were associated with mPD-L1 positivity (P = 0.001 and P = 0.0001). In multivariate analysis, independently, high CD3 density predicted better OS (P = 0.023), while CD8 high density and PD-L1 positivity were both associated with prolonged PFS (P = 0.013 and P = 0.036, respectively). Even in the subgroup treated with R, univariate analyses indicated that high CD3 density and PD-L1 positivity were associated with better OS (P = 0.041) and PFS (P = 0.033), respectively. The infiltrating densities of CD3+ T-cells, CD8+ T-cells, and PD-L1 expression are predictive of survival in DLBCLs, irrespective of R usage.

Scale-up of Carbon/Carbon Bipolar Plates

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

David P. Haack

2009-04-08

This project was focused upon developing a unique material technology for use in PEM fuel cell bipolar plates. The carbon/carbon composite material developed in this program is uniquely suited for use in fuel cell systems, as it is lightweight, highly conductive and corrosion resistant. The project further focused upon developing the manufacturing methodology to cost-effectively produce this material for use in commercial fuel cell systems. United Technology Fuel Cells Corp., a leading fuel cell developer was a subcontractor to the project was interested in the performance and low-cost potential of the material. The accomplishments of the program included the developmentmore » and testing of a low-cost, fully molded, net-shape carbon-carbon bipolar plate. The process to cost-effectively manufacture these carbon-carbon bipolar plates was focused on extensively in this program. Key areas for cost-reduction that received attention in this program was net-shape molding of the detailed flow structures according to end-user design. Correlations between feature detail and process parameters were formed so that mold tooling could be accurately designed to meet a variety of flow field dimensions. A cost model was developed that predicted the cost of manufacture for the product in near-term volumes and long-term volumes (10+ million units per year). Because the roduct uses lowcost raw materials in quantities that are less than competitive tech, it was found that the cost of the product in high volume can be less than with other plate echnologies, and can meet the DOE goal of $4/kW for transportation applications. The excellent performance of the all-carbon plate in net shape was verified in fuel cell testing. Performance equivalent to much higher cost, fully machined graphite plates was found.« less

An analytical study of reduced-gravity liquid reorientation using a simplified marker and cell technique

NASA Technical Reports Server (NTRS)

Betts, W. S., Jr.

1972-01-01

A computer program called HOPI was developed to predict reorientation flow dynamics, wherein liquids move from one end of a closed, partially filled, rigid container to the other end under the influence of container acceleration. The program uses the simplified marker and cell numerical technique and, using explicit finite-differencing, solves the Navier-Stokes equations for an incompressible viscous fluid. The effects of turbulence are also simulated in the program. HOPI can consider curved as well as straight walled boundaries. Both free-surface and confined flows can be calculated. The program was used to simulate five liquid reorientation cases. Three of these cases simulated actual NASA LeRC drop tower test conditions while two cases simulated full-scale Centaur tank conditions. It was concluded that while HOPI can be used to analytically determine the fluid motion in a typical settling problem, there is a current need to optimize HOPI. This includes both reducing the computer usage time and also reducing the core storage required for a given size problem.

Usefulness of the ElliPro epitope predictor program in defining the repertoire of HLA-ABC eplets.

PubMed

Duquesnoy, Rene J; Marrari, Marilyn

HLA matching at the epitope level offers new opportunities to identify suitable donors for transplant patients. The International HLA Epitope Registry (www.Epregistry.com.br) describes for the various HLA loci, repertoires of eplets including those that correspond to epitopes experimentally verified with specific antibodies. There are also many eplets which have remained as theoretical entities because no informative antibodies have been found. Which of them have immunogenic potential or conversely, might be considered as non-epitopes that cannot elicit specific antibody responses? This question is important for the application of epitope-based HLA matching in clinical transplantation. Correct predictions of B-cell epitopes on antigenic proteins are essential to the effective design of microbial vaccines and the development of specific antibodies used in immunotherapy and immunodiagnostics but prediction programs based on structural and physiochemical properties of amino acid residues are generally ineffective. Recent prediction programs based on three-dimensional structures of antigen-antibody complexes are more promising. One such program is called ElliPro developed by Ponomarenko. This report describes studies demonstrating that ElliPro can predict alloantibody responses to HLA-ABC eplets. Antibody-verified eplets have amino acid residues with much higher ElliPro scores than eplets for which no specific antibodies have been found. The latter group includes residues with very low ElliPro scores; they appear to represent eplets that might be classified as non-epitopes. In conclusion, ElliPro offers a new approach to characterize epitope repertoires that are clinically relevant in HLA matching. Copyright © 2017. Published by Elsevier Inc.

Thermoelastic analysis of solar cell arrays and their material properties

NASA Technical Reports Server (NTRS)

Salama, M. A.; Rowe, W. M.; Yasui, R. K.

1973-01-01

A thermoelastic stress analysis procedure is reported for predicting the thermally induced stresses and failures in silicon solar cell arrays. A prerequisite for the analysis is the characterization of the temperature-dependent thermal and mechanical properties of the solar cell materials. Extensive material property testing was carried out in the temperature range -200 to +200 C for the filter glass, P- and N-type silicon, interconnector metals, solder, and several candidate silicone rubber adhesives. The analysis procedure is applied to several solar cell array design configurations. Results of the analysis indicate the optimum design configuration, with respect to compatible materials, effect of the solder coating, and effect of the interconnector geometry. Good agreement was found between results of the analysis and the test program.

WE-H-BRA-07: Mechanistic Modelling of the Relative Biological Effectiveness of Heavy Charged Particles

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

McMahon, S; Queen’s University, Belfast, Belfast; McNamara, A

2016-06-15

Purpose Uncertainty in the Relative Biological Effectiveness (RBE) of heavy charged particles compared to photons remains one of the major uncertainties in particle therapy. As RBEs depend strongly on clinical variables such as tissue type, dose, and radiation quality, more accurate individualised models are needed to fully optimise treatments. MethodsWe have developed a model of DNA damage and repair following X-ray irradiation in a number of settings, incorporating mechanistic descriptions of DNA repair pathways, geometric effects on DNA repair, cell cycle effects and cell death. Our model has previously been shown to accurately predict a range of biological endpoints includingmore » chromosome aberrations, mutations, and cell death. This model was combined with nanodosimetric models of individual ion tracks to calculate the additional probability of lethal damage forming within a single track. These lethal damage probabilities can be used to predict survival and RBE for cells irradiated with ions of different Linear Energy Transfer (LET). ResultsBy combining the X-ray response model with nanodosimetry information, predictions of RBE can be made without cell-line specific fitting. The model’s RBE predictions were found to agree well with empirical proton RBE models (Mean absolute difference between models of 1.9% and 1.8% for cells with α/β ratios of 9 and 1.4, respectively, for LETs between 0 and 15 keV/µm). The model also accurately recovers the impact of high-LET carbon ion exposures, showing both the reduced efficacy of ions at extremely high LET, as well as the impact of defects in non-homologous end joining on RBE values in Chinese Hamster Ovary cells.ConclusionOur model is predicts RBE without the inclusion of empirical LET fitting parameters for a range of experimental conditions. This approach has the potential to deliver improved personalisation of particle therapy, with future developments allowing for the calculation of individualised RBEs. SJM is supported by a Marie Curie International Outgoing Fellowship from the European Commission’s FP7 program (EC FP7 MC-IOF-623630)« less

Fusion Genes Predict Prostate Cancer Recurrence

DTIC Science & Technology

2017-10-01

we will develop a training program centered on genomics and cell culturing methods to train new investigators to carry out research in benign urologic...Medical Research and Materiel Command Fort Detrick, Maryland 21702-5012 DISTRIBUTION STATEMENT: Approved for Public Release; Distribution...MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR’S ACRONYM(S) U.S. Army Medical Research and Materiel Command Fort Detrick, Maryland

Month-wise variation and prediction of bulk tank somatic cell count in Brazilian dairy herds and its impact on payment based on milk quality.

PubMed

Busanello, Marcos; de Freitas, Larissa Nazareth; Winckler, João Pedro Pereira; Farias, Hiron Pereira; Dos Santos Dias, Carlos Tadeu; Cassoli, Laerte Dagher; Machado, Paulo Fernando

2017-01-01

Payment programs based on milk quality (PPBMQ) are used in several countries around the world as an incentive to improve milk quality. One of the principal milk parameters used in such programs is the bulk tank somatic cell count (BTSCC). In this study, using data from an average of 37,000 farms per month in Brazil where milk was analyzed, BTSCC data were divided into different payment classes based on milk quality. Then, descriptive and graphical analyses were performed. The probability of a change to a worse payment class was calculated, future BTSCC values were predicted using time series models, and financial losses due to the failure to reach the maximum bonus for the payment based on milk quality were simulated. In Brazil, the mean BTSCC has remained high in recent years, without a tendency to improve. The probability of changing to a worse payment class was strongly affected by both the BTSCC average and BTSCC standard deviation for classes 1 and 2 (1000-200,000 and 201,000-400,000 cells/mL, respectively) and only by the BTSCC average for classes 3 and 4 (401,000-500,000 and 501,000-800,000 cells/mL, respectively). The time series models indicated that at some point in the year, farms would not remain in their current class and would accrue financial losses due to payments based on milk quality. The BTSCC for Brazilian dairy farms has not recently improved. The probability of a class change to a worse class is a metric that can aid in decision-making and stimulate farmers to improve milk quality. A time series model can be used to predict the future value of the BTSCC, making it possible to estimate financial losses and to show, moreover, that financial losses occur in all classes of the PPBMQ because the farmers do not remain in the best payment class in all months.

[PD-L1 expression: An emerging biomarker in non-small cell lung cancer].

PubMed

Adam, Julien; Planchard, David; Marabelle, Aurélien; Soria, Jean-Charles; Scoazec, Jean-Yves; Lantuéjoul, Sylvie

2016-01-01

Therapies targeting immune checkpoints, in particular programmed death 1 (PD-1) and its ligand programmed death ligand 1 (PD-L1), are major new strategies for the treatment of several malignancies including mestatatic non-small cell lung cancer (NSCLC). The identification of predictive biomarkers of response is required, considering efficacy, cost and potential adverse events. Expression of PD-L1 by immunohistochemistry has been associated with higher response rate and overall survival in several clinical trials evaluating anti-PD-1 and anti-PD-L1 monoclonal antibodies. Thus, PD-L1 immunohistochemical companion assays could be required for treatment with some of these therapies in NSCLC. However, heterogeneity in methodologies of PD-L1 assays in terms of primary antibodies and scoring algorithms, and tumor heterogenity for PD-L1 expression are important issues to be considered. More studies are required to compare the different assays, ensure their harmonization and standardization and identify the optimal conditions for testing. PD-L1 expression is likely an imperfect predictive biomarker for patient selection and association with other markers of the tumor immune microenvironment will be probably necessary in the future. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

First principles-based moiré model for incommensurate graphene on BN

NASA Astrophysics Data System (ADS)

Spataru, Catalin; Thurmer, Konrad

Various properties of supported graphene films depend strongly on the exact positions of carbon atoms with respect to the underlying substrate. While density functional theory (DFT) can predict atom position in many systems, it cannot be applied straightforwardly to systems that are incommensurate or have large unit cells, such as graphene on a BN surface. We address these limitations by developing a simple moiré model with parameters derived from DFT calculations for systems strained into commensurate structures with manageable unit cell sizes. Our moiré model, which takes into account the flexural rigidity of graphene and includes the influence of the substrate, is able to reproduce the DFT-relaxed carbon positions with an accuracy of <0.01 Å. We then apply this model to the unstrained C/BN system and predict how structure and energy vary with azimuthal orientation of the graphene sheet with respect to the BN substrate. Work supported by the Laboratory Directed Research and Development program at Sandia National Laboratories, a multi-program laboratory operated by Sandia Corporation, a Lockheed Martin Co., for the U.S. DOE under Contract DE-AC04-94AL85000.

Validation of Skeletal Muscle cis-Regulatory Module Predictions Reveals Nucleotide Composition Bias in Functional Enhancers

PubMed Central

Kwon, Andrew T.; Chou, Alice Yi; Arenillas, David J.; Wasserman, Wyeth W.

2011-01-01

We performed a genome-wide scan for muscle-specific cis-regulatory modules (CRMs) using three computational prediction programs. Based on the predictions, 339 candidate CRMs were tested in cell culture with NIH3T3 fibroblasts and C2C12 myoblasts for capacity to direct selective reporter gene expression to differentiated C2C12 myotubes. A subset of 19 CRMs validated as functional in the assay. The rate of predictive success reveals striking limitations of computational regulatory sequence analysis methods for CRM discovery. Motif-based methods performed no better than predictions based only on sequence conservation. Analysis of the properties of the functional sequences relative to inactive sequences identifies nucleotide sequence composition can be an important characteristic to incorporate in future methods for improved predictive specificity. Muscle-related TFBSs predicted within the functional sequences display greater sequence conservation than non-TFBS flanking regions. Comparison with recent MyoD and histone modification ChIP-Seq data supports the validity of the functional regions. PMID:22144875

Evaluation of a Hydrogen Fuel Cell Powered Blended-Wing-Body Aircraft Concept for Reduced Noise and Emissions

NASA Technical Reports Server (NTRS)

Guynn, Mark D.; Freh, Joshua E.; Olson, Erik D.

2004-01-01

This report describes the analytical modeling and evaluation of an unconventional commercial transport aircraft concept designed to address aircraft noise and emission issues. A blended-wing-body configuration with advanced technology hydrogen fuel cell electric propulsion is considered. Predicted noise and emission characteristics are compared to a current technology conventional configuration designed for the same mission. The significant technology issues which have to be addressed to make this concept a viable alternative to current aircraft designs are discussed. This concept is one of the "Quiet Green Transport" aircraft concepts studied as part of NASA's Revolutionary Aerospace Systems Concepts (RASC) Program. The RASC Program was initiated to develop revolutionary concepts that address strategic objectives of the NASA Enterprises, such as reducing aircraft noise and emissions, and to identify advanced technology requirements for the concepts.

The Association Between PD-L1 Expression and the Clinical Outcomes to Vascular Endothelial Growth Factor-Targeted Therapy in Patients With Metastatic Clear Cell Renal Cell Carcinoma

PubMed Central

Shin, Su-Jin; Jeon, Yoon Kyung; Cho, Yong Mee; Lee, Jae-Lyun; Chung, Doo Hyun; Park, Ji Young

2015-01-01

Background. Vascular endothelial growth factor pathway (VEGF)-tyrosine kinase inhibitors (TKIs) are used as the first-line treatment for patients with metastatic clear cell renal cell carcinoma (mCCRCC). Recently, programmed death-1 (PD-1) and programmed death ligand-1 (PD-L1) blockade emerged as promising therapy for renal cell carcinoma. However, the expression pattern and prognostic implication of programmed death-ligands (PD-Ls) in mCCRCC patients receiving VEGF-TKI remain unclear. Patients and Methods. PD-L1 and PD-L2 expression in tumor cells and the quantities of PD-1+ tumor-infiltrating lymphocytes were immunohistochemically evaluated in 91 mCCRCC patients treated with VEGF-TKI, and their associations with VEGF-TKI responsiveness and clinical outcome were analyzed. Results. PD-L1 immunopositivity was observed in 17.6% and significantly associated with a high International Society of Urological Pathology grade (p = .031) and sarcomatoid features (p = .014). PD-L2 immunopositivity was observed in 39.6% and was not associated with any of the assessed clinicopathological variables. PD-L1-positive cases showed poor VEGF-TKI responsiveness (p = .012) compared with PD-L1-negative cases. In univariate survival analysis, PD-L1 immunopositivity was significantly associated with shorter overall survival (OS) (p = .037) and progression-free survival (PFS) (p = .043). Multivariate survival analysis revealed that PD-L1 expression was independently associated with poor OS (p = .038) and PFS (p = .013) in addition to tumor necrosis (p = .006; p = .029, respectively) and Memorial Sloan Kettering Cancer Center score (p = .018; p = .032, respectively). PD-L2 expression was neither associated with VEGF-TKI responsiveness nor patients’ outcome. Conclusion. PD-L1 expression was significantly related to lack of VEGF-TKI responsiveness and independently associated with shorter survival in mCCRCC patients after VEGF-TKI treatment. PD-L1 may have a predictive and prognostic value for determining the value of VEGF-TKI treatment in patients with mCCRCC. Implications for Practice: Vascular endothelial growth factor pathway (VEGF)-tyrosine kinase inhibitors (TKIs) are essential for the treatment of metastatic renal cell carcinoma patients, but the treatment suffers from a lack of predictive markers. This study demonstrates that PD-L1 expression is a predictor for unfavorable response to VEGF-TKI and a prognostic indicator for poor overall survival and progression-free survival in patients with metastatic clear cell renal cell carcinoma receiving VEGF-TKI. PMID:26424759

Particle-In-Cell Modeling For MJ Dense Plasma Focus with Varied Anode Shape

NASA Astrophysics Data System (ADS)

Link, A.; Halvorson, C.; Schmidt, A.; Hagen, E. C.; Rose, D.; Welch, D.

2014-10-01

Megajoule scale dense plasma focus (DPF) Z-pinches with deuterium gas fill are compact devices capable of producing 1012 neutrons per shot but past predictive models of large-scale DPF have not included kinetic effects such as ion beam formation or anomalous resistivity. We report on progress of developing a predictive DPF model by extending our 2D axisymmetric collisional kinetic particle-in-cell (PIC) simulations to the 1 MJ, 2 MA Gemini DPF using the PIC code LSP. These new simulations incorporate electrodes, an external pulsed-power driver circuit, and model the plasma from insulator lift-off through the pinch phase. The simulations were performed using a new hybrid fluid-to-kinetic model transitioning from a fluid description to a fully kinetic PIC description during the run-in phase. Simulations are advanced through the final pinch phase using an adaptive variable time-step to capture the fs and sub-mm scales of the kinetic instabilities involved in the ion beam formation and neutron production. Results will be present on the predicted effects of different anode configurations. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory (LLNL) under Contract DE-AC52-07NA27344 and supported by the Laboratory Directed Research and Development Program (11-ERD-063) and the Computing Grand Challenge program at LLNL. This work supported by Office of Defense Nuclear Nonproliferation Research and Development within U.S. Department of Energy's National Nuclear Security Administration.

AMTEC radioisotope power system for the Pluto Express mission

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

Ivanenok, J.F. III; Sievers, R.K.

1995-12-31

The Alkali Metal Thermal to Electric Converter (AMTEC) technology has made substantial advances in the last 3 years through design improvements and technical innovations. In 1993 programs began to produce an AMTEC cell specifically for the NASA Pluto Express Mission. A set of efficiency goals was established for this series of cells to be developed. According to this plan, cell {number_sign}8 would be 17% efficient but was actually 18% efficient. Achieving this goal, as well as design advances that allow the cell to be compact, has resulted in pushing the cell from an unexciting 2 W/kg and 2% efficiency tomore » very attractive 40 W/kg and 18% measured efficiency. This paper will describe the design and predict the performance of a radioisotope powered AMTEC system for the Pluto Express mission.« less

Prioritizing CD4 Count Monitoring in Response to ART in Resource-Constrained Settings: A Retrospective Application of Prediction-Based Classification

PubMed Central

Liu, Yan; Li, Xiaohong; Johnson, Margaret; Smith, Collette; Kamarulzaman, Adeeba bte; Montaner, Julio; Mounzer, Karam; Saag, Michael; Cahn, Pedro; Cesar, Carina; Krolewiecki, Alejandro; Sanne, Ian; Montaner, Luis J.

2012-01-01

Background Global programs of anti-HIV treatment depend on sustained laboratory capacity to assess treatment initiation thresholds and treatment response over time. Currently, there is no valid alternative to CD4 count testing for monitoring immunologic responses to treatment, but laboratory cost and capacity limit access to CD4 testing in resource-constrained settings. Thus, methods to prioritize patients for CD4 count testing could improve treatment monitoring by optimizing resource allocation. Methods and Findings Using a prospective cohort of HIV-infected patients (n = 1,956) monitored upon antiretroviral therapy initiation in seven clinical sites with distinct geographical and socio-economic settings, we retrospectively apply a novel prediction-based classification (PBC) modeling method. The model uses repeatedly measured biomarkers (white blood cell count and lymphocyte percent) to predict CD4+ T cell outcome through first-stage modeling and subsequent classification based on clinically relevant thresholds (CD4+ T cell count of 200 or 350 cells/µl). The algorithm correctly classified 90% (cross-validation estimate = 91.5%, standard deviation [SD] = 4.5%) of CD4 count measurements <200 cells/µl in the first year of follow-up; if laboratory testing is applied only to patients predicted to be below the 200-cells/µl threshold, we estimate a potential savings of 54.3% (SD = 4.2%) in CD4 testing capacity. A capacity savings of 34% (SD = 3.9%) is predicted using a CD4 threshold of 350 cells/µl. Similar results were obtained over the 3 y of follow-up available (n = 619). Limitations include a need for future economic healthcare outcome analysis, a need for assessment of extensibility beyond the 3-y observation time, and the need to assign a false positive threshold. Conclusions Our results support the use of PBC modeling as a triage point at the laboratory, lessening the need for laboratory-based CD4+ T cell count testing; implementation of this tool could help optimize the use of laboratory resources, directing CD4 testing towards higher-risk patients. However, further prospective studies and economic analyses are needed to demonstrate that the PBC model can be effectively applied in clinical settings. Please see later in the article for the Editors' Summary PMID:22529752

Flocking Transition in Confluent Tissues

NASA Astrophysics Data System (ADS)

Paoluzzi, Matteo; Giavazzi, Fabio; Macchi, Marta; Scita, Giorgio; Cerbino, Roberto; Manning, Lisa; Marchetti, Cristina

The emerging of collective migration in biological tissues plays a pivotal role in embryonic morphogenesis, wound healing and cancer invasion. While many aspects of single cell movements are well established, the mechanisms leading to coherent displacements of cohesive cell groups are still poorly understood. Some of us recently proposed a Self-Propelled Voronoi (SPV) model of dense tissues that combines self-propelled particle models and vertex models of confluent cell layers and exhibits a liquid-solid transition as a function of cell shape and cell motility. We now examine the role of cell polarization on collective cell dynamics by introducing an orientation mechanism that aligns cell polarization with local cell motility. The model predicts a density-independent flocking transition tuned by the strength of the aligning interaction, with both solid and liquid flocking states existing in different regions of parameter space. MP and MCM were supported by the Simons Foundation Targeted Grant in the Mathematical Modeling of Living Systems Number: 342354 and by the Syracuse Soft Matter Program.

Decoding the Regulatory Network for Blood Development from Single-Cell Gene Expression Measurements

PubMed Central

Haghverdi, Laleh; Lilly, Andrew J.; Tanaka, Yosuke; Wilkinson, Adam C.; Buettner, Florian; Macaulay, Iain C.; Jawaid, Wajid; Diamanti, Evangelia; Nishikawa, Shin-Ichi; Piterman, Nir; Kouskoff, Valerie; Theis, Fabian J.; Fisher, Jasmin; Göttgens, Berthold

2015-01-01

Here we report the use of diffusion maps and network synthesis from state transition graphs to better understand developmental pathways from single cell gene expression profiling. We map the progression of mesoderm towards blood in the mouse by single-cell expression analysis of 3,934 cells, capturing cells with blood-forming potential at four sequential developmental stages. By adapting the diffusion plot methodology for dimensionality reduction to single-cell data, we reconstruct the developmental journey to blood at single-cell resolution. Using transitions between individual cellular states as input, we develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model that recapitulates blood development. Model predictions were validated by showing that Sox7 inhibits primitive erythropoiesis, and that Sox and Hox factors control early expression of Erg. We therefore demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that control organogenesis. PMID:25664528

Analytical determination of critical crack size in solar cells

NASA Technical Reports Server (NTRS)

Chen, C. P.

1988-01-01

Although solar cells usually have chips and cracks, no material specifications concerning the allowable crack size on solar cells are available for quality assurance and engineering design usage. Any material specifications that the cell manufacturers use were developed for cosmetic reasons that have no technical basis. Therefore, the Applied Solar Energy Corporation (ASEC) has sponsored a continuing program for the fracture mechanics evaluation of GaAs. Fracture mechanics concepts were utilized to develop an analytical model that can predict the critical crack size of solar cells. This model indicates that the edge cracks of a solar cell are more critical than its surface cracks. In addition, the model suggests that the material specifications on the allowable crack size used for Si solar cells should not be applied to GaAs solar cells. The analytical model was applied to Si and GaAs solar cells, but it would also be applicable to the semiconductor wafers of other materials, such as a GaAs thin film on a Ge substrate, using appropriate input data.

Immune Biomarkers Predictive for Disease-Free Survival with Adjuvant Sunitinib in High-Risk Locoregional Renal Cell Carcinoma: From Randomized Phase III S-TRAC Study.

PubMed

George, Daniel J; Martini, Jean-François; Staehler, Michael; Motzer, Robert J; Magheli, Ahmed; Escudier, Bernard; Gerletti, Paola; Li, Sherry; Casey, Michelle; Laguerre, Brigitte; Pandha, Hardev S; Pantuck, Allan J; Patel, Anup; Lechuga, Maria J; Ravaud, Alain

2018-04-01

Purpose: Adjuvant sunitinib therapy compared with placebo prolonged disease-free survival (DFS) in patients with locoregional high-risk renal cell carcinoma (RCC) in the S-TRAC trial (ClinicalTrials.gov number NCT00375674). A prospectively designed exploratory analysis of tissue biomarkers was conducted to identify predictors of treatment benefit. Experimental Design: Tissue blocks were used for immunohistochemistry (IHC) staining of programmed cell death ligand 1 (PD-L1), CD4, CD8, and CD68. DFS was compared between < versus ≥ median IHC parameter using the Kaplan-Meier method. For biomarkers with predictive potential, receiver operating characteristics curves were generated. Results: Baseline characteristics were similar in patients with ( n = 191) and without ( n = 419) IHC analysis. Among patients with IHC, longer DFS was observed in patients with tumor CD8 + T-cell density ≥ versus < median [median (95% CI), not reached (6.83-not reached) versus 3.47 years (1.73-not reached); hazard ratio (HR) 0.40 (95% CI, 0.20-0.81); P = 0.009] treated with sunitinib ( n = 101), but not with placebo ( n = 90). The sensitivity and specificity for CD8 + T-cell density in predicting DFS were 0.604 and 0.658, respectively. Shorter DFS was observed in placebo-treated patients with PD-L1 + versus PD-L1 - tumors (HR 1.75; P = 0.103). Among all patients with PD-L1 + tumors, DFS was numerically longer with sunitinib versus placebo (HR 0.58; P = 0.175). Conclusions: Greater CD8 + T-cell density in tumor tissue was associated with longer DFS with sunitinib but not placebo, suggesting predictive treatment effect utility. Further independent cohort validation studies are warranted. The prognostic value of PD-L1 expression in primary tumors from patients with high-risk nonmetastatic RCC should also be further explored. Clin Cancer Res; 24(7); 1554-61. ©2018 AACR . ©2018 American Association for Cancer Research.

Modeling of Sonos Memory Cell Erase Cycle

NASA Technical Reports Server (NTRS)

Phillips, Thomas A.; MacLeond, Todd C.; Ho, Fat D.

2010-01-01

Silicon-oxide-nitride-oxide-silicon (SONOS) nonvolatile semiconductor memories (NVSMS) have many advantages. These memories are electrically erasable programmable read-only memories (EEPROMs). They utilize low programming voltages, endure extended erase/write cycles, are inherently resistant to radiation, and are compatible with high-density scaled CMOS for low power, portable electronics. The SONOS memory cell erase cycle was investigated using a nonquasi-static (NQS) MOSFET model. The SONOS floating gate charge and voltage, tunneling current, threshold voltage, and drain current were characterized during an erase cycle. Comparisons were made between the model predictions and experimental device data.

Predictive factors for red blood cell transfusion in children undergoing noncomplex cardiac surgery.

PubMed

Mulaj, Muj; Faraoni, David; Willems, Ariane; Sanchez Torres, Cristel; Van der Linden, Philippe

2014-08-01

Red blood cell (RBC) transfusion is frequently required in pediatric cardiac surgery and is associated with altered outcome and increased costs. Determining which factors predict transfusion in this context will enable clinicians to adopt strategies that will reduce the risk of RBC transfusion. This study aimed to assess predictive factors associated with RBC transfusion in children undergoing low-risk cardiac surgery with cardiopulmonary bypass (CPB). Children undergoing surgery to repair ventricular septal defect or atrioventricular septal defect from 2006 to 2011 were included in this retrospective study. Demography, preoperative laboratory testing, intraoperative data, and RBC transfusion were reviewed. Univariate and multivariate logistic regression analysis were used to define factors that were able to predict RBC transfusion. Then, we employed receiver operating characteristic analysis to design a predictive score. Among the 334 children included, 261 (78%) were transfused. Age (<18 months), priming volume of the CPB (>43 mL/kg), type of oxygenator used, minimal temperature reached during CPB (<32°C), and preoperative hematocrit (<34%) were independently associated with RBC transfusion in the studied population. A predictive score 2 or greater was the best predictor of RBC transfusion. The present study identified several factors that were significantly associated with perioperative RBC transfusion. Based on these factors, we designed a predictive score that can be used to develop a patient-based blood management program with the aim of reducing the incidence of RBC transfusion. Copyright © 2014 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Designing optimal cell factories: integer programming couples elementary mode analysis with regulation

PubMed Central

2012-01-01

Background Elementary mode (EM) analysis is ideally suited for metabolic engineering as it allows for an unbiased decomposition of metabolic networks in biologically meaningful pathways. Recently, constrained minimal cut sets (cMCS) have been introduced to derive optimal design strategies for strain improvement by using the full potential of EM analysis. However, this approach does not allow for the inclusion of regulatory information. Results Here we present an alternative, novel and simple method for the prediction of cMCS, which allows to account for boolean transcriptional regulation. We use binary linear programming and show that the design of a regulated, optimal metabolic network of minimal functionality can be formulated as a standard optimization problem, where EM and regulation show up as constraints. We validated our tool by optimizing ethanol production in E. coli. Our study showed that up to 70% of the predicted cMCS contained non-enzymatic, non-annotated reactions, which are difficult to engineer. These cMCS are automatically excluded by our approach utilizing simple weight functions. Finally, due to efficient preprocessing, the binary program remains computationally feasible. Conclusions We used integer programming to predict efficient deletion strategies to metabolically engineer a production organism. Our formulation utilizes the full potential of cMCS but adds additional flexibility to the design process. In particular our method allows to integrate regulatory information into the metabolic design process and explicitly favors experimentally feasible deletions. Our method remains manageable even if millions or potentially billions of EM enter the analysis. We demonstrated that our approach is able to correctly predict the most efficient designs for ethanol production in E. coli. PMID:22898474

The COOLER Code: A Novel Analytical Approach to Calculate Subcellular Energy Deposition by Internal Electron Emitters.

PubMed

Siragusa, Mattia; Baiocco, Giorgio; Fredericia, Pil M; Friedland, Werner; Groesser, Torsten; Ottolenghi, Andrea; Jensen, Mikael

2017-08-01

COmputation Of Local Electron Release (COOLER), a software program has been designed for dosimetry assessment at the cellular/subcellular scale, with a given distribution of administered low-energy electron-emitting radionuclides in cellular compartments, which remains a critical step in risk/benefit analysis for advancements in internal radiotherapy. The software is intended to overcome the main limitations of the medical internal radiation dose (MIRD) formalism for calculations of cellular S-values (i.e., dose to a target region in the cell per decay in a given source region), namely, the use of the continuous slowing down approximation (CSDA) and the assumption of a spherical cell geometry. To this aim, we developed an analytical approach, entrusted to a MATLAB-based program, using as input simulated data for electron spatial energy deposition directly derived from full Monte Carlo track structure calculations with PARTRAC. Results from PARTRAC calculations on electron range, stopping power and residual energy versus traveled distance curves are presented and, when useful for implementation in COOLER, analytical fit functions are given. Example configurations for cells in different culture conditions (V79 cells in suspension or adherent culture) with realistic geometrical parameters are implemented for use in the tool. Finally, cellular S-value predictions by the newly developed code are presented for different cellular geometries and activity distributions (uniform activity in the nucleus, in the entire cell or on the cell surface), validated against full Monte Carlo calculations with PARTRAC, and compared to MIRD standards, as well as results based on different track structure calculations (Geant4-DNA). The largest discrepancies between COOLER and MIRD predictions were generally found for electrons between 25 and 30 keV, where the magnitude of disagreement in S-values can vary from 50 to 100%, depending on the activity distribution. In calculations for activity distribution on the cell surface, MIRD predictions appeared to fail the most. The proposed method is suitable for Auger-cascade electrons, but can be extended to any energy of interest and to beta spectra; as an example, the 3 H case is also discussed. COOLER is intended to be accessible to everyone (preclinical and clinical researchers included), and may provide important information for the selection of radionuclides, the interpretation of radiobiological or preclinical results, and the general establishment of doses in any scenario, e.g., with cultured cells in the laboratory or with therapeutic or diagnostic applications. The software will be made available for download from the DTU-Nutech website: http://www.nutech.dtu.dk/ .

Intrinsically Disordered Proteins and the Origins of Multicellular Organisms

NASA Astrophysics Data System (ADS)

Dunker, A. Keith

In simple multicellular organisms all of the cells are in direct contact with the surrounding milieu, whereas in complex multicellular organisms some cells are completely surrounded by other cells. Current phylogenetic trees indicate that complex multicellular organisms evolved independently from unicellular ancestors about 10 times, and only among the eukaryotes, including once for animals, twice each for green, red, and brown algae, and thrice for fungi. Given these multiple independent evolutionary lineages, we asked two questions: 1. Which molecular functions underpinned the evolution of multicellular organisms?; and, 2. Which of these molecular functions depend on intrinsically disordered proteins (IDPs)? Compared to unicellularity, multicellularity requires the advent of molecules for cellular adhesion, for cell-cell communication and for developmental programs. In addition, the developmental programs need to be regulated over space and time. Finally, each multicellular organism has cell-specific biochemistry and physiology. Thus, the evolution of complex multicellular organisms from unicellular ancestors required five new classes of functions. To answer the second question we used Key-words in Swiss Protein ranked for associations with predictions of protein structure or disorder. With a Z-score of 18.8 compared to random-function proteins, à differentiation was the biological process most strongly associated with IDPs. As expected from this result, large numbers of individual proteins associated with differentiation exhibit substantial regions of predicted disorder. For the animals for which there is the most readily available data all five of the underpinning molecular functions for multicellularity were found to depend critically on IDP-based mechanisms and other evidence supports these ideas. While the data are more sparse, IDPs seem to similarly underlie the five new classes of functions for plants and fungi as well, suggesting that IDPs were indeed crucial for the evolution of complex multicellular organisms. These new findings necessitate a rethinking of the gene regulatory network models currently used to explain cellular differentiation and the evolution of complex multicellular organisms.

Modelling and Simulation of the Dynamics of the Antigen-Specific T Cell Response Using Variable Structure Control Theory.

PubMed

Anelone, Anet J N; Spurgeon, Sarah K

2016-01-01

Experimental and mathematical studies in immunology have revealed that the dynamics of the programmed T cell response to vigorous infection can be conveniently modelled using a sigmoidal or a discontinuous immune response function. This paper hypothesizes strong synergies between this existing work and the dynamical behaviour of engineering systems with a variable structure control (VSC) law. These findings motivate the interpretation of the immune system as a variable structure control system. It is shown that dynamical properties as well as conditions to analytically assess the transition from health to disease can be developed for the specific T cell response from the theory of variable structure control. In particular, it is shown that the robustness properties of the specific T cell response as observed in experiments can be explained analytically using a VSC perspective. Further, the predictive capacity of the VSC framework to determine the T cell help required to overcome chronic Lymphocytic Choriomeningitis Virus (LCMV) infection is demonstrated. The findings demonstrate that studying the immune system using variable structure control theory provides a new framework for evaluating immunological dynamics and experimental observations. A modelling and simulation tool results with predictive capacity to determine how to modify the immune response to achieve healthy outcomes which may have application in drug development and vaccine design.

The Distribution of Chromosomal Aberrations in Human Cells Predicted by a Generalized Time-Dependent Model of Radiation-Induced Formation of Aberrations

NASA Technical Reports Server (NTRS)

Ponomarev, Artem L.; George, K.; Cucinotta, F. A.

2011-01-01

New experimental data show how chromosomal aberrations for low- and high-LET radiation are dependent on DSB repair deficiencies in wild-type, AT and NBS cells. We simulated the development of chromosomal aberrations in these cells lines in a stochastic track-structure-dependent model, in which different cells have different kinetics of DSB repair. We updated a previously formulated model of chromosomal aberrations, which was based on a stochastic Monte Carlo approach, to consider the time-dependence of DSB rejoining. The previous version of the model had an assumption that all DSBs would rejoin, and therefore we called it a time-independent model. The chromosomal-aberrations model takes into account the DNA and track structure for low- and high-LET radiations, and provides an explanation and prediction of the statistics of rare and more complex aberrations. We compared the program-simulated kinetics of DSB rejoining to the experimentally-derived bimodal exponential curves of the DSB kinetics. We scored the formation of translocations, dicentrics, acentric and centric rings, deletions, and inversions. The fraction of DSBs participating in aberrations was studied in relation to the rejoining time. Comparisons of simulated dose dependence for simple aberrations to the experimental dose-dependence for HF19, AT and NBS cells will be made.

The genetic network controlling plasma cell differentiation.

PubMed

Nutt, Stephen L; Taubenheim, Nadine; Hasbold, Jhagvaral; Corcoran, Lynn M; Hodgkin, Philip D

2011-10-01

Upon activation by antigen, mature B cells undergo immunoglobulin class switch recombination and differentiate into antibody-secreting plasma cells, the endpoint of the B cell developmental lineage. Careful quantitation of these processes, which are stochastic, independent and strongly linked to the division history of the cell, has revealed that populations of B cells behave in a highly predictable manner. Considerable progress has also been made in the last few years in understanding the gene regulatory network that controls the B cell to plasma cell transition. The mutually exclusive transcriptomes of B cells and plasma cells are maintained by the antagonistic influences of two groups of transcription factors, those that maintain the B cell program, including Pax5, Bach2 and Bcl6, and those that promote and facilitate plasma cell differentiation, notably Irf4, Blimp1 and Xbp1. In this review, we discuss progress in the definition of both the transcriptional and cellular events occurring during late B cell differentiation, as integrating these two approaches is crucial to defining a regulatory network that faithfully reflects the stochastic features and complexity of the humoral immune response. 2011 Elsevier Ltd. All rights reserved.

Ricinosomes Predict Programmed Cell Death Leading to Anther Dehiscence in Tomato1[C][W][OA

PubMed Central

Senatore, Adriano; Trobacher, Christopher P.; Greenwood, John S.

2009-01-01

Successful development and dehiscence of the anther and release of pollen are dependent upon the programmed cell death (PCD) of the tapetum and other sporophytic tissues. Ultrastructural examination of the developing and dehiscing anther of tomato (Solanum lycopersicum) revealed that cells of the interlocular septum, the connective tissue, the middle layer/endothecium, and the epidermal cells surrounding the stomium all exhibit features consistent with progression through PCD. Ricinosomes, a subset of precursor protease vesicles that are unique to some incidents of plant PCD, were also present in all of these cell types. These novel organelles are known to harbor KDEL-tailed cysteine proteinases that act in the final stages of corpse processing following cell death. Indeed, a tomato KDEL-tailed cysteine proteinase, SlCysEP, was identified and its gene was cloned, sequenced, and characterized. SlCysEP transcript and protein were restricted to the anthers of the senescing tomato flower. Present in the interlocular septum and in the epidermal cells surrounding the stomium relatively early in development, SlCysEP accumulates later in the sporophytic tissues surrounding the locules as dehiscence ensues. At the ultrastuctural level, immunogold labeling localized SlCysEP to the ricinosomes within the cells of these tissues, but not in the tapetum. It is suggested that the accumulation of SlCysEP and the appearance of ricinosomes act as very early predictors of cell death in the tomato anther. PMID:19098090

Dissecting Germ Cell Metabolism through Network Modeling.

PubMed

Whitmore, Leanne S; Ye, Ping

2015-01-01

Metabolic pathways are increasingly postulated to be vital in programming cell fate, including stemness, differentiation, proliferation, and apoptosis. The commitment to meiosis is a critical fate decision for mammalian germ cells, and requires a metabolic derivative of vitamin A, retinoic acid (RA). Recent evidence showed that a pulse of RA is generated in the testis of male mice thereby triggering meiotic commitment. However, enzymes and reactions that regulate this RA pulse have yet to be identified. We developed a mouse germ cell-specific metabolic network with a curated vitamin A pathway. Using this network, we implemented flux balance analysis throughout the initial wave of spermatogenesis to elucidate important reactions and enzymes for the generation and degradation of RA. Our results indicate that primary RA sources in the germ cell include RA import from the extracellular region, release of RA from binding proteins, and metabolism of retinal to RA. Further, in silico knockouts of genes and reactions in the vitamin A pathway predict that deletion of Lipe, hormone-sensitive lipase, disrupts the RA pulse thereby causing spermatogenic defects. Examination of other metabolic pathways reveals that the citric acid cycle is the most active pathway. In addition, we discover that fatty acid synthesis/oxidation are the primary energy sources in the germ cell. In summary, this study predicts enzymes, reactions, and pathways important for germ cell commitment to meiosis. These findings enhance our understanding of the metabolic control of germ cell differentiation and will help guide future experiments to improve reproductive health.

Trial watch: Immune checkpoint blockers for cancer therapy.

PubMed

Vanpouille-Box, Claire; Lhuillier, Claire; Bezu, Lucillia; Aranda, Fernando; Yamazaki, Takahiro; Kepp, Oliver; Fucikova, Jitka; Spisek, Radek; Demaria, Sandra; Formenti, Silvia C; Zitvogel, Laurence; Kroemer, Guido; Galluzzi, Lorenzo

2017-01-01

Immune checkpoint blockers (ICBs) are literally revolutionizing the clinical management of an ever more diversified panel of oncological indications. Although considerable attention persists around the inhibition of cytotoxic T lymphocyte-associated protein 4 (CTLA4) and programmed cell death 1 (PDCD1, best known as PD-1) signaling, several other co-inhibitory T-cell receptors are being evaluated as potential targets for the development of novel ICBs. Moreover, substantial efforts are being devoted to the identification of biomarkers that reliably predict the likelihood of each patient to obtain clinical benefits from ICBs in the absence of severe toxicity. Tailoring the delivery of specific ICBs or combinations thereof to selected patient populations in the context of precision medicine programs constitutes indeed a major objective of the future of ICB-based immunotherapy. Here, we discuss recent preclinical and clinical advances on the development of ICBs for oncological indications.

Feed-forward transcriptional programming by nuclear receptors: regulatory principles and therapeutic implications.

PubMed

Sasse, Sarah K; Gerber, Anthony N

2015-01-01

Nuclear receptors (NRs) are widely targeted to treat a range of human diseases. Feed-forward loops are an ancient mechanism through which single cell organisms organize transcriptional programming and modulate gene expression dynamics, but they have not been systematically studied as a regulatory paradigm for NR-mediated transcriptional responses. Here, we provide an overview of the basic properties of feed-forward loops as predicted by mathematical models and validated experimentally in single cell organisms. We review existing evidence implicating feed-forward loops as important in controlling clinically relevant transcriptional responses to estrogens, progestins, and glucocorticoids, among other NR ligands. We propose that feed-forward transcriptional circuits are a major mechanism through which NRs integrate signals, exert temporal control over gene regulation, and compartmentalize client transcriptomes into discrete subunits. Implications for the design and function of novel selective NR ligands are discussed. Copyright © 2014 Elsevier Inc. All rights reserved.

Determining the Localization of Carbohydrate Active Enzymes Within Gram-Negative Bacteria.

PubMed

McLean, Richard; Inglis, G Douglas; Mosimann, Steven C; Uwiera, Richard R E; Abbott, D Wade

2017-01-01

Investigating the subcellular location of secreted proteins is valuable for illuminating their biological function. Although several bioinformatics programs currently exist to predict the destination of a trafficked protein using its signal peptide sequence, these programs have limited accuracy and often require experimental validation. Here, we present a systematic method to fractionate gram-negative cells and characterize the subcellular localization of secreted carbohydrate active enzymes (CAZymes). This method involves four parallel approaches that reveal the relative abundance of protein within the cytoplasm, periplasm, outer membrane, and extracellular environment. Cytoplasmic and periplasmic proteins are fractionated by lysis and osmotic shock, respectively. Outer membrane bound proteins are determined by comparing cells before and after exoproteolytic digestion. Extracellularly secreted proteins are collected from the media and concentrated. These four different fractionations can then be probed for the presence and quantity of target proteins using immunochemical methods such as Western blots and ELISAs, or enzyme activity assays.

Primary zinc-air batteries for space power

NASA Technical Reports Server (NTRS)

Bragg, Bobby J.; Bourland, Deborah S.; Merry, Glenn; Putt, Ron

1992-01-01

Prismatic HR and LC cells and batteries were built and tested, and they performed well with respect to the program goals of high capacity and high rate capability at specific energies. The HR batteries suffered reduced utilizations owing to dryout at the 2 and 3 A rates for the 50 C tests owing to the requirement for forced convection. The LC batteries suffered reduced utilizations under all conditions owing to the chimney effect at 1 G, although this effect would not occur at 0 G. An empirical model was developed which accurately predicted utilizations and average voltages for single cells, although thermal effects encountered during battery testing caused significant deviations, both positive and negative, from the model. Based on the encouraging results of the test program, we believe that the zinc-air primary battery of a flat, stackable configuration can serve as a high performance and safe power source for a range of space applications.

Mechanisms of immune evasion and current status of checkpoint inhibitors in non-small cell lung cancer.

PubMed

Qin, Angel; Coffey, David G; Warren, Edus H; Ramnath, Nithya

2016-09-01

In the past several years, immunotherapy has emerged as a viable treatment option for patients with advanced non-small cell lung cancer (NSCLC) without actionable driver mutations that have progressed on standard chemotherapy. We are also beginning to understand the methods of immune evasion employed by NSCLC which likely contribute to the 20% response rate to immunotherapy. It is also yet unclear what tumor or patient factors predict response to immunotherapy. The objectives of this review are (1) review the immunogenicity of NSCLC (2) describe the mechanisms of immune evasion (3) summarize efforts to target the anti-program death-1 (PD-1) and anti-program death-ligand 1(PD-L1) pathway (4) outline determinants of response to PD-1/PD-L1 therapy and (5) discuss potential future areas for research. © 2016 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

RAD-ADAPT: Software for modelling clonogenic assay data in radiation biology.

PubMed

Zhang, Yaping; Hu, Kaiqiang; Beumer, Jan H; Bakkenist, Christopher J; D'Argenio, David Z

2017-04-01

We present a comprehensive software program, RAD-ADAPT, for the quantitative analysis of clonogenic assays in radiation biology. Two commonly used models for clonogenic assay analysis, the linear-quadratic model and single-hit multi-target model, are included in the software. RAD-ADAPT uses maximum likelihood estimation method to obtain parameter estimates with the assumption that cell colony count data follow a Poisson distribution. The program has an intuitive interface, generates model prediction plots, tabulates model parameter estimates, and allows automatic statistical comparison of parameters between different groups. The RAD-ADAPT interface is written using the statistical software R and the underlying computations are accomplished by the ADAPT software system for pharmacokinetic/pharmacodynamic systems analysis. The use of RAD-ADAPT is demonstrated using an example that examines the impact of pharmacologic ATM and ATR kinase inhibition on human lung cancer cell line A549 after ionizing radiation. Copyright © 2017 Elsevier B.V. All rights reserved.

Interferon Gamma Messenger RNA Signature in Tumor Biopsies Predicts Outcomes in Patients with Non-Small-Cell Lung Carcinoma or Urothelial Cancer Treated with Durvalumab.

PubMed

Higgs, Brandon W; Morehouse, Christopher; Streicher, Katie L; Brohawn, Philip; Pilataxi, Fernanda; Gupta, Ashok; Ranade, Koustubh

2018-05-01

To identify a predictive biomarker for durvalumab, an anti-programmed death ligand 1 (PD-L1) monoclonal antibody. RNA sequencing of 97 advanced-stage non-small-cell lung carcinoma (NSCLC) biopsies from a nonrandomized phase 1b/2 clinical trial (1108/NCT01693562) were profiled to identify a predictive signature; 62 locally advanced or metastatic urothelial cancer (UC) tumors from the same study were profiled to confirm predictive utility of the signature. Thirty NSCLC patients provided pre- and posttreatment tumors for messenger RNA (mRNA) analysis. NSCLC with ≥25% tumor cells and UC with ≥25% tumor or immune cells stained for PD-L1 at any intensity were scored PD-L1 positive (PD-L1+). Kaplan-Meier and Cox proportional hazards analyses were used to adjust for gender, age, prior therapies, histology, ECOG, liver metastasis, and smoking. Tumor mutation burden (TMB) was calculated using data from The Cancer Genome Atlas (TCGA).  In the NSCLC discovery set, a four-gene interferon gamma (IFNγ)-positive (IFNγ+) signature comprising IFNγ, CD274, LAG3, and CXCL9 was associated with higher overall response rates, longer median progression-free survival, and overall survival compared with signature-low patients. IFNγ+-signature NSCLC patients had improved survival regardless of immunohistochemistry (IHC) PD-L1 status. These associations were replicated in a UC cohort. The IFNγ+ signature was induced twofold (P = 0.003) by durvalumab after 8 weeks of therapy in NSCLC patients, and baseline signature was associated with TMB but not survival in TCGA data.  The IFNγ+ mRNA signature may assist in identifying patients with improved outcomes to durvalumab, independent of PD-L1 assessed by IHC. Copyright ©2018, American Association for Cancer Research.

Expression mapping using a retroviral vector for CD8+ T cell epitopes: definition of a Mycobacterium tuberculosis peptide presented by H2-Dd.

PubMed

Aoshi, Taiki; Suzuki, Mina; Uchijima, Masato; Nagata, Toshi; Koide, Yukio

2005-03-01

Identification of CD8+ T cell epitopes is important because detection of specific CD8+ T cells after infection or immunization requires prior knowledge of epitope specificity. Furthermore, identification of CD8+ T cell epitopes permits the development of specific preventive and therapeutic approaches to both infections and tumors. Thus far, CD8+ T cell epitopes have been identified either using an overlapping peptide library covering an entire protein, or using algorithms designed to identify likely peptides that bind to major histocompatibility complex (MHC) class I molecules. The synthesis of overlapping peptides can be prohibitively expensive, and the algorithm programs used to predict CD8+ T cell epitopes are not always accurate. Here we describe a retroviral expression system that specifically allows longer polypeptides and shorter peptides to be expressed in the cytoplasm, and thereby to be processed onto class I MHC molecules. T cells from mice that were immunized with a DNA vaccine encoding MPT-51 were probed against MHC-compatible cell lines retrovirally transduced with overlapping gene fragments encoding 120-140 amino acids of the MPT-51 molecule. After further testing of shorter peptide sequences, we identified a CD8+ T cell epitope using cell lines expressing a relatively small number of algorithm-predicted candidate epitopes. We found that one of the requirements for cell surface display of the 20-mer peptide was the need for cotranslational ubiquitination. The restriction molecule was identified as Dd following transduction with MHC class I genes followed by transduction with the oligonucleotide encoding the epitope. The retroviral expression system described here is cost-effective, particularly if the target molecule is large, and could be adapted to identifying T cell epitopes recognized in infectious disease and against tumor cell antigens.

A novel representation for apoptosis protein subcellular localization prediction using support vector machine.

PubMed

Zhang, Li; Liao, Bo; Li, Dachao; Zhu, Wen

2009-07-21

Apoptosis, or programmed cell death, plays an important role in development of an organism. Obtaining information on subcellular location of apoptosis proteins is very helpful to understand the apoptosis mechanism. In this paper, based on the concept that the position distribution information of amino acids is closely related with the structure and function of proteins, we introduce the concept of distance frequency [Matsuda, S., Vert, J.P., Ueda, N., Toh, H., Akutsu, T., 2005. A novel representation of protein sequences for prediction of subcellular location using support vector machines. Protein Sci. 14, 2804-2813] and propose a novel way to calculate distance frequencies. In order to calculate the local features, each protein sequence is separated into p parts with the same length in our paper. Then we use the novel representation of protein sequences and adopt support vector machine to predict subcellular location. The overall prediction accuracy is significantly improved by jackknife test.

Active model-based balancing strategy for self-reconfigurable batteries

NASA Astrophysics Data System (ADS)

Bouchhima, Nejmeddine; Schnierle, Marc; Schulte, Sascha; Birke, Kai Peter

2016-08-01

This paper describes a novel balancing strategy for self-reconfigurable batteries where the discharge and charge rates of each cell can be controlled. While much effort has been focused on improving the hardware architecture of self-reconfigurable batteries, energy equalization algorithms have not been systematically optimized in terms of maximizing the efficiency of the balancing system. Our approach includes aspects of such optimization theory. We develop a balancing strategy for optimal control of the discharge rate of battery cells. We first formulate the cell balancing as a nonlinear optimal control problem, which is modeled afterward as a network program. Using dynamic programming techniques and MATLAB's vectorization feature, we solve the optimal control problem by generating the optimal battery operation policy for a given drive cycle. The simulation results show that the proposed strategy efficiently balances the cells over the life of the battery, an obvious advantage that is absent in the other conventional approaches. Our algorithm is shown to be robust when tested against different influencing parameters varying over wide spectrum on different drive cycles. Furthermore, due to the little computation time and the proved low sensitivity to the inaccurate power predictions, our strategy can be integrated in a real-time system.

Vacuolar processing enzyme in plant programmed cell death

PubMed Central

Hatsugai, Noriyuki; Yamada, Kenji; Goto-Yamada, Shino; Hara-Nishimura, Ikuko

2015-01-01

Vacuolar processing enzyme (VPE) is a cysteine proteinase originally identified as the proteinase responsible for the maturation and activation of vacuolar proteins in plants, and it is known to be an ortholog of animal asparaginyl endopeptidase (AEP/VPE/legumain). VPE has been shown to exhibit enzymatic properties similar to that of caspase 1, which is a cysteine protease that mediates the programmed cell death (PCD) pathway in animals. Although there is limited sequence identity between VPE and caspase 1, their predicted three-dimensional structures revealed that the essential amino-acid residues for these enzymes form similar pockets for the substrate peptide YVAD. In contrast to the cytosolic localization of caspases, VPE is localized in vacuoles. VPE provokes vacuolar rupture, initiating the proteolytic cascade leading to PCD in the plant immune response. It has become apparent that the VPE-dependent PCD pathway is involved not only in the immune response, but also in the responses to a variety of stress inducers and in the development of various tissues. This review summarizes the current knowledge on the contribution of VPE to plant PCD and its role in vacuole-mediated cell death, and it also compares VPE with the animal cell death executor caspase 1. PMID:25914711

Predicting discovery rates of genomic features.

PubMed

Gravel, Simon

2014-06-01

Successful sequencing experiments require judicious sample selection. However, this selection must often be performed on the basis of limited preliminary data. Predicting the statistical properties of the final sample based on preliminary data can be challenging, because numerous uncertain model assumptions may be involved. Here, we ask whether we can predict "omics" variation across many samples by sequencing only a fraction of them. In the infinite-genome limit, we find that a pilot study sequencing 5% of a population is sufficient to predict the number of genetic variants in the entire population within 6% of the correct value, using an estimator agnostic to demography, selection, or population structure. To reach similar accuracy in a finite genome with millions of polymorphisms, the pilot study would require ∼15% of the population. We present computationally efficient jackknife and linear programming methods that exhibit substantially less bias than the state of the art when applied to simulated data and subsampled 1000 Genomes Project data. Extrapolating based on the National Heart, Lung, and Blood Institute Exome Sequencing Project data, we predict that 7.2% of sites in the capture region would be variable in a sample of 50,000 African Americans and 8.8% in a European sample of equal size. Finally, we show how the linear programming method can also predict discovery rates of various genomic features, such as the number of transcription factor binding sites across different cell types. Copyright © 2014 by the Genetics Society of America.

Porous matrix structures for alkaline electrolyte fuel cells

NASA Technical Reports Server (NTRS)

Vine, R. W.; Narsavage, S. T.

1975-01-01

A number of advancements have been realized by a continuing research program to develop higher chemically stable porous matrix structures with high bubble pressure (crossover resistance) for use as separators in potassium hydroxide electrolyte fuel cells. More uniform, higher-bubble-pressure asbestos matrices were produced by reconstituting Johns-Manville asbestos paper; Fybex potassium titanate which was found compatible with 42% KOH at 250 F for up to 3000 hr; good agreement was found between bubble pressures predicted by an analytical study and those measured with filtered structures; Teflon-bonded Fybex matrices with bubble pressures greater than 30 psi were obtained by filtering a water slurry of the mixture directly onto fuel cell electrodes; and PBI fibers have satisfactory compatibility with 42% KOH at 250 F.

PCR-based detection of a rare linear DNA in cell culture.

PubMed

Saveliev, Sergei V.

2002-11-11

The described method allows for detection of rare linear DNA fragments generated during genomic deletions. The predicted limit of the detection is one DNA molecule per 10(7) or more cells. The method is based on anchor PCR and involves gel separation of the linear DNA fragment and chromosomal DNA before amplification. The detailed chemical structure of the ends of the linear DNA can be defined with the use of additional PCR-based protocols. The method was applied to study the short-lived linear DNA generated during programmed genomic deletions in a ciliate. It can be useful in studies of spontaneous DNA deletions in cell culture or for tracking intracellular modifications at the ends of transfected DNA during gene therapy trials.

PCR-based detection of a rare linear DNA in cell culture

PubMed Central

2002-01-01

The described method allows for detection of rare linear DNA fragments generated during genomic deletions. The predicted limit of the detection is one DNA molecule per 107 or more cells. The method is based on anchor PCR and involves gel separation of the linear DNA fragment and chromosomal DNA before amplification. The detailed chemical structure of the ends of the linear DNA can be defined with the use of additional PCR-based protocols. The method was applied to study the short-lived linear DNA generated during programmed genomic deletions in a ciliate. It can be useful in studies of spontaneous DNA deletions in cell culture or for tracking intracellular modifications at the ends of transfected DNA during gene therapy trials. PMID:12734566

Fiber-Optic Array Scanning Technology (FAST) for Detection and Molecular Characterization of Circulating Tumor Cells.

PubMed

Ao, Zheng; Liu, Xiaohe

2017-01-01

Circulating tumor cell (CTC) as an important component in "liquid biopsy" holds crucial clinical relevance in cancer prognosis, treatment efficiency evaluation, prediction and potentially early detection. Here, we present a Fiber-optic Array Scanning Technology (FAST) that enables antigen-agnostic, size-agnostic detection of CTC. By immunofluorescence staining detection of a combination of a panel of markers, FAST technology can be applied to detect rare CTC in non-small cell lung cancer (NSCLC) setting with high sensitivity and specificity. In combination with Automated Digital Microscopy (ADM) platform, companion markers on CTC such as Vimentin and Programmed death-ligand 1 (PD-L1) can also be analyzed to further characterize these CTCs. FAST data output is also compatible with downstream single cell picking platforms. Single cell can be isolated post ADM confirmation and used for "actionable" genetic mutations analysis.

A Summary of The 2000-2001 NASA Glenn Lear Jet AM0 Solar Cell Calibration Program

NASA Technical Reports Server (NTRS)

Scheiman, David; Brinker, David; Snyder, David; Baraona, Cosmo; Jenkins, Phillip; Rieke, William J.; Blankenship, Kurt S.; Tom, Ellen M.

2002-01-01

Calibration of solar cells for space is extremely important for satellite power system design. Accurate prediction of solar cell performance is critical to solar array sizing, often required to be within 1%. The NASA Glenn Research Center solar cell calibration airplane facility has been in operation since 1963 with 531 flights to date. The calibration includes real data to Air Mass (AM) 0.2 and uses the Langley plot method plus an ozone correction factor to extrapolate to AM0. Comparison of the AM0 calibration data indicates that there is good correlation with Balloon and Shuttle flown solar cells. This paper will present a history of the airplane calibration procedure, flying considerations, and a brief summary of the previous flying season with some measurement results. This past flying season had a record 35 flights. It will also discuss efforts to more clearly define the ozone correction factor.

Use of the partial farm budget technique to predict the economic impact of the flock management decision to use B-mode ultrasonographic pregnancy diagnosis.

PubMed

Sprecher, D J; Ley, W B; Whittier, W D; Bowen, J M; Thatcher, C D; Pelzer, K D; Moore, J M

1989-07-15

A computer spreadsheet was developed to predict the economic impact of a management decision to use B-mode ultrasonographic ovine pregnancy diagnosis. The spreadsheet design and spreadsheet cell formulas are provided. The program used the partial farm budget technique to calculate net return (NR) or cash flow changes that resulted from the decision to use ultrasonography. Using the program, either simple pregnancy diagnosis or pregnancy diagnosis with the ability to determine singleton or multiple pregnancies may be compared with no flock ultrasonographic pregnancy diagnosis. A wide range of user-selected regional variables are used to calculate the cash flow changes associated with the ultrasonography decisions. A variable may be altered through a range of values to conduct a sensitivity analysis of predicted NR. Example sensitivity analyses are included for flock conception rate, veterinary ultrasound fee, and the price of corn. Variables that influence the number of cull animals and the cost of ultrasonography have the greatest impact on predicted NR. Because the determination of singleton or multiple pregnancies is more time consuming, its economic practicality in comparison with simple pregnancy diagnosis is questionable. The value of feed saved by identifying and separately feeding ewes with singleton pregnancies is not offset by the increased ultrasonography cost.

Control of cancer-related signal transduction networks

NASA Astrophysics Data System (ADS)

Albert, Reka

2013-03-01

Intra-cellular signaling networks are crucial to the maintenance of cellular homeostasis and for cell behavior (growth, survival, apoptosis, movement). Mutations or alterations in the expression of elements of cellular signaling networks can lead to incorrect behavioral decisions that could result in tumor development and/or the promotion of cell migration and metastasis. Thus, mitigation of the cascading effects of such dysregulations is an important control objective. My group at Penn State is collaborating with wet-bench biologists to develop and validate predictive models of various biological systems. Over the years we found that discrete dynamic modeling is very useful in molding qualitative interaction information into a predictive model. We recently demonstrated the effectiveness of network-based targeted manipulations on mitigating the disease T cell large granular lymphocyte (T-LGL) leukemia. The root of this disease is the abnormal survival of T cells which, after successfully fighting an infection, should undergo programmed cell death. We synthesized the relevant network of within-T-cell interactions from the literature, integrated it with qualitative knowledge of the dysregulated (abnormal) states of several network components, and formulated a Boolean dynamic model. The model indicated that the system possesses a steady state corresponding to the normal cell death state and a T-LGL steady state corresponding to the abnormal survival state. For each node, we evaluated the restorative manipulation consisting of maintaining the node in the state that is the opposite of its T-LGL state, e.g. knocking it out if it is overexpressed in the T-LGL state. We found that such control of any of 15 nodes led to the disappearance of the T-LGL steady state, leaving cell death as the only potential outcome from any initial condition. In four additional cases the probability of reaching the T-LGL state decreased dramatically, thus these nodes are also possible control targets. Our collaborators validated two of these predicted control mechanisms experimentally. Our work suggests that external control of a single node can be a fruitful therapeutic strategy.

Procalcitonin and C-reactive protein as early markers of anastomotic leak after laparoscopic colorectal surgery within an enhanced recovery after surgery (ERAS) program.

PubMed

Muñoz, José Luis; Alvarez, María Oliva; Cuquerella, Vicent; Miranda, Elena; Picó, Carlos; Flores, Raquel; Resalt-Pereira, Marta; Moya, Pedro; Pérez, Ana; Arroyo, Antonio

2018-03-08

C-reactive protein (CRP) and procalcitonin (PCT) have been described as good predictors of anastomotic leak after colorectal surgery, obtaining the highest diagnostic accuracy on the 5th postoperative day. However, if an enhanced recovery after surgery (ERAS) program is performed, early predictors are needed in order to ensure a safe and early discharge. The aim of this study was to investigate the efficacy of CRP, PCT, and white blood cell (WBC) count determined on first postoperative days, in predicting septic complications, especially anastomotic leak, after laparoscopic colorectal surgery performed within an ERAS program. We conducted a prospective study including 134 patients who underwent laparoscopic colorectal surgery within an ERAS program between 2015 and 2017. The primary endpoint investigated was anastomotic leak. CRP, PCT, and WBC count were determined in the blood sample extracted on postoperative day 1 (POD 1), POD 2 and POD 3. Anastomotic leak (AL) was detected in 6 patients (4.5%). Serum levels of CRP and PCT, but not WBC, determined on POD 1, POD 2, and POD 3 were significantly higher in patients who had AL in the postoperative course. Using ROC analysis, the best AUC of the CRP and PCT levels was on POD 3 (0.837 and 0.947, respectively). A CRP cutoff level at 163 mg/l yielded 85% sensitivity, 80% specificity, and 99% negative predictive value (NPV). A PCT cutoff level at 2.5 ng/ml achieved 85% sensitivity, 95% specificity, 44% positive predictive value, and 99% NPV. CRP and PCT are relevant markers for detecting postoperative AL after laparoscopic colorectal surgery. Furthermore, they can ensure an early discharge with a low probability of AL when an ERAS program is performed.

Clinical Use of Programmed Cell Death-1 and Its Ligand Expression as Discriminatory and Predictive Markers in Ovarian Cancer.

PubMed

Chatterjee, Jayanta; Dai, Wei; Aziz, Nor Haslinda Abd; Teo, Pei Yun; Wahba, John; Phelps, David L; Maine, Christian J; Whilding, Lynsey M; Dina, Roberto; Trevisan, Giorgia; Flower, Kirsty J; George, Andrew J T; Ghaem-Maghami, Sadaf

2017-07-01

Purpose: We aimed to establish whether programmed cell death-1 (PD-1) and programmed cell death ligand 1 (PD-L1) expression, in ovarian cancer tumor tissue and blood, could be used as biomarkers for discrimination of tumor histology and prognosis of ovarian cancer. Experimental Design: Immune cells were separated from blood, ascites, and tumor tissue obtained from women with suspected ovarian cancer and studied for the differential expression of possible immune biomarkers using flow cytometry. PD-L1 expression on tumor-associated inflammatory cells was assessed by immunohistochemistry and tissue microarray. Plasma soluble PD-L1 was measured using sandwich ELISA. The relationships among immune markers were explored using hierarchical cluster analyses. Results: Biomarkers from the discovery cohort that associated with PD-L1 + cells were found. PD-L1 + CD14 + cells and PD-L1 + CD11c + cells in the monocyte gate showed a distinct expression pattern when comparing benign tumors and epithelial ovarian cancers (EOCs)-confirmed in the validation cohort. Receiver operating characteristic curves showed PD-L1 + and PD-L1 + CD14 + cells in the monocyte gate performed better than the well-established tumor marker CA-125 alone. Plasma soluble PD-L1 was elevated in patients with EOC compared with healthy women and patients with benign ovarian tumors. Low total PD-1 + expression on lymphocytes was associated with improved survival. Conclusions: Differential expression of immunological markers relating to the PD-1/PD-L1 pathway in blood can be used as potential diagnostic and prognostic markers in EOC. These data have implications for the development and trial of anti-PD-1/PD-L1 therapy in ovarian cancer. Clin Cancer Res; 23(13); 3453-60. ©2016 AACR . ©2016 American Association for Cancer Research.

Experimental Assessment of Splicing Variants Using Expression Minigenes and Comparison with In Silico Predictions

PubMed Central

Sharma, Neeraj; Sosnay, Patrick R.; Ramalho, Anabela S.; Douville, Christopher; Franca, Arianna; Gottschalk, Laura B.; Park, Jeenah; Lee, Melissa; Vecchio-Pagan, Briana; Raraigh, Karen S.; Amaral, Margarida D.; Karchin, Rachel; Cutting, Garry R.

2015-01-01

Assessment of the functional consequences of variants near splice sites is a major challenge in the diagnostic laboratory. To address this issue, we created expression minigenes (EMGs) to determine the RNA and protein products generated by splice site variants (n = 10) implicated in cystic fibrosis (CF). Experimental results were compared with the splicing predictions of eight in silico tools. EMGs containing the full-length Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) coding sequence and flanking intron sequences generated wild-type transcript and fully processed protein in Human Embryonic Kidney (HEK293) and CF bronchial epithelial (CFBE41o-) cells. Quantification of variant induced aberrant mRNA isoforms was concordant using fragment analysis and pyrosequencing. The splicing patterns of c.1585−1G>A and c.2657+5G>A were comparable to those reported in primary cells from individuals bearing these variants. Bioinformatics predictions were consistent with experimental results for 9/10 variants (MES), 8/10 variants (NNSplice), and 7/10 variants (SSAT and Sroogle). Programs that estimate the consequences of mis-splicing predicted 11/16 (HSF and ASSEDA) and 10/16 (Fsplice and SplicePort) experimentally observed mRNA isoforms. EMGs provide a robust experimental approach for clinical interpretation of splice site variants and refinement of in silico tools. PMID:25066652

Programmed cell death in periodontitis: recent advances and future perspectives.

PubMed

Song, B; Zhou, T; Yang, W L; Liu, J; Shao, L Q

2017-07-01

Periodontitis is a highly prevalent infectious disease, characterized by destruction of the periodontium, and is the main cause of tooth loss. Periodontitis is initiated by periodontal pathogens, while other risk factors including smoking, stress, and systemic diseases aggravate its progression. Periodontitis affects many people worldwide, but the molecular mechanisms by which pathogens and risk factors destroy the periodontium are unclear. Programmed cell death (PCD), different from necrosis, is an active cell death mediated by a cascade of gene expression events and can be mainly classified into apoptosis, autophagy, necroptosis, and pyroptosis. Although PCD is involved in many inflammatory diseases, its correlation with periodontitis is unclear. After reviewing the relevant published articles, we found that apoptosis has indeed been reported to play a role in periodontitis. However, the role of autophagy in periodontitis needs further verification. Additionally, implication of necroptosis or pyroptosis in periodontitis remains unknown. Therefore, we recommend future studies, which will unravel the pivotal role of PCD in periodontitis, allowing us to prevent, diagnose, and treat the disease, as well as predict its outcomes. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Predictive relevance of PD-L1 expression combined with CD8+ TIL density in stage III non-small cell lung cancer patients receiving concurrent chemoradiotherapy.

PubMed

Tokito, Takaaki; Azuma, Koichi; Kawahara, Akihiko; Ishii, Hidenobu; Yamada, Kazuhiko; Matsuo, Norikazu; Kinoshita, Takashi; Mizukami, Naohisa; Ono, Hirofumi; Kage, Masayoshi; Hoshino, Tomoaki

2016-03-01

Expression of programmed cell death-ligand 1 (PD-L1) is known to be a mechanism whereby cancer can escape immune surveillance, but little is known about factors predictive of efficacy in patients with locally advanced non-small cell lung cancer (NSCLC). We investigated the predictive relevance of PD-L1 expression and CD8+ tumour-infiltrating lymphocytes (TILs) density in patients with locally advanced NSCLC receiving concurrent chemoradiotherapy (CCRT). We retrospectively reviewed 74 consecutive patients with stage III NSCLC who had received CCRT. PD-L1 expression and CD8+ TIL density were evaluated by immunohistochemical analysis. Univariate and multivariate analyses demonstrated that CD8+ TIL density was an independent and significant predictive factor for progression-free survival (PFS) and OS, whereas PD-L1 expression was not correlated with PFS and OS. Sub-analysis revealed that the PD-L1+/CD8 low group had the shortest PFS (8.6 months, p = 0.02) and OS (13.9 months, p = 0.11), and that the PD-L1-/CD8 high group had the longest prognosis (median PFS and OS were not reached) by Kaplan-Meier curves of the four sub-groups. Among stage III NSCLC patients who received CCRT, there was a trend for poor survival in those who expressed PD-L1. Our analysis indicated that a combination of lack of PD-L1 expression and CD8+ TIL density was significantly associated with favourable survival in these patients. It is proposed that PD-L1 expression in combination with CD8+ TIL density could be a useful predictive biomarker in patients with stage III NSCLC. Copyright © 2015 Elsevier Ltd. All rights reserved.

Induced PTF1a expression in pancreatic ductal adenocarcinoma cells activates acinar gene networks, reduces tumorigenic properties, and sensitizes cells to gemcitabine treatment.

PubMed

Jakubison, Brad L; Schweickert, Patrick G; Moser, Sarah E; Yang, Yi; Gao, Hongyu; Scully, Kathleen; Itkin-Ansari, Pamela; Liu, Yunlong; Konieczny, Stephen F

2018-05-02

Pancreatic acinar cells synthesize, package, and secrete digestive enzymes into the duodenum to aid in nutrient absorption and meet metabolic demands. When exposed to cellular stresses and insults, acinar cells undergo a dedifferentiation process termed acinar-ductal metaplasia (ADM). ADM lesions with oncogenic mutations eventually give rise to pancreatic ductal adenocarcinoma (PDAC). In healthy pancreata, the basic helix-loop-helix (bHLH) factors MIST1 and PTF1a coordinate an acinar-specific transcription network that maintains the highly developed differentiation status of the cells, protecting the pancreas from undergoing a transformative process. However, when MIST1 and PTF1a gene expression is silenced, cells are more prone to progress to PDAC. In this study, we tested whether induced MIST1 or PTF1a expression in PDAC cells could (i) re-establish the transcriptional program of differentiated acinar cells and (ii) simultaneously reduce tumor cell properties. As predicted, PTF1a induced gene expression of digestive enzymes and acinar-specific transcription factors, while MIST1 induced gene expression of vesicle trafficking molecules as well as activation of unfolded protein response components, all of which are essential to handle the high protein production load that is characteristic of acinar cells. Importantly, induction of PTF1a in PDAC also influenced cancer-associated properties, leading to a decrease in cell proliferation, cancer stem cell numbers, and repression of key ATP-binding cassette efflux transporters resulting in heightened sensitivity to gemcitabine. Thus, activation of pancreatic bHLH transcription factors rescues the acinar gene program and decreases tumorigenic properties in pancreatic cancer cells, offering unique opportunities to develop novel therapeutic intervention strategies for this deadly disease. © 2018 The Authors. Published by FEBS Press and John Wiley & Sons Ltd.

The capacity of Aspergillus niger to sense and respond to cell wall stress requires at least three transcription factors: RlmA, MsnA and CrzA.

PubMed

Fiedler, Markus Rm; Lorenz, Annett; Nitsche, Benjamin M; van den Hondel, Cees Amjj; Ram, Arthur Fj; Meyer, Vera

2014-01-01

Cell wall integrity, vesicle transport and protein secretion are key factors contributing to the vitality and productivity of filamentous fungal cell factories such as Aspergillus niger . In order to pioneer rational strain improvement programs, fundamental knowledge on the genetic basis of these processes is required. The aim of the present study was thus to unravel survival strategies of A. niger when challenged with compounds interfering directly or indirectly with its cell wall integrity: calcofluor white, caspofungin, aureobasidin A, FK506 and fenpropimorph. Transcriptomics signatures of A. niger and phenotypic analyses of selected null mutant strains were used to predict regulator proteins mediating the survival responses against these stressors. This integrated approach allowed us to reconstruct a model for the cell wall salvage gene network of A. niger that ensures survival of the fungus upon cell surface stress. The model predicts that (i) caspofungin and aureobasidin A induce the cell wall integrity pathway as a main compensatory response via induction of RhoB and RhoD, respectively, eventually activating the mitogen-activated protein kinase kinase MkkA and the transcription factor RlmA. (ii) RlmA is the main transcription factor required for the protection against calcofluor white but it cooperates with MsnA and CrzA to ensure survival of A. niger when challenged with caspofungin and aureobasidin A. (iii) Membrane stress provoked by aureobasidin A via disturbance of sphingolipid synthesis induces cell wall stress, whereas fenpropimorph-induced disturbance of ergosterol synthesis does not. The present work uncovered a sophisticated defence system of A. niger which employs at least three transcription factors - RlmA, MsnA and CrzA - to protect itself against cell wall stress. The transcriptomic data furthermore predicts a fourth transfactor, SrbA, which seems to be specifically important to survive fenpropimorph-induced cell membrane stress. Future studies will disclose how these regulators are interlocked in different signaling pathways to secure survival of A. niger under different cell wall stress conditions.

Mapping the landscape of metabolic goals of a cell

DOE PAGES

Zhao, Qi; Stettner, Arion I.; Reznik, Ed; ...

2016-05-23

Here, genome-scale flux balance models of metabolism provide testable predictions of all metabolic rates in an organism, by assuming that the cell is optimizing a metabolic goal known as the objective function. We introduce an efficient inverse flux balance analysis (invFBA) approach, based on linear programming duality, to characterize the space of possible objective functions compatible with measured fluxes. After testing our algorithm on simulated E. coli data and time-dependent S. oneidensis fluxes inferred from gene expression, we apply our inverse approach to flux measurements in long-term evolved E. coli strains, revealing objective functions that provide insight into metabolic adaptationmore » trajectories.« less

Material electronic quality specifications for polycrystalline silicon wafers

NASA Astrophysics Data System (ADS)

Kalejs, J. P.

1994-06-01

As the use of polycrystalline silicon wafers has expanded in the photovoltaic industry, the need grows for monitoring and qualification techniques for as-grown material that can be used to optimize crystal growth and help predict solar cell performance. Particular needs are for obtaining quantitative measures over full wafer areas of the effects of lifetime limiting defects and of the lifetime upgrading taking place during solar cell processing. We review here the approaches being pursued in programs under way to develop material quality specifications for thin Edge-defined Film-fed Growth (EFG) polycrystalline silicon as-grown wafers. These studies involve collaborations between Mobil Solar, and NREL and university-based laboratories.

Evaluation of Biomarkers Predictive of Benefit from the PD-1 Inhibitor MK-3475 in Patients with Non-Small Cell Lung Cancer and Brain Metastases

DTIC Science & Technology

2017-07-01

Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT Immunotherapies inhibiting the Programmed Death -1 (PD-1) axis can result in dramatic responses and durable...9. Appendices……………………………………………………………14 4 1. INTRODUCTION: Lung cancer is the leading cause of cancer death in the United States, resulting in more...than 160,000 deaths each year. The majority of patients with lung cancer have non-small cell lung cancer (NSCLC) and present with disease at an

Proliferation of PD-1+ CD8 T cells in peripheral blood after PD-1-targeted therapy in lung cancer patients.

PubMed

Kamphorst, Alice O; Pillai, Rathi N; Yang, Shu; Nasti, Tahseen H; Akondy, Rama S; Wieland, Andreas; Sica, Gabriel L; Yu, Ke; Koenig, Lydia; Patel, Nikita T; Behera, Madhusmita; Wu, Hong; McCausland, Megan; Chen, Zhengjia; Zhang, Chao; Khuri, Fadlo R; Owonikoko, Taofeek K; Ahmed, Rafi; Ramalingam, Suresh S

2017-05-09

Exhausted T cells in chronic infections and cancer have sustained expression of the inhibitory receptor programmed cell death 1 (PD-1). Therapies that block the PD-1 pathway have shown promising clinical results in a significant number of advanced-stage cancer patients. Nonetheless, a better understanding of the immunological responses induced by PD-1 blockade in cancer patients is lacking. Identification of predictive biomarkers is a priority in the field, but whether peripheral blood analysis can provide biomarkers to monitor or predict patients' responses to treatment remains to be resolved. In this study, we analyzed longitudinal blood samples from advanced stage non-small cell lung cancer (NSCLC) patients ( n = 29) receiving PD-1-targeted therapies. We detected an increase in Ki-67+ PD-1+ CD8 T cells following therapy in ∼70% of patients, and most responses were induced after the first or second treatment cycle. This T-cell activation was not indiscriminate because we observed only minimal effects on EBV-specific CD8 T cells, suggesting that responding cells may be tumor specific. These proliferating CD8 T cells had an effector-like phenotype (HLA-DR + , CD38 + , Bcl-2 lo ), expressed costimulatory molecules (CD28, CD27, ICOS), and had high levels of PD-1 and coexpression of CTLA-4. We found that 70% of patients with disease progression had either a delayed or absent PD-1+ CD8 T-cell response, whereas 80% of patients with clinical benefit exhibited PD-1+ CD8 T-cell responses within 4 wk of treatment initiation. Our results suggest that peripheral blood analysis may provide valuable insights into NSCLC patients' responses to PD-1-targeted therapies.

Proliferation of PD-1+ CD8 T cells in peripheral blood after PD-1–targeted therapy in lung cancer patients

PubMed Central

Kamphorst, Alice O.; Pillai, Rathi N.; Yang, Shu; Nasti, Tahseen H.; Sica, Gabriel L.; Yu, Ke; Koenig, Lydia; Patel, Nikita T.; Behera, Madhusmita; Wu, Hong; McCausland, Megan; Chen, Zhengjia; Zhang, Chao; Khuri, Fadlo R.; Owonikoko, Taofeek K.; Ahmed, Rafi; Ramalingam, Suresh S.

2017-01-01

Exhausted T cells in chronic infections and cancer have sustained expression of the inhibitory receptor programmed cell death 1 (PD-1). Therapies that block the PD-1 pathway have shown promising clinical results in a significant number of advanced-stage cancer patients. Nonetheless, a better understanding of the immunological responses induced by PD-1 blockade in cancer patients is lacking. Identification of predictive biomarkers is a priority in the field, but whether peripheral blood analysis can provide biomarkers to monitor or predict patients’ responses to treatment remains to be resolved. In this study, we analyzed longitudinal blood samples from advanced stage non–small cell lung cancer (NSCLC) patients (n = 29) receiving PD-1–targeted therapies. We detected an increase in Ki-67+ PD-1+ CD8 T cells following therapy in ∼70% of patients, and most responses were induced after the first or second treatment cycle. This T-cell activation was not indiscriminate because we observed only minimal effects on EBV-specific CD8 T cells, suggesting that responding cells may be tumor specific. These proliferating CD8 T cells had an effector-like phenotype (HLA-DR+, CD38+, Bcl-2lo), expressed costimulatory molecules (CD28, CD27, ICOS), and had high levels of PD-1 and coexpression of CTLA-4. We found that 70% of patients with disease progression had either a delayed or absent PD-1+ CD8 T-cell response, whereas 80% of patients with clinical benefit exhibited PD-1+ CD8 T-cell responses within 4 wk of treatment initiation. Our results suggest that peripheral blood analysis may provide valuable insights into NSCLC patients’ responses to PD-1–targeted therapies. PMID:28446615

Development of an evidence-based approach to external quality assurance for breast cancer hormone receptor immunohistochemistry: comparison of reference values.

PubMed

Makretsov, Nikita; Gilks, C Blake; Alaghehbandan, Reza; Garratt, John; Quenneville, Louise; Mercer, Joel; Palavdzic, Dragana; Torlakovic, Emina E

2011-07-01

External quality assurance and proficiency testing programs for breast cancer predictive biomarkers are based largely on traditional ad hoc design; at present there is no universal consensus on definition of a standard reference value for samples used in external quality assurance programs. To explore reference values for estrogen receptor and progesterone receptor immunohistochemistry in order to develop an evidence-based analytic platform for external quality assurance. There were 31 participating laboratories, 4 of which were previously designated as "expert" laboratories. Each participant tested a tissue microarray slide with 44 breast carcinomas for estrogen receptor and progesterone receptor and submitted it to the Canadian Immunohistochemistry Quality Control Program for analysis. Nuclear staining in 1% or more of the tumor cells was a positive score. Five methods for determining reference values were compared. All reference values showed 100% agreement for estrogen receptor and progesterone receptor scores, when indeterminate results were excluded. Individual laboratory performance (agreement rates, test sensitivity, test specificity, positive predictive value, negative predictive value, and κ value) was very similar for all reference values. Identification of suboptimal performance by all methods was identical for 30 of 31 laboratories. Estrogen receptor assessment of 1 laboratory was discordant: agreement was less than 90% for 3 of 5 reference values and greater than 90% with the use of 2 other reference values. Various reference values provide equivalent laboratory rating. In addition to descriptive feedback, our approach allows calculation of technical test sensitivity and specificity, positive and negative predictive values, agreement rates, and κ values to guide corrective actions.

Digital image analysis improves precision of programmed death ligand 1 (PD-L1) scoring in cutaneous melanoma.

PubMed

Koelzer, Viktor H; Gisler, Aline; Hanhart, Jonathan C; Griss, Johannes; Wagner, Stephan N; Willi, Niels; Cathomas, Gieri; Sachs, Melanie; Kempf, Werner; Thommen, Daniela S; Mertz, Kirsten D

2018-04-16

Immune checkpoint inhibitors have become a successful treatment in metastatic melanoma. The high response rates in a subset of patients suggest that a sensitive companion diagnostic test is required. The predictive value of programmed death ligand 1 (PD-L1) staining in melanoma has been questioned due to inconsistent correlation with clinical outcome. Whether this is due to predictive irrelevance of PD-L1 expression or inaccurate assessment techniques remains unclear. The aim of this study was to develop a standardized digital protocol for the assessment of PD-L1 staining in melanoma and to compare the output data and reproducibility to conventional assessment by expert pathologists. In two cohorts with a total of 69 cutaneous melanomas, a highly significant correlation was found between pathologist-based consensus reading and automated PD-L1 analysis (R=0.97, p<0.0001). Digital scoring captured the full diagnostic spectrum of PD-L1 expression at single cell resolution. An average of 150.472 melanoma cells (median 38.668 cells; range 733-1.078.965) were scored per lesion. Machine learning was used to control for heterogeneity introduced by PD-L1 positive inflammatory cells in the tumour microenvironment. The PD-L1 image analysis protocol showed excellent reproducibility (R=1.0, p<0.0001) when carried out on independent workstations and reduced variability in PD-L1 scoring of human observers. When melanomas were grouped by PD-L1 expression status, we found a clear correlation of PD-L1 positivity with CD8 positive T-cell infiltration, but not with tumour stage, metastasis or driver mutation status. Digital evaluation of PD-L1 reduces scoring variability and may facilitate patient stratification in clinical practice. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Clinical Investigation Program Annual Progress Report.

DTIC Science & Technology

1983-09-30

Antiemetics (A Phase II Study).(O) ............... 049 79/110 Evaluation of Local Anesthetic Skin Testing and Progressive Challenge in Patients with a History ...Associated with Oat Cell Carcinoma. J Assoc Mil Derm 8, 1982. Grimwood, R.E.: The History and Principles of Immunofluorescence. J Assn Mil Derm 9(1...December, 1981. ""’ PRESENTATIONS: 1.) Kindig, N.B.: D CO correction using PaCO back pressure predicted from venous bloo . Sfresented: Carl E

Expression of the p53 target CDIP correlates with sensitivity to TNFα-induced apoptosis in cancer cells.

PubMed

Brown-Endres, Lauren; Schoenfeld, David; Tian, Fang; Kim, Hyung-Gu; Namba, Takushi; Muñoz-Fontela, César; Mandinova, Anna; Aaronson, Stuart A; Lee, Sam W

2012-05-01

TNFα is a pleiotropic cytokine that signals for both survival and apoptotic cell fates. It is still unclear that the dual role of TNFα can be regulated in cancer cells. We previously described an apoptotic pathway involving p53→CDIP→TNFα that was activated in response to genotoxic stress. This pathway operated in the presence of JNK activation; therefore, we postulated that CDIP itself could sensitize cells to a TNFα apoptotic cell fate, survival, or death. We show that CDIP mediates sensitivity to TNFα-induced apoptosis and that cancer cells with endogenous CDIP expression are inherently sensitive to the growth-suppressive effects of TNFα in vitro and in vivo. Thus, CDIP expression correlates with sensitivity of cancer cells with TNFα, and CDIP seems to be a regulator of the p53-mediated death versus survival response of cells to TNFα. This CDIP-mediated sensitivity to TNFα-induced apoptosis favors pro- over antiapoptotic program in cancer cells, and CDIP may serve as a predictive biomarker for such sensitivity. ©2012 AACR

Expression of the p53 target CDIP correlates with sensitivity to TNF-alpha induced apoptosis in cancer cells

PubMed Central

Brown-Endres, Lauren; Schoenfeld, David; Tian, Fang; Kim, Hyung-Gu; Namba, Takushi; Muñoz-Fontela, César; Mandinova, Anna; Aaronson, Stuart A.; Lee, Sam W.

2012-01-01

TNFα is a pleiotropic cytokine that signals for both survival and apoptotic cell fates. It is still unclear that the dual role of TNFα can be regulated in cancer cells. We previously described an apoptotic pathway involving p53→CDIP→TNFα that was activated in response to genotoxic stress. This pathway operated in the presence of JNK activation; therefore, we postulated that CDIP itself could sensitize cells to a TNFα apoptotic cell fate, survival or death. We show that CDIP mediates sensitivity to TNFα-induced apoptosis, and that cancer cells with endogenous CDIP expression are inherently sensitive to the growth suppressive effects of TNFα in vitro and in vivo. Thus, CDIP expression correlates with sensitivity of cancer cells with TNFα, and CDIP appears to be a regulator of the p53-mediated death versus survival response of cells to TNFα. This CDIP-mediated sensitivity to TNFα-induced apoptosis favors pro-over anti-apoptotic program in cancer cells and CDIP may serve as a predictive biomarker for such sensitivity. PMID:22549949

Comprehensive Evaluation of Programmed Death-Ligand 1 Expression in Primary and Metastatic Prostate Cancer.

PubMed

Haffner, Michael C; Guner, Gunes; Taheri, Diana; Netto, George J; Palsgrove, Doreen N; Zheng, Qizhi; Guedes, Liana Benevides; Kim, Kunhwa; Tsai, Harrison; Esopi, David M; Lotan, Tamara L; Sharma, Rajni; Meeker, Alan K; Chinnaiyan, Arul M; Nelson, William G; Yegnasubramanian, Srinivasan; Luo, Jun; Mehra, Rohit; Antonarakis, Emmanuel S; Drake, Charles G; De Marzo, Angelo M

2018-06-01

Antibodies targeting the programmed cell death protein 1/programmed death-ligand 1 (PD-L1) interaction have shown clinical activity in multiple cancer types. PD-L1 protein expression is a clinically validated predictive biomarker of response for such therapies. Prior studies evaluating the expression of PD-L1 in primary prostate cancers have reported highly variable rates of PD-L1 positivity. In addition, limited data exist on PD-L1 expression in metastatic castrate-resistant prostate cancer (mCRPC). Here, we determined PD-L1 protein expression by immunohistochemistry using a validated PD-L1-specific antibody (SP263) in a large and representative cohort of primary prostate cancers and prostate cancer metastases. The study included 539 primary prostate cancers comprising 508 acinar adenocarcinomas, 24 prostatic duct adenocarcinomas, 7 small-cell carcinomas, and a total of 57 cases of mCRPC. PD-L1 positivity was low in primary acinar adenocarcinoma, with only 7.7% of cases showing detectable PD-L1 staining. Increased levels of PD-L1 expression were noted in 42.9% of small-cell carcinomas. In mCRPC, 31.6% of cases showed PD-L1-specific immunoreactivity. In conclusion, in this comprehensive evaluation of PD-L1 expression in prostate cancer, PD-L1 expression is rare in primary prostate cancers, but increased rates of PD-L1 positivity were observed in mCRPC. These results will be important for the future clinical development of programmed cell death protein 1/PD-L1-targeting therapies in prostate cancer. Copyright © 2018 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Rate-equation modelling and ensemble approach to extraction of parameters for viral infection-induced cell apoptosis and necrosis

NASA Astrophysics Data System (ADS)

Domanskyi, Sergii; Schilling, Joshua E.; Gorshkov, Vyacheslav; Libert, Sergiy; Privman, Vladimir

2016-09-01

We develop a theoretical approach that uses physiochemical kinetics modelling to describe cell population dynamics upon progression of viral infection in cell culture, which results in cell apoptosis (programmed cell death) and necrosis (direct cell death). Several model parameters necessary for computer simulation were determined by reviewing and analyzing available published experimental data. By comparing experimental data to computer modelling results, we identify the parameters that are the most sensitive to the measured system properties and allow for the best data fitting. Our model allows extraction of parameters from experimental data and also has predictive power. Using the model we describe interesting time-dependent quantities that were not directly measured in the experiment and identify correlations among the fitted parameter values. Numerical simulation of viral infection progression is done by a rate-equation approach resulting in a system of "stiff" equations, which are solved by using a novel variant of the stochastic ensemble modelling approach. The latter was originally developed for coupled chemical reactions.

Rate-equation modelling and ensemble approach to extraction of parameters for viral infection-induced cell apoptosis and necrosis

NASA Astrophysics Data System (ADS)

Domanskyi, Sergii; Schilling, Joshua; Gorshkov, Vyacheslav; Libert, Sergiy; Privman, Vladimir

We develop a theoretical approach that uses physiochemical kinetics modelling to describe cell population dynamics upon progression of viral infection in cell culture, which results in cell apoptosis (programmed cell death) and necrosis (direct cell death). Several model parameters necessary for computer simulation were determined by reviewing and analyzing available published experimental data. By comparing experimental data to computer modelling results, we identify the parameters that are the most sensitive to the measured system properties and allow for the best data fitting. Our model allows extraction of parameters from experimental data and also has predictive power. Using the model we describe interesting time-dependent quantities that were not directly measured in the experiment and identify correlations among the fitted parameter values. Numerical simulation of viral infection progression is done by a rate-equation approach resulting in a system of ``stiff'' equations, which are solved by using a novel variant of the stochastic ensemble modelling approach. The latter was originally developed for coupled chemical reactions.

Identification of EGFRvIII-derived CTL epitopes restricted by HLA A0201 for dendritic cell based immunotherapy of gliomas.

PubMed

Wu, An-hua; Xiao, Jing; Anker, Lars; Hall, Walter A; Gregerson, Dale S; Cavenee, Webster K; Chen, Wei; Low, Walter C

2006-01-01

The type III variant of the epidermal growth factor receptor (EGFRvIII) mutation is present in 20-25% of patients with glioblastoma multiforme (GBM). EGFRvIII is not expressed in normal tissue and is therefore a suitable candidate antigen for dendritic cell (DC) based immunotherapy of GBM. To identify the antigenic epitope(s) that may serve as targets for EGFRvIII-specific cytotoxic T lymphocytes (CTLs), the peptide sequence of EGFRvIII was screened with two software programs to predict candidate epitopes restricted by the major histocompatibility complex class I subtype HLA-A0201, which is the predominant subtype in most ethnic groups. Three predicted peptides were constructed and loaded to mature human DCs generated from peripheral blood monocytes. Autologous CD8+ T cells were stimulated in vitro with the EGFRvIII peptide-pulsed DCs. One of the three peptides was found to induce EGFRvIII-specific CTLs as demonstrated by IFN-gamma production and cytotoxicity against HLA-A0201+ EGFRvIII transfected U87 glioma cells. These results suggest that vaccination with EGFRvIII peptide-pulsed DCs or adoptive transfer of in vitro elicited EGFRvIII-specific CTLs by EGFRvIII peptide-pulsed DCs are potential approaches to the treatment of glioma patients.

Experimental and numerical studies of natural convection in a Hele-Shaw cell

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

Viney, C.E.; Hickox, C.E.; Montoya, P.C.

1982-12-01

The results of an experimental study are reported in which a Hele-Shaw cell was used to simulate natural convection flow in a homogeneous porous region subjected to a horizonal temperature gradient. Measured velocities and photographs of streamline patterns are compared with numerical predictions produced with the finite element computer program, MARIAH. Results of numerical simulations are also reported for Rayleigh-Benard convection in a bottom-heated, horizontal, prous layer. The numerical results are compared with the experimental Hele-Shaw cell results of Hartline and Lister. The comparison between these experimental and numerical studies provides some support for the qualification of MARIAH as amore » general purpose code for the description of natural convection in porous media at low Rayleigh numbers.« less

GPS-CCD: A Novel Computational Program for the Prediction of Calpain Cleavage Sites

PubMed Central

Gao, Xinjiao; Ma, Qian; Ren, Jian; Xue, Yu

2011-01-01

As one of the most essential post-translational modifications (PTMs) of proteins, proteolysis, especially calpain-mediated cleavage, plays an important role in many biological processes, including cell death/apoptosis, cytoskeletal remodeling, and the cell cycle. Experimental identification of calpain targets with bona fide cleavage sites is fundamental for dissecting the molecular mechanisms and biological roles of calpain cleavage. In contrast to time-consuming and labor-intensive experimental approaches, computational prediction of calpain cleavage sites might more cheaply and readily provide useful information for further experimental investigation. In this work, we constructed a novel software package of GPS-CCD (Calpain Cleavage Detector) for the prediction of calpain cleavage sites, with an accuracy of 89.98%, sensitivity of 60.87% and specificity of 90.07%. With this software, we annotated potential calpain cleavage sites for hundreds of calpain substrates, for which the exact cleavage sites had not been previously determined. In this regard, GPS-CCD 1.0 is considered to be a useful tool for experimentalists. The online service and local packages of GPS-CCD 1.0 were implemented in JAVA and are freely available at: http://ccd.biocuckoo.org/. PMID:21533053

Comprehensive Micromechanics-Analysis Code - Version 4.0

NASA Technical Reports Server (NTRS)

Arnold, S. M.; Bednarcyk, B. A.

2005-01-01

Version 4.0 of the Micromechanics Analysis Code With Generalized Method of Cells (MAC/GMC) has been developed as an improved means of computational simulation of advanced composite materials. The previous version of MAC/GMC was described in "Comprehensive Micromechanics-Analysis Code" (LEW-16870), NASA Tech Briefs, Vol. 24, No. 6 (June 2000), page 38. To recapitulate: MAC/GMC is a computer program that predicts the elastic and inelastic thermomechanical responses of continuous and discontinuous composite materials with arbitrary internal microstructures and reinforcement shapes. The predictive capability of MAC/GMC rests on a model known as the generalized method of cells (GMC) - a continuum-based model of micromechanics that provides closed-form expressions for the macroscopic response of a composite material in terms of the properties, sizes, shapes, and responses of the individual constituents or phases that make up the material. Enhancements in version 4.0 include a capability for modeling thermomechanically and electromagnetically coupled ("smart") materials; a more-accurate (high-fidelity) version of the GMC; a capability to simulate discontinuous plies within a laminate; additional constitutive models of materials; expanded yield-surface-analysis capabilities; and expanded failure-analysis and life-prediction capabilities on both the microscopic and macroscopic scales.

Reliability Analysis of Brittle Material Structures - Including MEMS(?) - With the CARES/Life Program

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.

2002-01-01

Brittle materials are being used, or considered, for a wide variety of high tech applications that operate in harsh environments, including static and rotating turbine parts. thermal protection systems, dental prosthetics, fuel cells, oxygen transport membranes, radomes, and MEMS. Designing components to sustain repeated load without fracturing while using the minimum amount of material requires the use of a probabilistic design methodology. The CARES/Life code provides a general-purpose analysis tool that predicts the probability of failure of a ceramic component as a function of its time in service. For this presentation an interview of the CARES/Life program will be provided. Emphasis will be placed on describing the latest enhancements to the code for reliability analysis with time varying loads and temperatures (fully transient reliability analysis). Also, early efforts in investigating the validity of using Weibull statistics, the basis of the CARES/Life program, to characterize the strength of MEMS structures will be described as as well as the version of CARES/Life for MEMS (CARES/MEMS) being prepared which incorporates single crystal and edge flaw reliability analysis capability. It is hoped this talk will open a dialog for potential collaboration in the area of MEMS testing and life prediction.

Analysis of optimality in natural and perturbed metabolic networks

PubMed Central

Segrè, Daniel; Vitkup, Dennis; Church, George M.

2002-01-01

An important goal of whole-cell computational modeling is to integrate detailed biochemical information with biological intuition to produce testable predictions. Based on the premise that prokaryotes such as Escherichia coli have maximized their growth performance along evolution, flux balance analysis (FBA) predicts metabolic flux distributions at steady state by using linear programming. Corroborating earlier results, we show that recent intracellular flux data for wild-type E. coli JM101 display excellent agreement with FBA predictions. Although the assumption of optimality for a wild-type bacterium is justifiable, the same argument may not be valid for genetically engineered knockouts or other bacterial strains that were not exposed to long-term evolutionary pressure. We address this point by introducing the method of minimization of metabolic adjustment (MOMA), whereby we test the hypothesis that knockout metabolic fluxes undergo a minimal redistribution with respect to the flux configuration of the wild type. MOMA employs quadratic programming to identify a point in flux space, which is closest to the wild-type point, compatibly with the gene deletion constraint. Comparing MOMA and FBA predictions to experimental flux data for E. coli pyruvate kinase mutant PB25, we find that MOMA displays a significantly higher correlation than FBA. Our method is further supported by experimental data for E. coli knockout growth rates. It can therefore be used for predicting the behavior of perturbed metabolic networks, whose growth performance is in general suboptimal. MOMA and its possible future extensions may be useful in understanding the evolutionary optimization of metabolism. PMID:12415116

The genome sequence of the colonial chordate, Botryllus schlosseri

PubMed Central

Voskoboynik, Ayelet; Neff, Norma F; Sahoo, Debashis; Newman, Aaron M; Pushkarev, Dmitry; Koh, Winston; Passarelli, Benedetto; Fan, H Christina; Mantalas, Gary L; Palmeri, Karla J; Ishizuka, Katherine J; Gissi, Carmela; Griggio, Francesca; Ben-Shlomo, Rachel; Corey, Daniel M; Penland, Lolita; White, Richard A; Weissman, Irving L; Quake, Stephen R

2013-01-01

Botryllus schlosseri is a colonial urochordate that follows the chordate plan of development following sexual reproduction, but invokes a stem cell-mediated budding program during subsequent rounds of asexual reproduction. As urochordates are considered to be the closest living invertebrate relatives of vertebrates, they are ideal subjects for whole genome sequence analyses. Using a novel method for high-throughput sequencing of eukaryotic genomes, we sequenced and assembled 580 Mbp of the B. schlosseri genome. The genome assembly is comprised of nearly 14,000 intron-containing predicted genes, and 13,500 intron-less predicted genes, 40% of which could be confidently parceled into 13 (of 16 haploid) chromosomes. A comparison of homologous genes between B. schlosseri and other diverse taxonomic groups revealed genomic events underlying the evolution of vertebrates and lymphoid-mediated immunity. The B. schlosseri genome is a community resource for studying alternative modes of reproduction, natural transplantation reactions, and stem cell-mediated regeneration. DOI: http://dx.doi.org/10.7554/eLife.00569.001 PMID:23840927

Predictive variables for the occurrence of early clinical mastitis in primiparous Holstein cows under field conditions in France.

PubMed Central

Barnouin, J; Chassagne, M

2001-01-01

Holstein heifers from 47 dairy herds in France were enrolled in a field study to determine predictors for clinical mastitis within the first month of lactation. Precalving and calving variables (biochemical, hematological, hygienic, and disease indicators) were collected. Early clinical mastitis (ECM) predictive variables were analyzed by using a multiple logistic regression model (99 cows with ECM vs. 571 without clinical mastitis throughout the first lactation). Two variables were associated with a higher risk of ECM: a) difficult calving and b) medium and high white blood cell (WBC) counts in late gestation. Two prepartum indicators were associated with a lower ECM risk: a) medium and high serum concentrations of immunoglobulin G1 (IgG1) and b) high percentage of eosinophils among white blood cells. Calving difficulty and certain biological blood parameters (IgG1, eosinophils) could represent predictors that would merit further experimental studies, with the aim of designing programs for reducing the risk of clinical mastitis in the first lactation. PMID:11195522

NASA's Space Environments and Effects (SEE) Program: Contamination Engineering Technology Development

NASA Technical Reports Server (NTRS)

Pearson, Steven D.; Clifton, K. Stuart

1999-01-01

ABSTRACT The return of the Long Duration Exposure Facility (LDEF) in 1990 brought a wealth of space exposure data on materials, paints, solar cells, etc. and data on the many space environments. The effects of the harsh space environments can provide damaging or even disabling effects on spacecraft, its materials, and its instruments. In partnership with industry, academia, and other government agencies, National Aeronautics & Space Administration's (NASA's) Space Environments & Effects (SEE) Program defines the space environments and provides technology development to accommodate or mitigate these harmful environments on the spacecraft. This program provides a very comprehensive and focused approach to understanding the space environment, to define the best techniques for both flight and ground-based experimentation, to update the models which predict both the environments and the environmental effects on spacecraft, and finally to ensure that this information is properly maintained and inserted into spacecraft design programs. This paper will describe the current SEE Program and will present SEE contamination engineering technology development and risk mitigation for future spacecraft design.

NASA's Space Environments and Effects (SEE) program: contamination engineering technology development

NASA Astrophysics Data System (ADS)

Pearson, Steven D.; Clifton, K. Stuart

1999-10-01

The return of the Long Duration Exposure Facility (LDEF) in 1990 brought a wealth of space exposure data on materials, paints, solar cells, etc. and data on the many space environments. The effects of the harsh space environments can provide damaging or even disabling effects on spacecraft, its materials, and its instruments. In partnership with industry, academia, and other government agencies, National Aeronautics & Space Administration's (NASA's) Space Environments & Effects (SEE) Program defines the space environments and provides technology development to accommodate or mitigate these harmful environments on the spacecraft. This program provides a very comprehensive and focused approach to understanding the space environment, to define the best techniques for both flight and ground-based experimentation, to update the models which predict both the environments and the environmental effects on spacecraft, and finally to ensure that this information is properly maintained and inserted into spacecraft design programs. This paper will describe the current SEE Program and will present SEE contamination engineering technology development and risk mitigation for future spacecraft design.

Correlation of cell surface proteins of distinct Beauveria bassiana cell types and adaption to varied environment and interaction with the host insect.

PubMed

Yang, Zhi; Jiang, Hongyan; Zhao, Xin; Lu, Zhuoyue; Luo, Zhibing; Li, Xuebing; Zhao, Jing; Zhang, Yongjun

2017-02-01

The insect fungal pathogen Beauveria bassiana produces a number of distinct cell types that include aerial conidia, blastospores and haemolymph-derived cells, termed hyphal bodies, to adapt varied environment niches and within the host insect. These cells display distinct biochemical properties and surface structures, and a highly ordered outermost brush-like structure uniquely present on hyphal bodies, but not on any in vitro cells. Here, we found that the outermost structure on the hyphal bodies mainly consisted of proteins associated to structural wall components in that most of it could be removed by dithiothreitol (DTT) or proteinase K. DTT-treatment also caused delayed germination, decreased tolerance to ultraviolet irradiation and virulence of conidia or blastospores, with decreased adherence and alternated carbohydrate epitopes, suggesting involvement in fungal development, stress responses and virulence. To characterize these cell surface molecules, proteins were released from the living cells using DTT, and identified and quantitated using label-free quantitative mass spectrometry. Thereafter, a series of bioinformatics programs were used to predict cell surface-associated proteins (CSAPs), and 96, 166 and 54 CSAPs were predicted from the identified protein pools of conidia, blastospores and hyphal bodies, respectively, which were involved in utilization of carbohydrate, nitrogen, and lipid, detoxification, pathogen-host interaction, and likely other cellular processes. Thirteen, sixty-nine and six CSAPs were exclusive in conidia, blastospores and hyphal bodies, respectively, which were verified by eGFP-tagged proteins at their N-terminus. Our data provide a crucial cue to understand mechanism of B. bassiana to adapt to varied environment and interaction with insect host. Copyright © 2016 Elsevier Inc. All rights reserved.

Key results of the mini-dome Fresnel lens concentrator array development program under recently completed NASA and SDIO SBIR projects

NASA Technical Reports Server (NTRS)

Oneill, Mark J.; Piszczor, Michael F.; Fraas, Lewis M.

1991-01-01

Since 1986, ENTECH and the NASA Lewis Research Center have been developing a new photovoltaic concentrator system for space power applications. The unique refractive system uses small, dome shaped Fresnel lenses to focus sunlight onto high efficiency photovoltaic concentrator cells which use prismatic cell covers to further increase their performance. Highlights of the five-year development include near Air Mass Zero (AM0) Lear Jet flight testing of mini-dome lenses (90 pct. net optical efficiency achieved); tests verifying sun-pointing error tolerance with negligible power loss; simulator testing of prism-covered GaAs concentrator cells (24 pct. AM0 efficiency); testing of prism-covered Boeing GaAs/GaSb tandem cells (31 pct. AM0 efficiency); and fabrication and outdoor testing of a 36-lens/cell element panel. These test results have confirmed previous analytical predictions which indicate substantial performance improvements for this technology over current array systems. Based on program results to date, it appears than an array power density of 300 watts/sq m and a specific power of 100 watts/kg can be achieved in the near term. All components of the array appear to be readily manufacturable from space-durable materials at reasonable cost. A concise review is presented of the key results leading to the current array, and further development plans for the future are briefly discussed.

Specific expression of PD-L1 in RELA-fusion supratentorial ependymoma: Implications for PD-1-targeted therapy.

PubMed

Witt, Davis A; Donson, Andrew M; Amani, Vladimir; Moreira, Daniel C; Sanford, Bridget; Hoffman, Lindsey M; Handler, Michael H; Levy, Jean M Mulcahy; Jones, Kenneth L; Nellan, Anandani; Foreman, Nicholas K; Griesinger, Andrea M

2018-05-01

A desperate need for novel therapies in pediatric ependymoma (EPN) exists, as chemotherapy remains ineffective and radiotherapy often fails. EPN have significant infiltration of immune cells, which correlates with outcome. Immune checkpoint inhibitors provide an avenue for new treatments. This study characterizes tumor-infiltrating immune cells in EPN and aims at predicting candidates for clinical trials using checkpoint inhibitors targeting PD-L1/PD-1 (programmed death ligand 1/programmed death 1). The transcriptomic profiles of the primary study cohort of EPN and other pediatric brain tumors were interrogated to identify PD-L1 expression levels. Transcriptomic findings were validated using the western blotting, immunohistochemistry and flow cytometry. We evaluated PD-L1 mRNA expression across four intracranial subtypes of EPN in two independent cohorts and found supratentorial RELA fusion (ST-RELA) tumors to have significantly higher levels. There was a correlation between high gene expression and protein PD-L1 levels in ST-RELA tumors by both the western blot and immunohistochemisty. The investigation of EPN cell populations revealed PD-L1 was expressed on both tumor and myeloid cells in ST-RELA. Other subtypes had little PD-L1 in either tumor or myeloid cell compartments. Lastly, we measured PD-1 levels on tumor-infiltrating T cells and found ST-RELA tumors express PD-1 in both CD4 and CD8 T cells. A functional T-cell exhaustion assay found ST-RELA T cells to be exhausted and unable to secrete IFNγ on stimulation. These findings in ST-RELA suggest tumor evasion and immunsuppression due to PD-L1/PD-1-mediated T-cell exhaustion. Trials of checkpoint inhibitors in EPN should be enriched for ST-RELA tumors. © 2018 Wiley Periodicals, Inc.

Non Linear Programming (NLP) Formulation for Quantitative Modeling of Protein Signal Transduction Pathways

PubMed Central

Morris, Melody K.; Saez-Rodriguez, Julio; Lauffenburger, Douglas A.; Alexopoulos, Leonidas G.

2012-01-01

Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms. PMID:23226239

Non Linear Programming (NLP) formulation for quantitative modeling of protein signal transduction pathways.

PubMed

Mitsos, Alexander; Melas, Ioannis N; Morris, Melody K; Saez-Rodriguez, Julio; Lauffenburger, Douglas A; Alexopoulos, Leonidas G

2012-01-01

Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.

Machine learning-based methods for prediction of linear B-cell epitopes.

PubMed

Wang, Hsin-Wei; Pai, Tun-Wen

2014-01-01

B-cell epitope prediction facilitates immunologists in designing peptide-based vaccine, diagnostic test, disease prevention, treatment, and antibody production. In comparison with T-cell epitope prediction, the performance of variable length B-cell epitope prediction is still yet to be satisfied. Fortunately, due to increasingly available verified epitope databases, bioinformaticians could adopt machine learning-based algorithms on all curated data to design an improved prediction tool for biomedical researchers. Here, we have reviewed related epitope prediction papers, especially those for linear B-cell epitope prediction. It should be noticed that a combination of selected propensity scales and statistics of epitope residues with machine learning-based tools formulated a general way for constructing linear B-cell epitope prediction systems. It is also observed from most of the comparison results that the kernel method of support vector machine (SVM) classifier outperformed other machine learning-based approaches. Hence, in this chapter, except reviewing recently published papers, we have introduced the fundamentals of B-cell epitope and SVM techniques. In addition, an example of linear B-cell prediction system based on physicochemical features and amino acid combinations is illustrated in details.

A Physics-Based Engineering Approach to Predict the Cross Section for Advanced SRAMs

NASA Astrophysics Data System (ADS)

Li, Lei; Zhou, Wanting; Liu, Huihua

2012-12-01

This paper presents a physics-based engineering approach to estimate the heavy ion induced upset cross section for 6T SRAM cells from layout and technology parameters. The new approach calculates the effects of radiation with junction photocurrent, which is derived based on device physics. The new and simple approach handles the problem by using simple SPICE simulations. At first, the approach uses a standard SPICE program on a typical PC to predict the SPICE-simulated curve of the collected charge vs. its affected distance from the drain-body junction with the derived junction photocurrent. And then, the SPICE-simulated curve is used to calculate the heavy ion induced upset cross section with a simple model, which considers that the SEU cross section of a SRAM cell is more related to a “radius of influence” around a heavy ion strike than to the physical size of a diffusion node in the layout for advanced SRAMs in nano-scale process technologies. The calculated upset cross section based on this method is in good agreement with the test results for 6T SRAM cells processed using 90 nm process technology.

Accurate prediction of subcellular location of apoptosis proteins combining Chou's PseAAC and PsePSSM based on wavelet denoising.

PubMed

Yu, Bin; Li, Shan; Qiu, Wen-Ying; Chen, Cheng; Chen, Rui-Xin; Wang, Lei; Wang, Ming-Hui; Zhang, Yan

2017-12-08

Apoptosis proteins subcellular localization information are very important for understanding the mechanism of programmed cell death and the development of drugs. The prediction of subcellular localization of an apoptosis protein is still a challenging task because the prediction of apoptosis proteins subcellular localization can help to understand their function and the role of metabolic processes. In this paper, we propose a novel method for protein subcellular localization prediction. Firstly, the features of the protein sequence are extracted by combining Chou's pseudo amino acid composition (PseAAC) and pseudo-position specific scoring matrix (PsePSSM), then the feature information of the extracted is denoised by two-dimensional (2-D) wavelet denoising. Finally, the optimal feature vectors are input to the SVM classifier to predict subcellular location of apoptosis proteins. Quite promising predictions are obtained using the jackknife test on three widely used datasets and compared with other state-of-the-art methods. The results indicate that the method proposed in this paper can remarkably improve the prediction accuracy of apoptosis protein subcellular localization, which will be a supplementary tool for future proteomics research.

Accurate prediction of subcellular location of apoptosis proteins combining Chou’s PseAAC and PsePSSM based on wavelet denoising

PubMed Central

Chen, Cheng; Chen, Rui-Xin; Wang, Lei; Wang, Ming-Hui; Zhang, Yan

2017-01-01

Apoptosis proteins subcellular localization information are very important for understanding the mechanism of programmed cell death and the development of drugs. The prediction of subcellular localization of an apoptosis protein is still a challenging task because the prediction of apoptosis proteins subcellular localization can help to understand their function and the role of metabolic processes. In this paper, we propose a novel method for protein subcellular localization prediction. Firstly, the features of the protein sequence are extracted by combining Chou's pseudo amino acid composition (PseAAC) and pseudo-position specific scoring matrix (PsePSSM), then the feature information of the extracted is denoised by two-dimensional (2-D) wavelet denoising. Finally, the optimal feature vectors are input to the SVM classifier to predict subcellular location of apoptosis proteins. Quite promising predictions are obtained using the jackknife test on three widely used datasets and compared with other state-of-the-art methods. The results indicate that the method proposed in this paper can remarkably improve the prediction accuracy of apoptosis protein subcellular localization, which will be a supplementary tool for future proteomics research. PMID:29296195

Hox-C9 activates the intrinsic pathway of apoptosis and is associated with spontaneous regression in neuroblastoma.

PubMed

Kocak, H; Ackermann, S; Hero, B; Kahlert, Y; Oberthuer, A; Juraeva, D; Roels, F; Theissen, J; Westermann, F; Deubzer, H; Ehemann, V; Brors, B; Odenthal, M; Berthold, F; Fischer, M

2013-04-11

Neuroblastoma is an embryonal malignancy of the sympathetic nervous system. Spontaneous regression and differentiation of neuroblastoma is observed in a subset of patients, and has been suggested to represent delayed activation of physiologic molecular programs of fetal neuroblasts. Homeobox genes constitute an important family of transcription factors, which play a fundamental role in morphogenesis and cell differentiation during embryogenesis. In this study, we demonstrate that expression of the majority of the human HOX class I homeobox genes is significantly associated with clinical covariates in neuroblastoma using microarray expression data of 649 primary tumors. Moreover, a HOX gene expression-based classifier predicted neuroblastoma patient outcome independently of age, stage and MYCN amplification status. Among all HOX genes, HOXC9 expression was most prominently associated with favorable prognostic markers. Most notably, elevated HOXC9 expression was significantly associated with spontaneous regression in infant neuroblastoma. Re-expression of HOXC9 in three neuroblastoma cell lines led to a significant reduction in cell viability, and abrogated tumor growth almost completely in neuroblastoma xenografts. Neuroblastoma growth arrest was related to the induction of programmed cell death, as indicated by an increase in the sub-G1 fraction and translocation of phosphatidylserine to the outer membrane. Programmed cell death was associated with the release of cytochrome c from the mitochondria into the cytosol and activation of the intrinsic cascade of caspases, indicating that HOXC9 re-expression triggers the intrinsic apoptotic pathway. Collectively, our results show a strong prognostic impact of HOX gene expression in neuroblastoma, and may point towards a role of Hox-C9 in neuroblastoma spontaneous regression.

Prognostic impact of programmed cell death 1 ligand 1 expression in human leukocyte antigen class I-positive hepatocellular carcinoma after curative hepatectomy.

PubMed

Umemoto, Yuichiroh; Okano, Shinji; Matsumoto, Yoshihiro; Nakagawara, Hidekazu; Matono, Rumi; Yoshiya, Shohei; Yamashita, Yo-Ichi; Yoshizumi, Tomoharu; Ikegami, Toru; Soejima, Yuji; Harada, Mamoru; Aishima, Shinichi; Oda, Yoshinao; Shirabe, Ken; Maehara, Yoshihiko

2015-01-01

Hepatocellular carcinoma (HCC) is one of the most common solid tumors worldwide. Surgery is potentially curative, but high recurrence rates worsen patient prognosis. The interaction between the proteins programmed cell death 1 (PD-1) and programmed cell death 1 ligand 1 (PD-L1) is an important immune checkpoint. The significance of PD-L1 expression and human leukocyte antigen class I (HLA class I), recognized by CD8 T cells, in the prognosis of patients with HCC remains to be determined. We assessed the levels of PD-L1 and HLA class I expression on HCC samples from 80 patients who had undergone hepatectomy at our institution, and evaluated the correlations between PD-L1 and HLA class I expression and patient prognosis. High HLA class I expression was correlated with significantly better recurrence-free survival (RFS), but not overall survival (OS). Multivariate analysis showed that high HLA class I expression was an independent predictor of improved RFS. Low expression of PD-L1 on HCC tended to predict better OS, but the difference was not statistically significant. PD-L1 expression on HCC correlated with the number of CD163-positive macrophages and HLA class I expression with CD3-positive cell infiltration. Univariable and multivariable analyses showed that combined PD-L1 low/HLA class I high expression on HCCs was prognostic for improved OS and RFS. PD-L1 status may be a good predictor of prognosis in HCC patients with high HLA class I expression. Novel therapies targeting the PD-L1/PD-1 pathway may improve the prognosis of patients with HCC.

Ab-initio conformational epitope structure prediction using genetic algorithm and SVM for vaccine design.

PubMed

Moghram, Basem Ameen; Nabil, Emad; Badr, Amr

2018-01-01

T-cell epitope structure identification is a significant challenging immunoinformatic problem within epitope-based vaccine design. Epitopes or antigenic peptides are a set of amino acids that bind with the Major Histocompatibility Complex (MHC) molecules. The aim of this process is presented by Antigen Presenting Cells to be inspected by T-cells. MHC-molecule-binding epitopes are responsible for triggering the immune response to antigens. The epitope's three-dimensional (3D) molecular structure (i.e., tertiary structure) reflects its proper function. Therefore, the identification of MHC class-II epitopes structure is a significant step towards epitope-based vaccine design and understanding of the immune system. In this paper, we propose a new technique using a Genetic Algorithm for Predicting the Epitope Structure (GAPES), to predict the structure of MHC class-II epitopes based on their sequence. The proposed Elitist-based genetic algorithm for predicting the epitope's tertiary structure is based on Ab-Initio Empirical Conformational Energy Program for Peptides (ECEPP) Force Field Model. The developed secondary structure prediction technique relies on Ramachandran Plot. We used two alignment algorithms: the ROSS alignment and TM-Score alignment. We applied four different alignment approaches to calculate the similarity scores of the dataset under test. We utilized the support vector machine (SVM) classifier as an evaluation of the prediction performance. The prediction accuracy and the Area Under Receiver Operating Characteristic (ROC) Curve (AUC) were calculated as measures of performance. The calculations are performed on twelve similarity-reduced datasets of the Immune Epitope Data Base (IEDB) and a large dataset of peptide-binding affinities to HLA-DRB1*0101. The results showed that GAPES was reliable and very accurate. We achieved an average prediction accuracy of 93.50% and an average AUC of 0.974 in the IEDB dataset. Also, we achieved an accuracy of 95.125% and an AUC of 0.987 on the HLA-DRB1*0101 allele of the Wang benchmark dataset. The results indicate that the proposed prediction technique "GAPES" is a promising technique that will help researchers and scientists to predict the protein structure and it will assist them in the intelligent design of new epitope-based vaccines. Copyright © 2017 Elsevier B.V. All rights reserved.

Autoimmune Granulomatous Inflammation of Lacrimal Glands and Axonal Neuritis Following Treatment With Ipilimumab and Radiation Therapy.

PubMed

Ileana Dumbrava, Ecaterina; Smith, Veronica; Alfattal, Rasha; El-Naggar, Adel K; Penas-Prado, Marta; Tsimberidou, Apostolia M

2018-05-21

Immune checkpoint inhibitors such as anti-CTLA-4 (cytotoxic T-lymphocyte-associated protein 4), anti PD-1 (programmed cell death protein 1) and PD-L1 (programmed cell death protein-ligand 1) monoclonal antibodies are emerging as standard oncology treatments in various tumor types. The indications will expand as immunotherapies are being investigated in various tumors with promising results. Currently, there is inadequate identification of predictive biomarkers of response or toxicity. Unique response patterns include pseudoprogression and delayed response. The use of immune checkpoint inhibitors exhibit an unique toxicity profile, the immune-related adverse events (irAEs). The most notable immune reactions are noted in skin (rash), gastrointestinal track (colitis, hepatitis, pancreatitis), lung (pneumonitis), heart (myocarditis), and endocrine system (thyroiditis, hypophysitis). We present a patient with metastatic adenoid cystic carcinoma of the left submandibular gland with granulomatous inflammation of the lacrimal glands and axonal neuritis of the cervical and paraspinal nerves following treatment with ipilimumab and radiation therapy.

[Predictive value of Hodgkin's lymphoma tumor burden in present].

PubMed

Kulyova, S A; Karitsky, A P

2014-01-01

Today approximately 70% of patients with Hodgkin lymphoma can be cured with the combined-modality therapy. Tumor burden, the importance of which was demonstrated 15 years ago for the first time, is a powerful prognostic factor. Data of literature of representations on predictive value of Hodgkin's lymphoma tumor burden are shown in the article. The difficult immunological relations between tumor cells and reactive ones lead to development of the main symptoms. Nevertheless, the collective sign of tumor burden shows the greatest influence on survival and on probability of resistance, which relative risk can be predicted on this variable and treatment program. Patients with bulky disease need escalated therapy with high-dose chemotherapy. Integration into predictive models of the variable will change an expected contribution of clinical and laboratory parameters in the regression analyses constructed on patients with Hodgkin's lymphoma. Today the role of diagnostic functional methods, in particular a positron emission tomography, for metabolic active measurement is conducted which allows excluding a reactive component.

Predicted structure of MIF/CD74 and RTL1000/CD74 complexes.

PubMed

Meza-Romero, Roberto; Benedek, Gil; Leng, Lin; Bucala, Richard; Vandenbark, Arthur A

2016-04-01

Macrophage migration inhibitory factor (MIF) is a key cytokine in autoimmune and inflammatory diseases that attracts and then retains activated immune cells from the periphery to the tissues. MIF exists as a homotrimer and its effects are mediated through its primary receptor, CD74 (the class II invariant chain that exhibits a highly structured trimerization domain), present on class II expressing cells. Although a number of binding residues have been identified between MIF and CD74 trimers, their spatial orientation has not been established. Using a docking program in silico, we have modeled binding interactions between CD74 and MIF as well as CD74 and a competitive MIF inhibitor, RTL1000, a partial MHC class II construct that is currently in clinical trials for multiple sclerosis. These analyses revealed 3 binding sites on the MIF trimer that each were predicted to bind one CD74 trimer through interactions with two distinct 5 amino acid determinants. Surprisingly, predicted binding of one CD74 trimer to a single RTL1000 antagonist utilized the same two 5 residue determinants, providing strong suggestive evidence in support of the MIF binding regions on CD74. Taken together, our structural modeling predicts a new MIF(CD74)3 dodecamer that may provide the basis for increased MIF potency and the requirement for ~3-fold excess RTL1000 to achieve full antagonism.

Optimization methods and silicon solar cell numerical models

NASA Technical Reports Server (NTRS)

Girardini, K.; Jacobsen, S. E.

1986-01-01

An optimization algorithm for use with numerical silicon solar cell models was developed. By coupling an optimization algorithm with a solar cell model, it is possible to simultaneously vary design variables such as impurity concentrations, front junction depth, back junction depth, and cell thickness to maximize the predicted cell efficiency. An optimization algorithm was developed and interfaced with the Solar Cell Analysis Program in 1 Dimension (SCAP1D). SCAP1D uses finite difference methods to solve the differential equations which, along with several relations from the physics of semiconductors, describe mathematically the performance of a solar cell. A major obstacle is that the numerical methods used in SCAP1D require a significant amount of computer time, and during an optimization the model is called iteratively until the design variables converge to the values associated with the maximum efficiency. This problem was alleviated by designing an optimization code specifically for use with numerically intensive simulations, to reduce the number of times the efficiency has to be calculated to achieve convergence to the optimal solution.

Life and death of female gametes during oogenesis and folliculogenesis.

PubMed

Krysko, Dmitri V; Diez-Fraile, Araceli; Criel, Godelieve; Svistunov, Andrei A; Vandenabeele, Peter; D'Herde, Katharina

2008-09-01

The vertebrate ovary is an extremely dynamic organ in which excessive or defective follicles are rapidly and effectively eliminated early in ontogeny and thereafter continuously throughout reproductive life. More than 99% of follicles disappear, primarily due to apoptosis of granulosa cells, and only a minute fraction of the surviving follicles successfully complete the path to ovulation. The balance between signals for cell death and survival determines the destiny of the follicles. An abnormally high rate of cell death followed by atresia can negatively affect fertility and eventually lead irreversibly to premature ovarian failure. In this review we provide a short overview of the role of programmed cell death in prenatal differentiation of the primordial germ cells and in postnatal folliculogenesis. We also discuss the issue of neo-oogenesis. Next, we highlight molecules involved in regulation of granulosa cell apoptosis. We further discuss the potential use of scores for apoptosis in granulosa cells and characteristics of follicular fluid as prognostic markers for predicting the outcome of assisted reproduction. Potential therapeutic strategies for combating premature ovarian failure are also addressed.

Computer-assisted prediction of HLA-DR binding and experimental analysis for human promiscuous Th1-cell peptides in the 24 kDa secreted lipoprotein (LppX) of Mycobacterium tuberculosis.

PubMed

Al-Attiyah, R; Mustafa, A S

2004-01-01

The secreted 24 kDa lipoprotein (LppX) is an antigen that is specific for Mycobacterium tuberculosis complex and M. leprae. The present study was carried out to identify the promiscuous T helper 1 (Th1)-cell epitopes of the M. tuberculosis LppX (MT24, Rv2945c) antigen by using 15 overlapping synthetic peptides (25 mers overlapping by 10 residues) covering the sequence of the complete protein. The analysis of Rv2945c sequence for binding to 51 alleles of nine serologically defined HLA-DR molecules, by using a virtual matrix-based prediction program (propred), showed that eight of the 15 peptides of Rv2945c were predicted to bind promiscuously to >/=10 alleles from more than or equal to three serologically defined HLA-DR molecules. The Th1-cell reactivity of all the peptides was assessed in antigen-induced proliferation and interferon-gamma (IFN-gamma)-secretion assays with peripheral blood mononuclear cells (PBMCs) from 37 bacille Calmette-Guérin (BCG)-vaccinated healthy subjects. The results showed that 17 of the 37 donors, which represented an HLA-DR-heterogeneous group, responded to one or more peptides of Rv2945c in the Th1-cell assays. Although each peptide stimulated PBMCs from one or more donors in the above assays, the best positive responses (12/17 (71%) responders) were observed with the peptide p14 (aa 196-220). This suggested a highly promiscuous presentation of p14 to Th1 cells. In addition, the sequence of p14 is completely identical among the LppX of M. tuberculosis, M. bovis and M. leprae, which further supports the usefulness of Rv2945c and p14 in the subunit vaccine design against both tuberculosis and leprosy.

Expression pattern of immunosurveillance-related antigen in adult T cell leukaemia/lymphoma.

PubMed

Asano, Naoko; Miyoshi, Hiroaki; Kato, Takeharu; Shimono, Joji; Yoshida, Noriaki; Kurita, Daisuke; Sasaki, Yuya; Kawamoto, Keisuke; Ohshima, Koichi; Seto, Masao

2018-05-01

Adult T cell leukaemia/lymphoma (ATLL) is an aggressive malignancy with a poor prognosis. Human leucocyte antigen (HLA) and β2 microglobulin (β2M) serve as key molecules in tumour immunity, and their expression is reduced frequently in tumour cells. Programmed cell death (PD)-1/PD-ligand1 (PD-L1) interactions play a role in escape of tumour cells from T cell immunity. Therefore, this study aimed to determine the clinicopathological relevance of HLA and β2M expressions in ATLL cells and PD-L1 expression in lymphoma or stromal cells and predict the overall survival of patients with ATLL. We analysed a total of 123 biopsy samples from patients newly diagnosed with ATLL by using immunohistochemical analysis. Of the patients enrolled, 91 (74%) were positive for HLA (in cell membrane, 60 patients), 89 (72%) were positive for β2M (in cell membrane, 54 patients) and 48 (39%) were positive for both HLA and β2M in the cell membrane (HLA m+ β2M m+ ). No significant clinical differences other than prognosis were found between the HLA m+ β2M m+ group and the other groups. Immunophenotypical evaluation revealed significantly higher rates of CD30-positive lymphoma cells (P = 0.003) and PD-L1-positive stromal cells in microenvironments (miPD-L1 high ) (P = 0.011) of the HLA m+ β2M m+ group than in the other groups. The HLA m+ β2M m+ group had a significantly better prognosis that the other groups (P = 0.0096), and patients showing HLA m+ β2M m+ with miPD-L1 high had the most favourable prognosis among all groups. The membranous expression of HLA and β2M is likely to reflect the immune response and would be useful to predict prognosis before starting ATLL therapy. © 2018 John Wiley & Sons Ltd.

Euler Technology Assessment for Preliminary Aircraft Design: Compressibility Predictions by Employing the Cartesian Unstructured Grid SPLITFLOW Code

NASA Technical Reports Server (NTRS)

Finley, Dennis B.; Karman, Steve L., Jr.

1996-01-01

The objective of the second phase of the Euler Technology Assessment program was to evaluate the ability of Euler computational fluid dynamics codes to predict compressible flow effects over a generic fighter wind tunnel model. This portion of the study was conducted by Lockheed Martin Tactical Aircraft Systems, using an in-house Cartesian-grid code called SPLITFLOW. The Cartesian grid technique offers several advantages, including ease of volume grid generation and reduced number of cells compared to other grid schemes. SPLITFLOW also includes grid adaption of the volume grid during the solution to resolve high-gradient regions. The SPLITFLOW code predictions of configuration forces and moments are shown to be adequate for preliminary design, including predictions of sideslip effects and the effects of geometry variations at low and high angles-of-attack. The transonic pressure prediction capabilities of SPLITFLOW are shown to be improved over subsonic comparisons. The time required to generate the results from initial surface data is on the order of several hours, including grid generation, which is compatible with the needs of the design environment.

Computer program for analysis of coupled-cavity traveling wave tubes

NASA Technical Reports Server (NTRS)

Connolly, D. J.; Omalley, T. A.

1977-01-01

A flexible, accurate, large signal computer program was developed for the design of coupled cavity traveling wave tubes. The program is written in FORTRAN IV for an IBM 360/67 time sharing system. The beam is described by a disk model and the slow wave structure by a sequence of cavities, or cells. The computational approach is arranged so that each cavity may have geometrical or electrical parameters different from those of its neighbors. This allows the program user to simulate a tube of almost arbitrary complexity. Input and output couplers, severs, complicated velocity tapers, and other features peculiar to one or a few cavities may be modeled by a correct choice of input data. The beam-wave interaction is handled by an approach in which the radio frequency fields are expanded in solutions to the transverse magnetic wave equation. All significant space harmonics are retained. The program was used to perform a design study of the traveling-wave tube developed for the Communications Technology Satellite. Good agreement was obtained between the predictions of the program and the measured performance of the flight tube.

Micromechanics Analysis Code Post-Processing (MACPOST) User Guide. 1.0

NASA Technical Reports Server (NTRS)

Goldberg, Robert K.; Comiskey, Michele D.; Bednarcyk, Brett A.

1999-01-01

As advanced composite materials have gained wider usage. the need for analytical models and computer codes to predict the thermomechanical deformation response of these materials has increased significantly. Recently, a micromechanics technique called the generalized method of cells (GMC) has been developed, which has the capability to fulfill this -oal. Tc provide a framework for GMC, the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) has been developed. As MAC/GMC has been updated, significant improvements have been made to the post-processing capabilities of the code. Through the MACPOST program, which operates directly within the MSC/PATRAN graphical pre- and post-processing package, a direct link between the analysis capabilities of MAC/GMC and the post-processing capabilities of MSC/PATRAN has been established. MACPOST has simplified the production, printing. and exportation of results for unit cells analyzed by MAC/GMC. MACPOST allows different micro-level quantities to be plotted quickly and easily in contour plots. In addition, meaningful data for X-Y plots can be examined. MACPOST thus serves as an important analysis and visualization tool for the macro- and micro-level data generated by MAC/GMC. This report serves as the user's manual for the MACPOST program.

Cosmetics-triggered percutaneous remote control of transgene expression in mice.

PubMed

Wang, Hui; Ye, Haifeng; Xie, Mingqi; Daoud El-Baba, Marie; Fussenegger, Martin

2015-08-18

Synthetic biology has significantly advanced the rational design of trigger-inducible gene switches that program cellular behavior in a reliable and predictable manner. Capitalizing on genetic componentry, including the repressor PmeR and its cognate operator OPmeR, that has evolved in Pseudomonas syringae pathovar tomato DC3000 to sense and resist plant-defence metabolites of the paraben class, we have designed a set of inducible and repressible mammalian transcription-control devices that could dose-dependently fine-tune transgene expression in mammalian cells and mice in response to paraben derivatives. With an over 60-years track record as licensed preservatives in the cosmetics industry, paraben derivatives have become a commonplace ingredient of most skin-care products including shower gels, cleansing toners and hand creams. As parabens can rapidly reach the bloodstream of mice following topical application, we used this feature to percutaneously program transgene expression of subcutaneous designer cell implants using off-the-shelf commercial paraben-containing skin-care cosmetics. The combination of non-invasive, transdermal and orthogonal trigger-inducible remote control of transgene expression may provide novel opportunities for dynamic interventions in future gene and cell-based therapies. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Cosmetics-triggered percutaneous remote control of transgene expression in mice

PubMed Central

Wang, Hui; Ye, Haifeng; Xie, Mingqi; Daoud El-Baba, Marie; Fussenegger, Martin

2015-01-01

Synthetic biology has significantly advanced the rational design of trigger-inducible gene switches that program cellular behavior in a reliable and predictable manner. Capitalizing on genetic componentry, including the repressor PmeR and its cognate operator OPmeR, that has evolved in Pseudomonas syringae pathovar tomato DC3000 to sense and resist plant-defence metabolites of the paraben class, we have designed a set of inducible and repressible mammalian transcription-control devices that could dose-dependently fine-tune transgene expression in mammalian cells and mice in response to paraben derivatives. With an over 60-years track record as licensed preservatives in the cosmetics industry, paraben derivatives have become a commonplace ingredient of most skin-care products including shower gels, cleansing toners and hand creams. As parabens can rapidly reach the bloodstream of mice following topical application, we used this feature to percutaneously program transgene expression of subcutaneous designer cell implants using off-the-shelf commercial paraben-containing skin-care cosmetics. The combination of non-invasive, transdermal and orthogonal trigger-inducible remote control of transgene expression may provide novel opportunities for dynamic interventions in future gene and cell-based therapies. PMID:25943548

Detrended cross-correlation coefficient: Application to predict apoptosis protein subcellular localization.

PubMed

Liang, Yunyun; Liu, Sanyang; Zhang, Shengli

2016-12-01

Apoptosis, or programed cell death, plays a central role in the development and homeostasis of an organism. Obtaining information on subcellular location of apoptosis proteins is very helpful for understanding the apoptosis mechanism. The prediction of subcellular localization of an apoptosis protein is still a challenging task, and existing methods mainly based on protein primary sequences. In this paper, we introduce a new position-specific scoring matrix (PSSM)-based method by using detrended cross-correlation (DCCA) coefficient of non-overlapping windows. Then a 190-dimensional (190D) feature vector is constructed on two widely used datasets: CL317 and ZD98, and support vector machine is adopted as classifier. To evaluate the proposed method, objective and rigorous jackknife cross-validation tests are performed on the two datasets. The results show that our approach offers a novel and reliable PSSM-based tool for prediction of apoptosis protein subcellular localization. Copyright © 2016 Elsevier Inc. All rights reserved.

Linear programming model can explain respiration of fermentation products.

PubMed

Möller, Philip; Liu, Xiaochen; Schuster, Stefan; Boley, Daniel

2018-01-01

Many differentiated cells rely primarily on mitochondrial oxidative phosphorylation for generating energy in the form of ATP needed for cellular metabolism. In contrast most tumor cells instead rely on aerobic glycolysis leading to lactate to about the same extent as on respiration. Warburg found that cancer cells to support oxidative phosphorylation, tend to ferment glucose or other energy source into lactate even in the presence of sufficient oxygen, which is an inefficient way to generate ATP. This effect also occurs in striated muscle cells, activated lymphocytes and microglia, endothelial cells and several mammalian cell types, a phenomenon termed the "Warburg effect". The effect is paradoxical at first glance because the ATP production rate of aerobic glycolysis is much slower than that of respiration and the energy demands are better to be met by pure oxidative phosphorylation. We tackle this question by building a minimal model including three combined reactions. The new aspect in extension to earlier models is that we take into account the possible uptake and oxidation of the fermentation products. We examine the case where the cell can allocate protein on several enzymes in a varying distribution and model this by a linear programming problem in which the objective is to maximize the ATP production rate under different combinations of constraints on enzymes. Depending on the cost of reactions and limitation of the substrates, this leads to pure respiration, pure fermentation, and a mixture of respiration and fermentation. The model predicts that fermentation products are only oxidized when glucose is scarce or its uptake is severely limited.

Linear programming model can explain respiration of fermentation products

PubMed Central

Möller, Philip; Liu, Xiaochen; Schuster, Stefan

2018-01-01

Many differentiated cells rely primarily on mitochondrial oxidative phosphorylation for generating energy in the form of ATP needed for cellular metabolism. In contrast most tumor cells instead rely on aerobic glycolysis leading to lactate to about the same extent as on respiration. Warburg found that cancer cells to support oxidative phosphorylation, tend to ferment glucose or other energy source into lactate even in the presence of sufficient oxygen, which is an inefficient way to generate ATP. This effect also occurs in striated muscle cells, activated lymphocytes and microglia, endothelial cells and several mammalian cell types, a phenomenon termed the “Warburg effect”. The effect is paradoxical at first glance because the ATP production rate of aerobic glycolysis is much slower than that of respiration and the energy demands are better to be met by pure oxidative phosphorylation. We tackle this question by building a minimal model including three combined reactions. The new aspect in extension to earlier models is that we take into account the possible uptake and oxidation of the fermentation products. We examine the case where the cell can allocate protein on several enzymes in a varying distribution and model this by a linear programming problem in which the objective is to maximize the ATP production rate under different combinations of constraints on enzymes. Depending on the cost of reactions and limitation of the substrates, this leads to pure respiration, pure fermentation, and a mixture of respiration and fermentation. The model predicts that fermentation products are only oxidized when glucose is scarce or its uptake is severely limited. PMID:29415045

The Climate Variability & Predictability (CVP) Program at NOAA - Recent Program Advancements in Understanding AMOC

NASA Astrophysics Data System (ADS)

Lucas, S. E.

2016-12-01

The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International and U.S. Climate Variability and Predictability (CLIVAR/US CLIVAR) Program, and the U.S. Global Change Research Program (USGCRP). The CVP program sits within NOAA's Climate Program Office (http://cpo.noaa.gov/CVP). This poster will present the recently funded CVP projects on improving the understanding Atlantic Meridional Overturning Circulation (AMOC), its impact on decadal predictability, and its relationship with the overall climate system.

The combination of kinetic and flow cytometric semen parameters as a tool to predict fertility in cryopreserved bull semen.

PubMed

Gliozzi, T M; Turri, F; Manes, S; Cassinelli, C; Pizzi, F

2017-11-01

Within recent years, there has been growing interest in the prediction of bull fertility through in vitro assessment of semen quality. A model for fertility prediction based on early evaluation of semen quality parameters, to exclude sires with potentially low fertility from breeding programs, would therefore be useful. The aim of the present study was to identify the most suitable parameters that would provide reliable prediction of fertility. Frozen semen from 18 Italian Holstein-Friesian proven bulls was analyzed using computer-assisted semen analysis (CASA) (motility and kinetic parameters) and flow cytometry (FCM) (viability, acrosomal integrity, mitochondrial function, lipid peroxidation, plasma membrane stability and DNA integrity). Bulls were divided into two groups (low and high fertility) based on the estimated relative conception rate (ERCR). Significant differences were found between fertility groups for total motility, active cells, straightness, linearity, viability and percentage of DNA fragmented sperm. Correlations were observed between ERCR and some kinetic parameters, and membrane instability and some DNA integrity indicators. In order to define a model with high relation between semen quality parameters and ERCR, backward stepwise multiple regression analysis was applied. Thus, we obtained a prediction model that explained almost half (R 2=0.47, P<0.05) of the variation in the conception rate and included nine variables: five kinetic parameters measured by CASA (total motility, active cells, beat cross frequency, curvilinear velocity and amplitude of lateral head displacement) and four parameters related to DNA integrity evaluated by FCM (degree of chromatin structure abnormality Alpha-T, extent of chromatin structure abnormality (Alpha-T standard deviation), percentage of DNA fragmented sperm and percentage of sperm with high green fluorescence representative of immature cells). A significant relationship (R 2=0.84, P<0.05) was observed between real and predicted fertility. Once the accuracy of fertility prediction has been confirmed, the model developed in the present study could be used by artificial insemination centers for bull selection or for elimination of poor fertility ejaculates.

Use of the cytosensor microphysiometer to predict results of a 21-day cumulative irritation patch test in humans.

PubMed

Landin, Wendell E; Mun, Greg C; Nims, Raymond W; Harbell, John W

2007-09-01

The cytosensor microphysiometer (mu phi) was investigated as a rapid, relatively inexpensive test to predict performance of skin cleansing wipes on the human 21-day cumulative irritation patch test (21CIPT). It indirectly measures metabolic rate changes in L929 cells as a function of test article dose, by measuring the acidification rate in a low-buffer medium. The dose producing a 50% reduction in metabolic rate (MRD50), relative to the baseline rate, is used as a measure of toxicity. The acute toxicity of the mu phi assay can be compared to the chronic toxicity of the 21CIPT, which is based largely on the exposure of test agents to the epidermal cells, resulting in damage and penetration of the stratum corneum leading to cell toxicity. Two series of surfactant-based cleansing wipe products were tested via the mu phi assay and 21CIPT. The first series, consisting of 20 products, was used to determine a prediction model. The second series of 38 products consisted of routine product development formulas or marketed products. Comparing the results from both tests, samples with an MRD50 greater than 50 mg/ml provided a 21CIPT score consistent with a product that performs satisfactorily in the market. When the MRD50 was greater than 78 mg/ml, the 21CIPT score was usually zero. The mu phi may be more sensitive than the 21CIPT for ranking minimally irritating materials. The mu phi assay is useful as a screen for predicting the performance of a wet wipes formula on the 21CIPT, and concurrently reduces the use of animals for safety testing in a product development program for cleansing wipes.

Systems analysis of apoptosis protein expression allows the case-specific prediction of cell death responsiveness of melanoma cells

PubMed Central

Passante, E; Würstle, M L; Hellwig, C T; Leverkus, M; Rehm, M

2013-01-01

Many cancer entities and their associated cell line models are highly heterogeneous in their responsiveness to apoptosis inducers and, despite a detailed understanding of the underlying signaling networks, cell death susceptibility currently cannot be predicted reliably from protein expression profiles. Here, we demonstrate that an integration of quantitative apoptosis protein expression data with pathway knowledge can predict the cell death responsiveness of melanoma cell lines. By a total of 612 measurements, we determined the absolute expression (nM) of 17 core apoptosis regulators in a panel of 11 melanoma cell lines, and enriched these data with systems-level information on apoptosis pathway topology. By applying multivariate statistical analysis and multi-dimensional pattern recognition algorithms, the responsiveness of individual cell lines to tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) or dacarbazine (DTIC) could be predicted with very high accuracy (91 and 82% correct predictions), and the most effective treatment option for individual cell lines could be pre-determined in silico. In contrast, cell death responsiveness was poorly predicted when not taking knowledge on protein–protein interactions into account (55 and 36% correct predictions). We also generated mathematical predictions on whether anti-apoptotic Bcl-2 family members or x-linked inhibitor of apoptosis protein (XIAP) can be targeted to enhance TRAIL responsiveness in individual cell lines. Subsequent experiments, making use of pharmacological Bcl-2/Bcl-xL inhibition or siRNA-based XIAP depletion, confirmed the accuracy of these predictions. We therefore demonstrate that cell death responsiveness to TRAIL or DTIC can be predicted reliably in a large number of melanoma cell lines when investigating expression patterns of apoptosis regulators in the context of their network-level interplay. The capacity to predict responsiveness at the cellular level may contribute to personalizing anti-cancer treatments in the future. PMID:23933815

Clinical Implementation of Novel Targeted Therapeutics in Advanced Breast Cancer.

PubMed

Chamberlin, Mary D; Bernhardt, Erica B; Miller, Todd W

2016-11-01

The majority of advanced breast cancers have genetic alterations that are potentially targetable with drugs. Through initiatives such as The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC), data can be mined to provide context for next-generation sequencing (NGS) results in the landscape of advanced breast cancer. Therapies for targets other than estrogen receptor alpha (ER) and HER2, such as cyclin-dependent kinases CDK4 and CDK6, were recently approved based on efficacy in patient subpopulations, but no predictive biomarkers have been found, leaving clinicians to continue a trial-and-error approach with each patient. Next-generation sequencing identifies potentially actionable alterations in genes thought to be drivers in the cancerous process including phosphatidylinositol 3-kinase (PI3K), AKT, fibroblast growth factor receptors (FGFRs), and mutant HER2. Epigenetically directed and immunologic therapies have also shown promise for the treatment of breast cancer via histone deacetylases (HDAC) 1 and 3, programmed T cell death 1 (PD-1), and programmed T cell death ligand 1 (PD-L1). Identifying biomarkers to predict primary resistance in breast cancer will ultimately affect clinical decisions regarding adjuvant therapy in the first-line setting. However, the bulk of medical decision-making is currently made in the secondary resistance setting. Herein, we review the clinical potential of PI3K, AKT, FGFRs, mutant HER2, HDAC1/3, PD-1, and PD-L1 as therapeutic targets in breast cancer, focusing on the rationale for therapeutic development and the status of clinical testing. J. Cell. Biochem. 117: 2454-2463, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

The status of lightweight photovoltaic space array technology based on amorphous silicon solar cells

NASA Technical Reports Server (NTRS)

Hanak, Joseph J.; Kaschmitter, Jim

1991-01-01

Ultralight, flexible photovoltaic (PV) array of amorphous silicon (a-Si) was identified as a potential low cost power source for small satellites. A survey was conducted of the status of the a-Si PV array technology with respect to present and future performance, availability, cost, and risks. For existing, experimental array blankets made of commercial cell material, utilizing metal foil substrates, the Beginning of Life (BOL) performance at Air Mass Zero (AM0) and 35 C includes total power up to 200 W, power per area of 64 W/sq m and power per weight of 258 W/kg. Doubling of power per weight occurs when polyimide substrates are used. Estimated End of Life (EOL) power output after 10 years in a nominal low earth orbit would be 80 pct. of BOL, the degradation being due to largely light induced effects (-10 to -15 pct.) and in part (-5 pct.) to space radiation. Predictions for the year 1995 for flexible PV arrays, made on the basis of published results for rigid a-Si modules, indicate EOL power output per area and per weight of 105 W/sq m and 400 W/kg, respectively, while predictions for the late 1990s based on existing U.S. national PV program goals indicate EOL values of 157 W/sq m and 600 W/kg. Cost estimates by vendors for 200 W ultralight arrays in volume of over 1000 units range from $100/watt to $125/watt. Identified risks include the lack of flexible, space compatible encapsulant, the lack of space qualification effort, recent partial or full acquisitions of US manufacturers of a-Si cells by foreign firms, and the absence of a national commitment for a long range development program toward developing of this important power source for space.

Virulence strategies for infecting phagocytes deduced from the in vivo transcriptional program of Legionella pneumophila.

PubMed

Brüggemann, Holger; Hagman, Arne; Jules, Matthieu; Sismeiro, Odile; Dillies, Marie-Agnès; Gouyette, Catherine; Kunst, Frank; Steinert, Michael; Heuner, Klaus; Coppée, Jean-Yves; Buchrieser, Carmen

2006-08-01

Adaptation to the host environment and exploitation of host cell functions are critical to the success of intracellular pathogens. Here, insight to these virulence mechanisms was obtained for the first time from the transcriptional program of the human pathogen Legionella pneumophila during infection of its natural host, Acanthamoeba castellanii. The biphasic life cycle of L. pneumophila was reflected by a major shift in gene expression from replicative to transmissive phase, concerning nearly half of the genes predicted in the genome. However, three different L. pneumophila strains showed similar in vivo gene expression patterns, indicating that common regulatory mechanisms govern the Legionella life cycle, despite the plasticity of its genome. During the replicative phase, in addition to components of aerobic metabolism and amino acid catabolism, the Entner-Doudoroff pathway, a NADPH producing mechanism used for sugar and/or gluconate assimilation, was expressed, suggesting for the first time that intracellular L. pneumophila may also scavenge host carbohydrates as nutrients and not only proteins. Identification of genes only upregulated in vivo but not in vitro, may explain higher virulence of in vivo grown L. pneumophila. Late in the life cycle, L. pneumophila upregulates genes predicted to promote transmission and manipulation of a new host cell, therewith priming it for the next attack. These including substrates of the Dot/Icm secretion system, other factors associated previously with invasion and virulence, the motility and the type IV pilus machineries, and > 90 proteins not characterized so far. Analysis of a fliA (sigma28) deletion mutant identified genes coregulated with the flagellar regulon, including GGDEF/EAL regulators and factors that promote host cell entry and survival.

Predicting Sensitivity of Breast Tumors to Src-Targeted Therapies through Assessment of Cas/Src/BCAR3 Activity

DTIC Science & Technology

2016-10-01

Amy H. Bouton, Ph.D. Associate Dean of Graduate and Medical ScienXst Programs Professor of Microbiology , Immunology, and Cancer Biology Box...We found that all of the BCAR3 in invasive breast cancer cells is present in a complex with Cas and 1Department of Microbiology , Immunology and Cancer...Harrisonburg, VA, USA. Correspondence: Dr AH Bouton, Department of Microbiology , Immunology and Cancer Biology, University of Virginia School of Medicine, Box

High Speed Research Noise Prediction Code (HSRNOISE) User's and Theoretical Manual

NASA Technical Reports Server (NTRS)

Golub, Robert (Technical Monitor); Rawls, John W., Jr.; Yeager, Jessie C.

2004-01-01

This report describes a computer program, HSRNOISE, that predicts noise levels for a supersonic aircraft powered by mixed flow turbofan engines with rectangular mixer-ejector nozzles. It fully documents the noise prediction algorithms, provides instructions for executing the HSRNOISE code, and provides predicted noise levels for the High Speed Research (HSR) program Technology Concept (TC) aircraft. The component source noise prediction algorithms were developed jointly by Boeing, General Electric Aircraft Engines (GEAE), NASA and Pratt & Whitney during the course of the NASA HSR program. Modern Technologies Corporation developed an alternative mixer ejector jet noise prediction method under contract to GEAE that has also been incorporated into the HSRNOISE prediction code. Algorithms for determining propagation effects and calculating noise metrics were taken from the NASA Aircraft Noise Prediction Program.

Receptor Interactive Protein Kinase 3 Promotes Cisplatin-Triggered Necrosis in Apoptosis-Resistant Esophageal Squamous Cell Carcinoma Cells

PubMed Central

Zhao, Nan; Zhou, Lanping; Liu, Fang; Cichacz, Zbigniew; Zhang, Lin; Zhan, Qimin; Zhao, Xiaohang

2014-01-01

Cisplatin-based chemotherapy is currently the standard treatment for locally advanced esophageal cancer. Cisplatin has been shown to induce both apoptosis and necrosis in cancer cells, but the mechanism by which programmed necrosis is induced remains unknown. In this study, we provide evidence that cisplatin induces necrotic cell death in apoptosis-resistant esophageal cancer cells. This cell death is dependent on RIPK3 and on necrosome formation via autocrine production of TNFα. More importantly, we demonstrate that RIPK3 is necessary for cisplatin-induced killing of esophageal cancer cells because inhibition of RIPK1 activity by necrostatin or knockdown of RIPK3 significantly attenuates necrosis and leads to cisplatin resistance. Moreover, microarray analysis confirmed an anti-apoptotic molecular expression pattern in esophageal cancer cells in response to cisplatin. Taken together, our data indicate that RIPK3 and autocrine production of TNFα contribute to cisplatin sensitivity by initiating necrosis when the apoptotic pathway is suppressed or absent in esophageal cancer cells. These data provide new insight into the molecular mechanisms underlying cisplatin-induced necrosis and suggest that RIPK3 is a potential marker for predicting cisplatin sensitivity in apoptosis-resistant and advanced esophageal cancer. PMID:24959694

Propeller aircraft interior noise model utilization study and validation

NASA Technical Reports Server (NTRS)

Pope, L. D.

1984-01-01

Utilization and validation of a computer program designed for aircraft interior noise prediction is considered. The program, entitled PAIN (an acronym for Propeller Aircraft Interior Noise), permits (in theory) predictions of sound levels inside propeller driven aircraft arising from sidewall transmission. The objective of the work reported was to determine the practicality of making predictions for various airplanes and the extent of the program's capabilities. The ultimate purpose was to discern the quality of predictions for tonal levels inside an aircraft occurring at the propeller blade passage frequency and its harmonics. The effort involved three tasks: (1) program validation through comparisons of predictions with scale-model test results; (2) development of utilization schemes for large (full scale) fuselages; and (3) validation through comparisons of predictions with measurements taken in flight tests on a turboprop aircraft. Findings should enable future users of the program to efficiently undertake and correctly interpret predictions.

A transient plasticity study and low cycle fatigue analysis of the Space Station Freedom photovoltaic solar array blanket

NASA Technical Reports Server (NTRS)

Armand, Sasan C.; Liao, Mei-Hwa; Morris, Ronald W.

1990-01-01

The Space Station Freedom photovoltaic solar array blanket assembly is comprised of several layers of materials having dissimilar elastic, thermal, and mechanical properties. The operating temperature of the solar array, which ranges from -75 to +60 C, along with the material incompatibility of the blanket assembly components combine to cause an elastic-plastic stress in the weld points of the assembly. The weld points are secondary structures in nature, merely serving as electrical junctions for gathering the current. The thermal mechanical loading of the blanket assembly operating in low earth orbit continually changes throughout each 90 min orbit, which raises the possibility of fatigue induced failure. A series of structural analyses were performed in an attempt to predict the fatigue life of the solar cell in the Space Station Freedom photovoltaic array blanket. A nonlinear elastic-plastic MSC/NASTRAN analysis followed by a fatigue calculation indicated a fatigue life of 92,000 to 160,000 cycles for the solar cell weld tabs. Additional analyses predict a permanent buckling phenomenon in the copper interconnect after the first loading cycle. This should reduce or eliminate the pulling of the copper interconnect on the joint where it is welded to the silicon solar cell. It is concluded that the actual fatigue life of the solar array blanket assembly should be significantly higher than the calculated 92,000 cycles, and thus the program requirement of 87,500 cycles (orbits) will be met. Another important conclusion that can be drawn from the overall analysis is that, the strain results obtained from the MSC/NASTRAN nonlinear module are accurate to use for low-cycle fatigue analysis, since both thermal cycle testing of solar cells and analysis have shown higher fatigue life than the minimum program requirement of 87,500 cycles.

Differential Activity of Nivolumab, Pembrolizumab and MPDL3280A according to the Tumor Expression of Programmed Death-Ligand-1 (PD-L1): Sensitivity Analysis of Trials in Melanoma, Lung and Genitourinary Cancers

PubMed Central

Carbognin, Luisa; Pilotto, Sara; Milella, Michele; Vaccaro, Vanja; Brunelli, Matteo; Caliò, Anna; Cuppone, Federica; Sperduti, Isabella; Giannarelli, Diana; Chilosi, Marco; Bronte, Vincenzo; Scarpa, Aldo

2015-01-01

Background The potential predictive role of programmed death-ligand-1 (PD-L1) expression on tumor cells in the context of solid tumor treated with checkpoint inhibitors targeting the PD-1 pathway represents an issue for clinical research. Methods Overall response rate (ORR) was extracted from phase I-III trials investigating nivolumab, pembrolizumab and MPDL3280A for advanced melanoma, non-small cell lung cancer (NSCLC) and genitourinary cancer, and cumulated by adopting a fixed and random-effect model with 95% confidence interval (CI). Interaction test according to tumor PD-L1 was accomplished. A sensitivity analysis according to adopted drug, tumor type, PD-L1 cut-off and treatment line was performed. Results Twenty trials (1,475 patients) were identified. A significant interaction (p<0.0001) according to tumor PD-L1 expression was found in the overall sample with an ORR of 34.1% (95% CI 27.6-41.3%) in the PD-L1 positive and 19.9% (95% CI 15.4-25.3%) in the PD-L1 negative population. ORR was significantly higher in PD-L1 positive in comparison to PD-L1 negative patients for nivolumab and pembrolizumab, with an absolute difference of 16.4% and 19.5%, respectively. A significant difference in activity of 22.8% and 8.7% according to PD-L1 was found for melanoma and NSCLC, respectively, with no significant difference for genitourinary cancer. Conclusion Overall, the three antibodies provide a significant differential effect in terms of activity according to PD-L1 expression on tumor cells. The predictive value of PD-L1 on tumor cells seems to be more robust for anti-PD-1 antibody (nivolumab and pembrolizumab), and in the context of advanced melanoma and NSCLC. PMID:26086854

Designing Tyrosinase siRNAs by Multiple Prediction Algorithms and Evaluation of Their Anti-Melanogenic Effects.

PubMed

Kwon, Ok-Seon; Kwon, Soo-Jung; Kim, Jin Sang; Lee, Gunbong; Maeng, Han-Joo; Lee, Jeongmi; Hwang, Gwi Seo; Cha, Hyuk-Jin; Chun, Kwang-Hoon

2018-05-01

Melanin is a pigment produced from tyrosine in melanocytes. Although melanin has a protective role against UVB radiation-induced damage, it is also associated with the development of melanoma and darker skin tone. Tyrosinase is a key enzyme in melanin synthesis, which regulates the rate-limiting step during conversion of tyrosine into DOPA and dopaquinone. To develop effective RNA interference therapeutics, we designed a melanin siRNA pool by applying multiple prediction programs to reduce human tyrosinase levels. First, 272 siRNAs passed the target accessibility evaluation using the RNAxs program. Then we selected 34 siRNA sequences with ΔG ≥-34.6 kcal/mol, i-Score value ≥65, and siRNA scales score ≤30. siRNAs were designed as 19-bp RNA duplexes with an asymmetric 3' overhang at the 3' end of the antisense strand. We tested if these siRNAs effectively reduced tyrosinase gene expression using qRT-PCR and found that 17 siRNA sequences were more effective than commercially available siRNA. Three siRNAs further tested showed an effective visual color change in MNT-1 human cells without cytotoxic effects, indicating these sequences are anti-melanogenic. Our study revealed that human tyrosinase siRNAs could be efficiently designed using multiple prediction algorithms.

Designing Tyrosinase siRNAs by Multiple Prediction Algorithms and Evaluation of Their Anti-Melanogenic Effects

PubMed Central

Kwon, Ok-Seon; Kwon, Soo-Jung; Kim, Jin Sang; Lee, Gunbong; Maeng, Han-Joo; Lee, Jeongmi; Hwang, Gwi Seo; Cha, Hyuk-Jin; Chun, Kwang-Hoon

2018-01-01

Melanin is a pigment produced from tyrosine in melanocytes. Although melanin has a protective role against UVB radiation-induced damage, it is also associated with the development of melanoma and darker skin tone. Tyrosinase is a key enzyme in melanin synthesis, which regulates the rate-limiting step during conversion of tyrosine into DOPA and dopaquinone. To develop effective RNA interference therapeutics, we designed a melanin siRNA pool by applying multiple prediction programs to reduce human tyrosinase levels. First, 272 siRNAs passed the target accessibility evaluation using the RNAxs program. Then we selected 34 siRNA sequences with ΔG ≥−34.6 kcal/mol, i-Score value ≥65, and siRNA scales score ≤30. siRNAs were designed as 19-bp RNA duplexes with an asymmetric 3′ overhang at the 3′ end of the antisense strand. We tested if these siRNAs effectively reduced tyrosinase gene expression using qRT-PCR and found that 17 siRNA sequences were more effective than commercially available siRNA. Three siRNAs further tested showed an effective visual color change in MNT-1 human cells without cytotoxic effects, indicating these sequences are anti-melanogenic. Our study revealed that human tyrosinase siRNAs could be efficiently designed using multiple prediction algorithms. PMID:29223142

Euler Technology Assessment program for preliminary aircraft design employing SPLITFLOW code with Cartesian unstructured grid method

NASA Technical Reports Server (NTRS)

Finley, Dennis B.

1995-01-01

This report documents results from the Euler Technology Assessment program. The objective was to evaluate the efficacy of Euler computational fluid dynamics (CFD) codes for use in preliminary aircraft design. Both the accuracy of the predictions and the rapidity of calculations were to be assessed. This portion of the study was conducted by Lockheed Fort Worth Company, using a recently developed in-house Cartesian-grid code called SPLITFLOW. The Cartesian grid technique offers several advantages for this study, including ease of volume grid generation and reduced number of cells compared to other grid schemes. SPLITFLOW also includes grid adaptation of the volume grid during the solution convergence to resolve high-gradient flow regions. This proved beneficial in resolving the large vortical structures in the flow for several configurations examined in the present study. The SPLITFLOW code predictions of the configuration forces and moments are shown to be adequate for preliminary design analysis, including predictions of sideslip effects and the effects of geometry variations at low and high angles of attack. The time required to generate the results from initial surface definition is on the order of several hours, including grid generation, which is compatible with the needs of the design environment.

Photodynamic therapy: computer modeling of diffusion and reaction phenomena

NASA Astrophysics Data System (ADS)

Hampton, James A.; Mahama, Patricia A.; Fournier, Ronald L.; Henning, Jeffery P.

1996-04-01

We have developed a transient, one-dimensional mathematical model for the reaction and diffusion phenomena that occurs during photodynamic therapy (PDT). This model is referred to as the PDTmodem program. The model is solved by the Crank-Nicholson finite difference technique and can be used to predict the fates of important molecular species within the intercapillary tissue undergoing PDT. The following factors govern molecular oxygen consumption and singlet oxygen generation within a tumor: (1) photosensitizer concentration; (2) fluence rate; and (3) intercapillary spacing. In an effort to maximize direct tumor cell killing, the model allows educated decisions to be made to insure the uniform generation and exposure of singlet oxygen to tumor cells across the intercapillary space. Based on predictions made by the model, we have determined that the singlet oxygen concentration profile within the intercapillary space is controlled by the product of the drug concentration, and light fluence rate. The model predicts that at high levels of this product, within seconds singlet oxygen generation is limited to a small core of cells immediately surrounding the capillary. The remainder of the tumor tissue in the intercapillary space is anoxic and protected from the generation and toxic effects of singlet oxygen. However, at lower values of this product, the PDT-induced anoxic regions are not observed. An important finding is that an optimal value of this product can be defined that maintains the singlet oxygen concentration throughout the intercapillary space at a near constant level. Direct tumor cell killing is therefore postulated to depend on the singlet oxygen exposure, defined as the product of the uniform singlet oxygen concentration and the time of exposure, and not on the total light dose.

Rate-equation modelling and ensemble approach to extraction of parameters for viral infection-induced cell apoptosis and necrosis

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

Domanskyi, Sergii; Schilling, Joshua E.; Privman, Vladimir, E-mail: privman@clarkson.edu

We develop a theoretical approach that uses physiochemical kinetics modelling to describe cell population dynamics upon progression of viral infection in cell culture, which results in cell apoptosis (programmed cell death) and necrosis (direct cell death). Several model parameters necessary for computer simulation were determined by reviewing and analyzing available published experimental data. By comparing experimental data to computer modelling results, we identify the parameters that are the most sensitive to the measured system properties and allow for the best data fitting. Our model allows extraction of parameters from experimental data and also has predictive power. Using the model wemore » describe interesting time-dependent quantities that were not directly measured in the experiment and identify correlations among the fitted parameter values. Numerical simulation of viral infection progression is done by a rate-equation approach resulting in a system of “stiff” equations, which are solved by using a novel variant of the stochastic ensemble modelling approach. The latter was originally developed for coupled chemical reactions.« less

Stochastic modeling and experimental analysis of phenotypic switching and survival of cancer cells under stress

NASA Astrophysics Data System (ADS)

Zamani Dahaj, Seyed Alireza; Kumar, Niraj; Sundaram, Bala; Celli, Jonathan; Kulkarni, Rahul

The phenotypic heterogeneity of cancer cells is critical to their survival under stress. A significant contribution to heterogeneity of cancer calls derives from the epithelial-mesenchymal transition (EMT), a conserved cellular program that is crucial for embryonic development. Several studies have investigated the role of EMT in growth of early stage tumors into invasive malignancies. Also, EMT has been closely associated with the acquisition of chemoresistance properties in cancer cells. Motivated by these studies, we analyze multi-phenotype stochastic models of the evolution of cancers cell populations under stress. We derive analytical results for time-dependent probability distributions that provide insights into the competing rates underlying phenotypic switching (e.g. during EMT) and the corresponding survival of cancer cells. Experimentally, we evaluate these model-based predictions by imaging human pancreatic cancer cell lines grown with and without cytotoxic agents and measure growth kinetics, survival, morphological changes and (terminal evaluation of) biomarkers with associated epithelial and mesenchymal phenotypes. The results derived suggest approaches for distinguishing between adaptation and selection scenarios for survival in the presence of external stresses.

A stable and reproducible human blood-brain barrier model derived from hematopoietic stem cells.

PubMed

Cecchelli, Romeo; Aday, Sezin; Sevin, Emmanuel; Almeida, Catarina; Culot, Maxime; Dehouck, Lucie; Coisne, Caroline; Engelhardt, Britta; Dehouck, Marie-Pierre; Ferreira, Lino

2014-01-01

The human blood brain barrier (BBB) is a selective barrier formed by human brain endothelial cells (hBECs), which is important to ensure adequate neuronal function and protect the central nervous system (CNS) from disease. The development of human in vitro BBB models is thus of utmost importance for drug discovery programs related to CNS diseases. Here, we describe a method to generate a human BBB model using cord blood-derived hematopoietic stem cells. The cells were initially differentiated into ECs followed by the induction of BBB properties by co-culture with pericytes. The brain-like endothelial cells (BLECs) express tight junctions and transporters typically observed in brain endothelium and maintain expression of most in vivo BBB properties for at least 20 days. The model is very reproducible since it can be generated from stem cells isolated from different donors and in different laboratories, and could be used to predict CNS distribution of compounds in human. Finally, we provide evidence that Wnt/β-catenin signaling pathway mediates in part the BBB inductive properties of pericytes.

SAI (Systems Applications, Incorporated) Urban Airshed Model. Model

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

Schere, K.L.

1985-06-01

This magnetic tape contains the FORTRAN source code, sample input data, and sample output data for the SAI Urban Airshed Model (UAM). The UAM is a 3-dimensional gridded air-quality simulation model that is well suited for predicting the spatial and temporal distribution of photochemical pollutant concentrations in an urban area. The model is based on the equations of conservation of mass for a set of reactive pollutants in a turbulent-flow field. To solve these equations, the UAM uses numerical techniques set in a 3-D finite-difference grid array of cells, each about 1 to 10 kilometers wide and 10 to severalmore » hundred meters deep. As output, the model provides the calculated pollutant concentrations in each cell as a function of time. The chemical species of prime interest included in the UAM simulations are O3, NO, NO/sub 2/ and several organic compounds and classes of compounds. The UAM system contains at its core the Airshed Simulation Program that accesses input data consisting of 10 to 14 files, depending on the program options chosen. Each file is created by a separate data-preparation program. There are 17 programs in the entire UAM system. The services of a qualified dispersion meteorologist, a chemist, and a computer programmer will be necessary to implement and apply the UAM and to interpret the results. Software Description: The program is written in the FORTRAN programming language for implementation on a UNIVAC 1110 computer under the UNIVAC 110 0 operating system level 38R5A. Memory requirement is 80K.« less

A Comprehensive Analysis of Programmed Cell Death Ligand-1 Expression With the Clone SP142 Antibody in Non-Small-Cell Lung Cancer Patients.

PubMed

Takada, Kazuki; Toyokawa, Gouji; Okamoto, Tatsuro; Shimokawa, Mototsugu; Kozuma, Yuka; Matsubara, Taichi; Haratake, Naoki; Akamine, Takaki; Takamori, Shinkichi; Katsura, Masakazu; Shoji, Fumihiro; Oda, Yoshinao; Maehara, Yoshihiko

2017-09-01

Programmed cell death-1 (PD-1) and programmed cell death ligand-1 (PD-L1) have been identified as novel targets for immunotherapy, with anti-PD-1 therapy currently the standard treatment for non-small-cell lung cancer (NSCLC) patients after the failure of first-line chemotherapy treatment. The recent phase II POPLAR and phase III OAK studies showed that atezolizumab, a representative PD-L1 inhibitor, exhibited a survival benefit compared with standard therapy in patients with NSCLC. We examined PD-L1 expression in NSCLC using the clone SP142 of POPLAR and OAK studies. PD-L1 expression in 499 surgically resected NSCLC patients was evaluated using immunohistochemistry using SP142. We set cutoff values as 1%, 5%, 10%, and 50%. The samples from 189 (37.9%), 119 (23.8%), 71 (14.2%), and 39 (7.8%) patients were positive for PD-L1 expression at cutoff values of 1%, 5%, 10%, and 50%, respectively. Fisher exact tests showed that PD-L1 positivity was significantly associated with male sex, smoking, advanced stage, the presence of vascular invasion, squamous cell carcinoma, and wild type epidermal growth factor receptor gene mutation status at all cutoff values. Univariate and multivariate survival analyses revealed that PD-L1-positive patients had a worse prognosis than PD-L1-negative patients only at the 1% cutoff value. Forest plot analyses showed that the 1% cutoff provided a more sensitive value for the prediction of postoperative prognosis. PD-L1 expression varied greatly according to different cutoff values. This study might be a useful reference to understand the results of POPLAR and OAK studies and to select patients likely to benefit from atezolizumab. Copyright © 2017 Elsevier Inc. All rights reserved.

Status of tubular SOFC field unit demonstrations

NASA Astrophysics Data System (ADS)

George, Raymond A.

Siemens Westinghouse is in the final stage of its tubular solid oxide fuel cell (SOFC) development program, and the program emphasis has shifted from basic technology development to cost reduction, scale-up and demonstration of pre-commercial power systems at customer sites. This paper describes our field unit demonstration program including the EDB/ELSAM 100-kW e combined heat and power (CHP) system, the Southern California Edison (SCE) 220-kW e pressurized SOFC/gas turbine (PSOFC/GT) power system, and the planned demonstrations of commercial prototype power systems. In the Spring of 1999, the EDB/ELSAM 100-kW e SOFC-CHP system produced 109 kW e net AC to the utility grid at 46% electrical efficiency and 65 kW t to the hot water district heating system, verifying the analytical predictions. The SCE 220-kW e PSOFC/GT power system will undergo factory startup in the Fall of 1999.

Down-Regulation of MicroRNA-210 Confers Sensitivity towards 1’S-1’-Acetoxychavicol Acetate (ACA) in Cervical Cancer Cells by Targeting SMAD4

PubMed Central

Phuah, Neoh Hun; Azmi, Mohamad Nurul; Awang, Khalijah; Nagoor, Noor Hasima

2017-01-01

MicroRNAs (miRNAs) are short non-coding RNAs that regulate genes posttranscriptionally. Past studies have reported that miR-210 is up-regulated in many cancers including cervical cancer, and plays a pleiotropic role in carcinogenesis. However, its role in regulating response towards anti-cancer agents has not been fully elucidated. We have previously reported that the natural compound 1’S-1’-acetoxychavicol acetate (ACA) is able to induce cytotoxicity in various cancer cells including cervical cancer cells. Hence, this study aims to investigate the mechanistic role of miR-210 in regulating response towards ACA in cervical cancer cells. In the present study, we found that ACA down-regulated miR-210 expression in cervical cancer cells, and suppression of miR-210 expression enhanced sensitivity towards ACA by inhibiting cell proliferation and promoting apoptosis. Western blot analysis showed increased expression of mothers against decapentaplegic homolog 4 (SMAD4), which was predicted as a target of miR-210 by target prediction programs, following treatment with ACA. Luciferase reporter assay confirmed that miR-210 binds to sequences in 3′UTR of SMAD4. Furthermore, decreased in SMAD4 protein expression was observed when miR-210 was overexpressed. Conversely, SMAD4 protein expression increased when miR-210 expression was suppressed. Lastly, we demonstrated that overexpression of SMAD4 augmented the anti-proliferative and apoptosis-inducing effects of ACA. Taken together, our results demonstrated that down-regulation of miR-210 conferred sensitivity towards ACA in cervical cancer cells by targeting SMAD4. These findings suggest that combination of miRNAs and natural compounds could provide new strategies in treating cervical cancer. PMID:28401751

Electrophysiological characteristics and pharmacological sensitivity of two lines of human induced pluripotent stem cell derived cardiomyocytes coming from two different suppliers.

PubMed

Goineau, Sonia; Castagné, Vincent

Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are increasingly used as preclinical tool for predicting drug-induced QT prolongation and arrhythmias. This study was conducted to assess the electrophysiological characteristics and the pharmacological sensitivity of two commercialized hiPSC-CMs. The baseline electrophysiological characteristics measured with a multi-electrode array (MEA) technology differ between Cor.4U and iCell 2 : higher beat rate (+32bpm) and shorter field potential duration (FPD, -201ms) for Cor.4U. The FPD lengthening after cisapride (100nM: +65% versus +18%), quinidine (10μM: +65% versus +31%), sotalol (30μM: +90% versus +47%) or flecainide (3μM: +76% versus +22%) application appeared earlier in iCell 2 as compared to Cor.4U. Arrhythmia occurrence also appeared earlier in iCell 2 as compared to Cor.4U for the 3 substances mentioned above. The FPD shortening recorded after verapamil or nifedipine application was similar in both hiPSC-CMs. In conclusion, Cor.4U and iCell 2 hiPSC-CMs are both sensitive enough to detect drug-induced delayed or shortened repolarization and arrhythmia and can provide useful predictive cardiac electrophysiology data. Arrhythmias occurred at concentrations higher than clinical free maximum plasma concentrations with an overestimation of the risk with cisapride. However, quantitative differences of baseline electrophysiological characteristics or pharmacological sensitivity of both cell types have to be considered with caution during the interpretation of data. The new chemical entities included within a given drug development program should be evaluated in hiPSC-CMs coming from a single supplier. Copyright © 2017 Elsevier Inc. All rights reserved.

Down-Regulation of MicroRNA-210 Confers Sensitivity towards 1'S-1'-Acetoxychavicol Acetate (ACA) in Cervical Cancer Cells by Targeting SMAD4.

PubMed

Phuah, Neoh Hun; Azmi, Mohamad Nurul; Awang, Khalijah; Nagoor, Noor Hasima

2017-04-01

MicroRNAs (miRNAs) are short non-coding RNAs that regulate genes posttranscriptionally. Past studies have reported that miR-210 is up-regulated in many cancers including cervical cancer, and plays a pleiotropic role in carcinogenesis. However, its role in regulating response towards anti-cancer agents has not been fully elucidated. We have previously reported that the natural compound 1'S-1'-acetoxychavicol acetate (ACA) is able to induce cytotoxicity in various cancer cells including cervical cancer cells. Hence, this study aims to investigate the mechanistic role of miR-210 in regulating response towards ACA in cervical cancer cells. In the present study, we found that ACA down-regulated miR-210 expression in cervical cancer cells, and suppression of miR-210 expression enhanced sensitivity towards ACA by inhibiting cell proliferation and promoting apoptosis. Western blot analysis showed increased expression of mothers against decapentaplegic homolog 4 (SMAD4), which was predicted as a target of miR-210 by target prediction programs, following treatment with ACA. Luciferase reporter assay confirmed that miR-210 binds to sequences in 3'UTR of SMAD4. Furthermore, decreased in SMAD4 protein expression was observed when miR-210 was overexpressed. Conversely, SMAD4 protein expression increased when miR-210 expression was suppressed. Lastly, we demonstrated that overexpression of SMAD4 augmented the anti-proliferative and apoptosis-inducing effects of ACA. Taken together, our results demonstrated that down-regulation of miR-210 conferred sensitivity towards ACA in cervical cancer cells by targeting SMAD4. These findings suggest that combination of miRNAs and natural compounds could provide new strategies in treating cervical cancer.

[Development of a predictive program for microbial growth under various temperature conditions].

PubMed

Fujikawa, Hiroshi; Yano, Kazuyoshi; Morozumi, Satoshi; Kimura, Bon; Fujii, Tateo

2006-12-01

A predictive program for microbial growth under various temperature conditions was developed with a mathematical model. The model was a new logistic model recently developed by us. The program predicts Escherichia coli growth in broth, Staphylococcus aureus growth and its enterotoxin production in milk, and Vibrio parahaemolyticus growth in broth at various temperature patterns. The program, which was built with Microsoft Excel (Visual Basic Application), is user-friendly; users can easily input the temperature history of a test food and obtain the prediction instantly on the computer screen. The predicted growth and toxin production can be important indices to determine whether a food is microbiologically safe or not. This program should be a useful tool to confirm the microbial safety of commercial foods.

PD-1 expression and clinical PD-1 blockade in B-cell lymphomas.

PubMed

Xu-Monette, Zijun Y; Zhou, Jianfeng; Young, Ken H

2018-01-04

Programmed cell death protein 1 (PD-1) blockade targeting the PD-1 immune checkpoint has demonstrated unprecedented clinical efficacy in the treatment of advanced cancers including hematologic malignancies. This article reviews the landscape of PD-1/programmed death-ligand 1 (PD-L1) expression and current PD-1 blockade immunotherapy trials in B-cell lymphomas. Most notably, in relapsed/refractory classical Hodgkin lymphoma, which frequently has increased PD-1 + tumor-infiltrating T cells, 9p24.1 genetic alteration, and high PD-L1 expression, anti-PD-1 monotherapy has demonstrated remarkable objective response rates (ORRs) of 65% to 87% and durable disease control in phase 1/2 clinical trials. The median duration of response was 16 months in a phase 2 trial. PD-1 blockade has also shown promise in a phase 1 trial of nivolumab in relapsed/refractory B-cell non-Hodgkin lymphomas, including follicular lymphoma, which often displays abundant PD-1 expression on intratumoral T cells, and diffuse large B-cell lymphoma, which variably expresses PD-1 and PD-L1. In primary mediastinal large B-cell lymphoma, which frequently has 9p24.1 alterations, the ORR was 35% in a phase 2 trial of pembrolizumab. In contrast, the ORR with pembrolizumab was 0% in relapsed chronic lymphocytic leukemia (CLL) and 44% in CLL with Richter transformation in a phase 2 trial. T cells from CLL patients have elevated PD-1 expression; CLL PD-1 + T cells can exhibit a pseudo-exhaustion or a replicative senescence phenotype. PD-1 expression was also found in marginal zone lymphoma but not in mantle cell lymphoma, although currently anti-PD-1 clinical trial data are not available. Mechanisms and predictive biomarkers for PD-1 blockade immunotherapy, treatment-related adverse events, hyperprogression, and combination therapies are discussed in the context of B-cell lymphomas. © 2018 by The American Society of Hematology.

Subseasonal-to-Seasonal Science and Prediction Initiatives of the NOAA MAPP Program

NASA Astrophysics Data System (ADS)

Archambault, H. M.; Barrie, D.; Mariotti, A.

2016-12-01

There is great practical interest in developing predictions beyond the 2-week weather timescale. Scientific communities have historically organized themselves around the weather and climate problems, but the subseasonal-to-seasonal (S2S) timescale range overall is recognized as new territory for which a concerted shared effort is needed. For instance, the climate community, as part of programs like CLIVAR, has historically tackled coupled phenomena and modeling, keys to harnessing predictability on longer timescales. In contrast, the weather community has focused on synoptic dynamics, higher-resolution modeling, and enhanced model initialization, of importance at the shorter timescales and especially for the prediction of extremes. The processes and phenomena specific to timescales between weather and climate require a unified approach to science, modeling, and predictions. Internationally, the WWRP/WCRP S2S Prediction Project is a promising catalyzer for these types of activities. Among the various contributing U.S. research programs, the Modeling, Analysis, Predictions and Projections (MAPP) program, as part of the NOAA Climate Program Office, has launched coordinated research and transition activities that help to meet the agency's goals to fill the weather-to-climate prediction gap and will contribute to advance international goals. This presentation will describe ongoing MAPP program S2S science and prediction initiatives, specifically the MAPP S2S Task Force and the SubX prediction experiment.

Fuel Cell and Hydrogen Technologies Program | Hydrogen and Fuel Cells |

Science.gov Websites

NREL Fuel Cell and Hydrogen Technologies Program Fuel Cell and Hydrogen Technologies Program Through its Fuel Cell and Hydrogen Technologies Program, NREL researches, develops, analyzes, and validates fuel cell and hydrogen production, delivery, and storage technologies for transportation

Metallic Hydrogen

NASA Astrophysics Data System (ADS)

Silvera, Isaac; Zaghoo, Mohamed; Salamat, Ashkan

2015-03-01

Hydrogen is the simplest and most abundant element in the Universe. At high pressure it is predicted to transform to a metal with remarkable properties: room temperature superconductivity, a metastable metal at ambient conditions, and a revolutionary rocket propellant. Both theory and experiment have been challenged for almost 80 years to determine its condensed matter phase diagram, in particular the insulator-metal transition. Hydrogen is predicted to dissociate to a liquid atomic metal at multi-megabar pressures and T =0 K, or at megabar pressures and very high temperatures. Thus, its predicted phase diagram has a broad field of liquid metallic hydrogen at high pressure, with temperatures ranging from thousands of degrees to zero Kelvin. In a bench top experiment using static compression in a diamond anvil cell and pulsed laser heating, we have conducted measurements on dense hydrogen in the region of 1.1-1.7 Mbar and up to 2200 K. We observe a first-order phase transition in the liquid phase, as well as sharp changes in optical transmission and reflectivity when this phase is entered. The optical signature is that of a metal. The mapping of the phase line of this transition is in excellent agreement with recent theoretical predictions for the long-sought plasma phase transition to metallic hydrogen. Research supported by the NSF, Grant DMR-1308641, the DOE Stockpile Stewardship Academic Alliance Program, Grant DE-FG52-10NA29656, and NASA Earth and Space Science Fellowship Program, Award NNX14AP17H.

WE-EF-BRA-02: A Monte Carlo Study of Macroscopic and Microscopic Dose Descriptors for Kilovoltage Cellular Dosimetry

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

Oliver, P; Thomson, R

2015-06-15

Purpose: To investigate how doses to cellular (microscopic) targets depend on cell morphology, and how cellular doses relate to doses to bulk tissues and water for 20 to 370 keV photon sources using Monte Carlo (MC) simulations. Methods: Simulation geometries involve cell clusters, single cells, and single nuclear cavities embedded in various healthy and cancerous bulk tissue phantoms. A variety of nucleus and cytoplasm elemental compositions are investigated. Cell and nucleus radii range from 5 to 10 microns and 2 to 9 microns, respectively. Doses to water and bulk tissue cavities are compared to nucleus and cytoplasm doses. Results: Variationsmore » in cell dose with simulation geometry are most pronounced for lower energy sources. Nuclear doses are sensitive to the surrounding geometry: the nuclear dose in a multicell model differs from the dose to a cavity of nuclear medium in an otherwise homogeneous bulk tissue phantom by more than 7% at 20 keV. Nuclear doses vary with cell size by up to 20% at 20 keV, with 10% differences persisting up to 90 keV. Bulk tissue and water cavity doses differ from cellular doses by up to 16%. MC results are compared to cavity theory predictions; large and small cavity theories qualitatively predict nuclear doses for energies below and above 50 keV, respectively. Burlin’s (1969) intermediate cavity theory best predicts MC results with an average discrepancy of 4%. Conclusion: Cellular doses vary as a function of source energy, subcellular compartment size, elemental composition, and tissue morphology. Neither water nor bulk tissue is an appropriate surrogate for subcellular targets in radiation dosimetry. The influence of microscopic inhomogeneities in the surrounding environment on the nuclear dose and the importance of the nucleus as a target for radiation-induced cell death emphasizes the potential importance of cellular dosimetry for understanding radiation effects. Funded by the Natural Sciences and Engineering Research Council of Canada (NSERC), the Canada Research Chairs Program (CRC), and the Ontario Ministry of Training, Colleges and Universities.« less

Structural imprints in vivo decode RNA regulatory mechanisms

PubMed Central

Spitale, Robert C.; Flynn, Ryan A.; Zhang, Qiangfeng Cliff; Crisalli, Pete; Lee, Byron; Jung, Jong-Wha; Kuchelmeister, Hannes Y.; Batista, Pedro J.; Torre, Eduardo A.; Kool, Eric T.; Chang, Howard Y.

2015-01-01

Visualizing the physical basis for molecular behavior inside living cells is a grand challenge in biology. RNAs are central to biological regulation, and RNA’s ability to adopt specific structures intimately controls every step of the gene expression program1. However, our understanding of physiological RNA structures is limited; current in vivo RNA structure profiles view only two of four nucleotides that make up RNA2,3. Here we present a novel biochemical approach, In Vivo Click SHAPE (icSHAPE), that enables the first global view of RNA secondary structures of all four bases in living cells. icSHAPE of mouse embryonic stem cell transcriptome versus purified RNA folded in vitro shows that the structural dynamics of RNA in the cellular environment distinguishes different classes of RNAs and regulatory elements. Structural signatures at translational start sites and ribosome pause sites are conserved from in vitro, suggesting that these RNA elements are programmed by sequence. In contrast, focal structural rearrangements in vivo reveal precise interfaces of RNA with RNA binding proteins or RNA modification sites that are consistent with atomic-resolution structural data. Such dynamic structural footprints enable accurate prediction of RNA-protein interactions and N6-methyladenosine (m6A) modification genome-wide. These results open the door for structural genomics of RNA in living cells and reveal key physiological structures controlling gene expression. PMID:25799993

Structural imprints in vivo decode RNA regulatory mechanisms.

PubMed

Spitale, Robert C; Flynn, Ryan A; Zhang, Qiangfeng Cliff; Crisalli, Pete; Lee, Byron; Jung, Jong-Wha; Kuchelmeister, Hannes Y; Batista, Pedro J; Torre, Eduardo A; Kool, Eric T; Chang, Howard Y

2015-03-26

Visualizing the physical basis for molecular behaviour inside living cells is a great challenge for biology. RNAs are central to biological regulation, and the ability of RNA to adopt specific structures intimately controls every step of the gene expression program. However, our understanding of physiological RNA structures is limited; current in vivo RNA structure profiles include only two of the four nucleotides that make up RNA. Here we present a novel biochemical approach, in vivo click selective 2'-hydroxyl acylation and profiling experiment (icSHAPE), which enables the first global view, to our knowledge, of RNA secondary structures in living cells for all four bases. icSHAPE of the mouse embryonic stem cell transcriptome versus purified RNA folded in vitro shows that the structural dynamics of RNA in the cellular environment distinguish different classes of RNAs and regulatory elements. Structural signatures at translational start sites and ribosome pause sites are conserved from in vitro conditions, suggesting that these RNA elements are programmed by sequence. In contrast, focal structural rearrangements in vivo reveal precise interfaces of RNA with RNA-binding proteins or RNA-modification sites that are consistent with atomic-resolution structural data. Such dynamic structural footprints enable accurate prediction of RNA-protein interactions and N(6)-methyladenosine (m(6)A) modification genome wide. These results open the door for structural genomics of RNA in living cells and reveal key physiological structures controlling gene expression.

NASA Tech Briefs, October 2005

NASA Technical Reports Server (NTRS)

2005-01-01

Topics covered include: Insect-Inspired Optical-Flow Navigation Sensors; Chemical Sensors Based on Optical Ring Resonators; A Broad-Band Phase-Contrast Wave-Front Sensor; Progress in Insect-Inspired Optical Navigation Sensors; Portable Airborne Laser System Measures Forest-Canopy Height; Deployable Wide-Aperture Array Antennas; Faster Evolution of More Multifunctional Logic Circuits; Video-Camera-Based Position-Measuring System; N-Type delta Doping of High-Purity Silicon Imaging Arrays; Avionics System Architecture Tool; Updated Chemical Kinetics and Sensitivity Analysis Code; Predicting Flutter and Forced Response in Turbomachinery; Upgrades of Two Computer Codes for Analysis of Turbomachinery; Program Facilitates CMMI Appraisals; Grid Visualization Tool; Program Computes Sound Pressures at Rocket Launches; Solar-System Ephemeris Toolbox; Data-Acquisition Software for PSP/TSP Wind-Tunnel Cameras; Corrosion-Prevention Capabilities of a Water-Borne, Silicone-Based, Primerless Coating; Sol-Gel Process for Making Pt-Ru Fuel-Cell Catalysts; Making Activated Carbon for Storing Gas; System Regulates the Water Contents of Fuel-Cell Streams; Five-Axis, Three-Magnetic-Bearing Dynamic Spin Rig; Modifications of Fabrication of Vibratory Microgyroscopes; Chamber for Growing and Observing Fungi; Electroporation System for Sterilizing Water; Thermoelectric Air/Soil Energy-Harvesting Device; Flexible Metal-Fabric Radiators; Actuated Hybrid Mirror Telescope; Optical Design of an Optical Communications Terminal; Algorithm for Identifying Erroneous Rain-Gauge Readings; Condition Assessment and End-of-Life Prediction System for Electric Machines and Their Loads; Lightweight Thermal Insulation for a Liquid-Oxygen Tank; Stellar Gyroscope for Determining Attitude of a Spacecraft; and Lifting Mechanism for the Mars Explorer Rover.

EffectorP: predicting fungal effector proteins from secretomes using machine learning.

PubMed

Sperschneider, Jana; Gardiner, Donald M; Dodds, Peter N; Tini, Francesco; Covarelli, Lorenzo; Singh, Karam B; Manners, John M; Taylor, Jennifer M

2016-04-01

Eukaryotic filamentous plant pathogens secrete effector proteins that modulate the host cell to facilitate infection. Computational effector candidate identification and subsequent functional characterization delivers valuable insights into plant-pathogen interactions. However, effector prediction in fungi has been challenging due to a lack of unifying sequence features such as conserved N-terminal sequence motifs. Fungal effectors are commonly predicted from secretomes based on criteria such as small size and cysteine-rich, which suffers from poor accuracy. We present EffectorP which pioneers the application of machine learning to fungal effector prediction. EffectorP improves fungal effector prediction from secretomes based on a robust signal of sequence-derived properties, achieving sensitivity and specificity of over 80%. Features that discriminate fungal effectors from secreted noneffectors are predominantly sequence length, molecular weight and protein net charge, as well as cysteine, serine and tryptophan content. We demonstrate that EffectorP is powerful when combined with in planta expression data for predicting high-priority effector candidates. EffectorP is the first prediction program for fungal effectors based on machine learning. Our findings will facilitate functional fungal effector studies and improve our understanding of effectors in plant-pathogen interactions. EffectorP is available at http://effectorp.csiro.au. © 2015 CSIRO New Phytologist © 2015 New Phytologist Trust.

Impact of early treatment programs on HIV epidemics: An immunity-based mathematical model.

PubMed

Rahman, S M Ashrafur; Vaidya, Naveen K; Zou, Xingfu

2016-10-01

While studies on pre-exposure prophylaxis (PrEP) and post-exposure prophylaxis (PEP) have demonstrated substantial advantages in controlling HIV transmission, the overall benefits of the programs with early initiation of antiretroviral therapy (ART) have not been fully understood and are still on debate. Here, we develop an immunity-based (CD4+ T cell count based) mathematical model to study the impacts of early treatment programs on HIV epidemics and the overall community-level immunity. The model is parametrized using the HIV prevalence data from South Africa and fully analyzed for stability of equilibria and infection persistence criteria. Using our model, we evaluate the effects of early treatment on the new infection transmission, disease death, basic reproduction number, HIV prevalence, and the community-level immunity. Our model predicts that the programs with early treatments significantly reduce the new infection transmission and increase the community-level immunity, but the treatments alone may not be enough to eliminate HIV epidemics. These findings, including the community-level immunity, might provide helpful information for proper implementation of HIV treatment programs. Copyright © 2016 Elsevier Inc. All rights reserved.

NASA's Space Environments and Effects (SEE) Program

NASA Technical Reports Server (NTRS)

Minor, Jody

2001-01-01

The return of the Long Duration Exposure Facility (LDEF) in 1990 brought a wealth of space exposure data on materials, paints, solar cells, adhesives and other data on the many space environments. The effects of the harsh space environments can provide damaging or even disabling effects on a spacecraft, its sub-systems, materials and instruments. In partnership with industry, academia, and other US and international government agencies, the National Aeronautics & Space Administration's (NASA's) Space Environments & Effects (SEE) Program defines the space environments and provides technology development to accommodate or mitigate these harmful environments on the spacecraft. This program (agency-wide in scope but managed at the Marshall Space Flight Center) provides a very comprehensive and focused approach to understanding the space environment. It does this by defining the best techniques for both flight- and groundbased experimentation, updating models which predict both the environments and the environmental effects on spacecraft and ensuring that this information is properly maintained and inserted into spacecraft design programs. This paper will describe the current SEE Program and discuss several current technology development activities associated with the spacecraft charging phenomenon.

Transcriptome characterization of immune suppression from battlefield-like stress

PubMed Central

Muhie, S; Hammamieh, R; Cummings, C; Yang, D; Jett, M

2013-01-01

Transcriptome alterations of leukocytes from soldiers who underwent 8 weeks of Army Ranger training (RASP, Ranger Assessment and Selection Program) were analyzed to evaluate impacts of battlefield-like stress on the immune response. About 1400 transcripts were differentially expressed between pre- and post-RASP leukocytes. Upon functional analysis, immune response was the most enriched biological process, and most of the transcripts associated with the immune response were downregulated. Microbial pattern recognition, chemotaxis, antigen presentation and T-cell activation were among the most downregulated immune processes. Transcription factors predicted to be stress-inhibited (IRF7, RELA, NFκB1, CREB1, IRF1 and HMGB) regulated genes involved in inflammation, maturation of dendritic cells and glucocorticoid receptor signaling. Many altered transcripts were predicted to be targets of stress-regulated microRNAs. Post-RASP leukocytes exposed ex vivo to Staphylococcal enterotoxin B showed a markedly impaired immune response to this superantigen compared with pre-RASP leukocytes, consistent with the suppression of the immune response revealed by transcriptome analyses. Our results suggest that suppression of antigen presentation and lymphocyte activation pathways, in the setting of normal blood cell counts, most likely contribute to the poor vaccine response, impaired wound healing and infection susceptibility associated with chronic intense stress. PMID:23096155

PDCD1 (PD-1) promoter methylation predicts outcome in head and neck squamous cell carcinoma patients.

PubMed

Goltz, Diane; Gevensleben, Heidrun; Dietrich, Joern; Schroeck, Friederike; de Vos, Luka; Droege, Freya; Kristiansen, Glen; Schroeck, Andreas; Landsberg, Jennifer; Bootz, Friedrich; Dietrich, Dimo

2017-06-20

Biomarkers that facilitate the prediction of disease recurrence in head and neck squamous cell carcinoma (HNSCC) may enable physicians to personalize treatment. In the current study, DNA promoter methylation of programmed cell death 1 (PDCD1, PD-1) was evaluated as a prognostic biomarker in HNSCC patients. High PDCD1 methylation (mPDCD1) was associated with a significantly shorter overall survival after surgical resection in both the discovery (HR = 2.24 [95%CI: 1.08-4.64], p = 0.029) and the validation cohort (HR = 1.54 [95%CI: 1.08-2.21], p = 0.017). In multivariate Cox proportional hazards analysis, PDCD1 methylation remained a significant prognostic factor for HNSCC (HR = 2.14 [95%CI: 1.19-3.84], p = 0.011). Further, mPDCD1 was strongly associated with the human papilloma virus (HPV) status. mPDCD1 was assessed retrospectively in a discovery cohort of 120 HNSCC patients treated at the University Hospital of Bonn and a validation cohort of 527 HNSCC cases analyzed by The Cancer Genome Atlas Research Network. PDCD1 methylation might aid the identification of HNSCC patients potentially benefitting from a radical or alternative treatment, particularly in the context of immunotherapies targeting PD-1/PD-L1.

Model comparison for Escherichia coli growth in pouched food.

PubMed

Fujikawa, Hiroshi; Yano, Kazuyoshi; Morozumi, Satoshi

2006-06-01

We recently studied the growth characteristics of Escherichia coli cells in pouched mashed potatoes (Fujikawa et al., J. Food Hyg. Soc. Japan, 47, 95-98 (2006)). Using those experimental data, in the present study, we compared a logistic model newly developed by us with the modified Gompertz and the Baranyi models, which are used as growth models worldwide. Bacterial growth curves at constant temperatures in the range of 12 to 34 degrees C were successfully described with the new logistic model, as well as with the other models. The Baranyi gave the least error in cell number and our model gave the least error in the rate constant and the lag period. For dynamic temperature, our model successfully predicted the bacterial growth, whereas the Baranyi model considerably overestimated it. Also, there was a discrepancy between the growth curves described with the differential equations of the Baranyi model and those obtained with DMfit, a software program for Baranyi model fitting. These results indicate that the new logistic model can be used to predict bacterial growth in pouched food.

Physiological significance of polyploidization in mammalian cells.

PubMed

Pandit, Shusil K; Westendorp, Bart; de Bruin, Alain

2013-11-01

Programmed polyploidization occurs in all mammalian species during development and aging in selected tissues, but the biological properties of polyploid cells remain obscure. Spontaneous polyploidization arises during stress and has been observed in a variety of pathological conditions, such as cancer and degenerative diseases. A major challenge in the field is to test the predicted functions of polyploidization in vivo. However, recent genetic mouse models with diminished polyploidization phenotypes represent novel, powerful tools to unravel the biological function of polyploidization. Contrary to a longstanding hypothesis, polyploidization appears to not be required for differentiation and has no obvious impact on proliferation. Instead, polyploidization leads to increased cell size and genetic diversity, which could promote better adaptation to chronic injury or stress. We discuss here the consequences of reducing polyploidization in mice and review which stress responses and molecular signals trigger polyploidization during development and disease. Copyright © 2013 Elsevier Ltd. All rights reserved.

Deciphering DNA replication dynamics in eukaryotic cell populations in relation with their averaged chromatin conformations

NASA Astrophysics Data System (ADS)

Goldar, A.; Arneodo, A.; Audit, B.; Argoul, F.; Rappailles, A.; Guilbaud, G.; Petryk, N.; Kahli, M.; Hyrien, O.

2016-03-01

We propose a non-local model of DNA replication that takes into account the observed uncertainty on the position and time of replication initiation in eukaryote cell populations. By picturing replication initiation as a two-state system and considering all possible transition configurations, and by taking into account the chromatin’s fractal dimension, we derive an analytical expression for the rate of replication initiation. This model predicts with no free parameter the temporal profiles of initiation rate, replication fork density and fraction of replicated DNA, in quantitative agreement with corresponding experimental data from both S. cerevisiae and human cells and provides a quantitative estimate of initiation site redundancy. This study shows that, to a large extent, the program that regulates the dynamics of eukaryotic DNA replication is a collective phenomenon that emerges from the stochastic nature of replication origins initiation.

Prediction monitoring and evaluation program; a progress report

USGS Publications Warehouse

Hunter, R.N.; Derr, J.S.

1978-01-01

As part of an attempt to separate useful predictions from inaccurate guesses, we have kept score on earthquake predictions from all sources brought to our attention over the past year and a half. The program was outlined in "Earthquake Prediction;Fact and Fallacy" by Roger N. Hunter (Earthquake Information Bulletin, vol. 8, no. 5, September-October 1976, p. 24-25). The program attracted a great deal of public attention, and, as a result, our files now contain over 2500 predictions from more than 230 different people. 

Predictors of Program Use and Child and Parent Outcomes of A Brief Online Parenting Intervention.

PubMed

Baker, Sabine; Sanders, Matthew R

2017-10-01

Web-based parenting interventions have the potential to increase the currently low reach of parenting programs, but few evidence-based online programs are available, and little is known about who benefits from this delivery format. This study investigated if improvements in child behavior and parenting, following participation in a brief online parenting program (Triple P Online Brief), can be predicted by family and program-related factors. Participants were 100 parents of 2-9-year-old children displaying disruptive behavior problems. Regression analyses showed that higher baseline levels of child behavior problems, older parental age and more intense conflict over parenting pre-intervention predicted greater improvement in child behavior at 9-month follow-up. Improvement in parenting was predicted by higher pre-intervention levels of ineffective parenting. Family demographics, parental adjustment and program related factors did not predict treatment outcomes. Younger child age and lower disagreement over parenting pre-intervention predicted completion of the recommended minimum dose of the program.

Network inference reveals novel connections in pathways regulating growth and defense in the yeast salt response.

PubMed

MacGilvray, Matthew E; Shishkova, Evgenia; Chasman, Deborah; Place, Michael; Gitter, Anthony; Coon, Joshua J; Gasch, Audrey P

2018-05-01

Cells respond to stressful conditions by coordinating a complex, multi-faceted response that spans many levels of physiology. Much of the response is coordinated by changes in protein phosphorylation. Although the regulators of transcriptome changes during stress are well characterized in Saccharomyces cerevisiae, the upstream regulatory network controlling protein phosphorylation is less well dissected. Here, we developed a computational approach to infer the signaling network that regulates phosphorylation changes in response to salt stress. We developed an approach to link predicted regulators to groups of likely co-regulated phospho-peptides responding to stress, thereby creating new edges in a background protein interaction network. We then use integer linear programming (ILP) to integrate wild type and mutant phospho-proteomic data and predict the network controlling stress-activated phospho-proteomic changes. The network we inferred predicted new regulatory connections between stress-activated and growth-regulating pathways and suggested mechanisms coordinating metabolism, cell-cycle progression, and growth during stress. We confirmed several network predictions with co-immunoprecipitations coupled with mass-spectrometry protein identification and mutant phospho-proteomic analysis. Results show that the cAMP-phosphodiesterase Pde2 physically interacts with many stress-regulated transcription factors targeted by PKA, and that reduced phosphorylation of those factors during stress requires the Rck2 kinase that we show physically interacts with Pde2. Together, our work shows how a high-quality computational network model can facilitate discovery of new pathway interactions during osmotic stress.

WallGen, software to construct layered cellulose-hemicellulose networks and predict their small deformation mechanics.

PubMed

Kha, Hung; Tuble, Sigrid C; Kalyanasundaram, Shankar; Williamson, Richard E

2010-02-01

We understand few details about how the arrangement and interactions of cell wall polymers produce the mechanical properties of primary cell walls. Consequently, we cannot quantitatively assess if proposed wall structures are mechanically reasonable or assess the effectiveness of proposed mechanisms to change mechanical properties. As a step to remedying this, we developed WallGen, a Fortran program (available on request) building virtual cellulose-hemicellulose networks by stochastic self-assembly whose mechanical properties can be predicted by finite element analysis. The thousands of mechanical elements in the virtual wall are intended to have one-to-one spatial and mechanical correspondence with their real wall counterparts of cellulose microfibrils and hemicellulose chains. User-defined inputs set the properties of the two polymer types (elastic moduli, dimensions of microfibrils and hemicellulose chains, hemicellulose molecular weight) and their population properties (microfibril alignment and volume fraction, polymer weight percentages in the network). This allows exploration of the mechanical consequences of variations in nanostructure that might occur in vivo and provides estimates of how uncertainties regarding certain inputs will affect WallGen's mechanical predictions. We summarize WallGen's operation and the choice of values for user-defined inputs and show that predicted values for the elastic moduli of multinet walls subject to small displacements overlap measured values. "Design of experiment" methods provide systematic exploration of how changed input values affect mechanical properties and suggest that changing microfibril orientation and/or the number of hemicellulose cross-bridges could change wall mechanical anisotropy.

Fuel cells

NASA Astrophysics Data System (ADS)

Hooie, D. T.; Harrington, B. C., III; Mayfield, M. J.; Parsons, E. L.

1992-07-01

The primary objective of DOE's Fossil Energy Fuel Cell program is to fund the development of key fuel cell technologies in a manner that maximizes private sector participation and in a way that will give contractors the opportunity for a competitive posture, early market entry, and long-term market growth. This summary includes an overview of the Fuel Cell program, an elementary explanation of how fuel cells operate, and a synopsis of the three major fuel cell technologies sponsored by the DOE/Fossil Energy Phosphoric Acid Fuel Cell program, the Molten Carbonate Fuel Cell program, and the Solid Oxide Fuel Cell program.

FLAPS (Fatigue Life Analysis Programs): Computer Programs to Predict Cyclic Life Using the Total Strain Version of Strainrange Partitioning and Other Life Prediction Methods. Users' Manual and Example Problems, Version 1.0

NASA Technical Reports Server (NTRS)

Arya, Vinod K.; Halford, Gary R. (Technical Monitor)

2003-01-01

This manual presents computer programs FLAPS for characterizing and predicting fatigue and creep-fatigue resistance of metallic materials in the high-temperature, long-life regime for isothermal and nonisothermal fatigue. The programs use the Total Strain version of Strainrange Partitioning (TS-SRP), and several other life prediction methods described in this manual. The user should be thoroughly familiar with the TS-SRP and these life prediction methods before attempting to use any of these programs. Improper understanding can lead to incorrect use of the method and erroneous life predictions. An extensive database has also been developed in a parallel effort. The database is probably the largest source of high-temperature, creep-fatigue test data available in the public domain and can be used with other life-prediction methods as well. This users' manual, software, and database are all in the public domain and can be obtained by contacting the author. The Compact Disk (CD) accompanying this manual contains an executable file for the FLAPS program, two datasets required for the example problems in the manual, and the creep-fatigue data in a format compatible with these programs.

Electron and proton damage on InGaAs solar cells having an InP window layer

NASA Technical Reports Server (NTRS)

Messenger, Scott R.; Cotal, Hector L.; Walters, Robert J.; Summers, Geoffrey P.

1995-01-01

As part of a continuing program to determine the space radiation resistance of InP/ln(0.53)Ga(0.47)As tandem solar cells, n/p In(0.53)Ga(0. 47)As solar cells fabricated by RTI were irradiated with 1 MeV electrons and with 3 MeV protons. The cells were grown with a 3 micron n-lnP window layer to mimic the top cell in the tandem cell configuration for both AMO solar absorption and radiation effects. The results have been plotted against 'displacement damage dose' which is the product of the nonionizing energy loss (NIEL) and the particle fluence. A characteristic radiation damage curve can then be obtained for predicting the effect of all particles and energies. AMO, 1 sun solar illumination IV measurements were performed on the irradiated InGaAs solar cells and a characteristic radiation degradation curve was obtained using the solar cell conversion efficiency as the model parameter. Also presented are data comparing the radiation response of both n/p and p/n (fabricated by NREL) InGaAs solar cells as a function of base doping concentration. For the solar cell efficiency, the radiation degradation was found to be independent of the sample polarity for the same base doping concentration.

PD-L1 Is a Therapeutic Target of the Bromodomain Inhibitor JQ1 and, Combined with HLA Class I, a Promising Prognostic Biomarker in Neuroblastoma.

PubMed

Melaiu, Ombretta; Mina, Marco; Chierici, Marco; Boldrini, Renata; Jurman, Giuseppe; Romania, Paolo; D'Alicandro, Valerio; Benedetti, Maria C; Castellano, Aurora; Liu, Tao; Furlanello, Cesare; Locatelli, Franco; Fruci, Doriana

2017-08-01

Purpose: This study sought to evaluate the expression of programmed cell death-ligand-1 (PD-L1) and HLA class I on neuroblastoma cells and programmed cell death-1 (PD-1) and lymphocyte activation gene 3 (LAG3) on tumor-infiltrating lymphocytes to better define patient risk stratification and understand whether this tumor may benefit from therapies targeting immune checkpoint molecules. Experimental Design: In situ IHC staining for PD-L1, HLA class I, PD-1, and LAG3 was assessed in 77 neuroblastoma specimens, previously characterized for tumor-infiltrating T-cell density and correlated with clinical outcome. Surface expression of PD-L1 was evaluated by flow cytometry and IHC in neuroblastoma cell lines and tumors genetically and/or pharmacologically inhibited for MYC and MYCN. A dataset of 477 human primary neuroblastomas from GEO and ArrayExpress databases was explored for PD-L1, MYC, and MYCN correlation. Results: Multivariate Cox regression analysis demonstrated that the combination of PD-L1 and HLA class I tumor cell density is a prognostic biomarker for predicting overall survival in neuroblastoma patients ( P = 0.0448). MYC and MYCN control the expression of PD-L1 in neuroblastoma cells both in vitro and in vivo Consistently, abundance of PD-L1 transcript correlates with MYC expression in primary neuroblastoma. Conclusions: The combination of PD-L1 and HLA class I represents a novel prognostic biomarker for neuroblastoma. Pharmacologic inhibition of MYCN and MYC may be exploited to target PD-L1 and restore an efficient antitumor immunity in high-risk neuroblastoma. Clin Cancer Res; 23(15); 4462-72. ©2017 AACR . ©2017 American Association for Cancer Research.

Emerging role of immunotherapy in urothelial carcinoma - immunobiology/biomarkers

PubMed Central

Sweis, Randy F.; Galsky, Matthew D.

2017-01-01

Urothelial bladder cancer is one of the first cancers recognized to be immunogenic since 40 years ago when the use of bacillus Calmette–Guerin (BCG) was shown to prevent recurrence. Since that time, our knowledge of immune biology of cancer has expanded tremendously, and bladder cancer patients finally have new active immunotherapeutic drugs with on the horizon. Anti-programmed cell death-1 (PD-1)/(programmed cell death ligand-1 (PD-L1) therapy has shown impressively durable responses in urothelial bladder cancer (UBC), but the reported response rates warrant improvement. To outline potential strategies to overcome tumor immune resistance, herein, we summarize current models of tumor immunology with a specific focus on bladder cancer. Recognition of tumor-specific antigens through cross-presentation, T cell priming and activation, and trafficking of immune cells to the tumor microenvironment are some of the critical steps we now understand to be necessary for an effective anti-tumor immune response. Many of the involved steps are important targets for therapeutic interventions. As new immunotherapies are developed, predictive biomarkers will also be important to select patients most likely to respond and to better understand tumor biology. Several potential biomarkers are reviewed including PD-L1 expression, identification of T cell-inflamed/non-T cell-inflamed tumors based on immune gene expression, intrinsic molecular subtyping based on luminal/basal or the cancer genome atlas (TCGA) groups, T cell receptor (TCR) sequencing, and somatic mutational density. Within even the past few years our current knowledge of immune biology has exploded, and we are highly optimistic about the future of UBC therapy that will be available to patients. PMID:27836246

A polynomial based model for cell fate prediction in human diseases.

PubMed

Ma, Lichun; Zheng, Jie

2017-12-21

Cell fate regulation directly affects tissue homeostasis and human health. Research on cell fate decision sheds light on key regulators, facilitates understanding the mechanisms, and suggests novel strategies to treat human diseases that are related to abnormal cell development. In this study, we proposed a polynomial based model to predict cell fate. This model was derived from Taylor series. As a case study, gene expression data of pancreatic cells were adopted to test and verify the model. As numerous features (genes) are available, we employed two kinds of feature selection methods, i.e. correlation based and apoptosis pathway based. Then polynomials of different degrees were used to refine the cell fate prediction function. 10-fold cross-validation was carried out to evaluate the performance of our model. In addition, we analyzed the stability of the resultant cell fate prediction model by evaluating the ranges of the parameters, as well as assessing the variances of the predicted values at randomly selected points. Results show that, within both the two considered gene selection methods, the prediction accuracies of polynomials of different degrees show little differences. Interestingly, the linear polynomial (degree 1 polynomial) is more stable than others. When comparing the linear polynomials based on the two gene selection methods, it shows that although the accuracy of the linear polynomial that uses correlation analysis outcomes is a little higher (achieves 86.62%), the one within genes of the apoptosis pathway is much more stable. Considering both the prediction accuracy and the stability of polynomial models of different degrees, the linear model is a preferred choice for cell fate prediction with gene expression data of pancreatic cells. The presented cell fate prediction model can be extended to other cells, which may be important for basic research as well as clinical study of cell development related diseases.

Agent-Based Deterministic Modeling of the Bone Marrow Homeostasis.

PubMed

Kurhekar, Manish; Deshpande, Umesh

2016-01-01

Modeling of stem cells not only describes but also predicts how a stem cell's environment can control its fate. The first stem cell populations discovered were hematopoietic stem cells (HSCs). In this paper, we present a deterministic model of bone marrow (that hosts HSCs) that is consistent with several of the qualitative biological observations. This model incorporates stem cell death (apoptosis) after a certain number of cell divisions and also demonstrates that a single HSC can potentially populate the entire bone marrow. It also demonstrates that there is a production of sufficient number of differentiated cells (RBCs, WBCs, etc.). We prove that our model of bone marrow is biologically consistent and it overcomes the biological feasibility limitations of previously reported models. The major contribution of our model is the flexibility it allows in choosing model parameters which permits several different simulations to be carried out in silico without affecting the homeostatic properties of the model. We have also performed agent-based simulation of the model of bone marrow system proposed in this paper. We have also included parameter details and the results obtained from the simulation. The program of the agent-based simulation of the proposed model is made available on a publicly accessible website.

HSF-1 activates the ubiquitin proteasome system to promote non-apoptotic developmental cell death in C. elegans.

PubMed

Kinet, Maxime J; Malin, Jennifer A; Abraham, Mary C; Blum, Elyse S; Silverman, Melanie R; Lu, Yun; Shaham, Shai

2016-03-08

Apoptosis is a prominent metazoan cell death form. Yet, mutations in apoptosis regulators cause only minor defects in vertebrate development, suggesting that another developmental cell death mechanism exists. While some non-apoptotic programs have been molecularly characterized, none appear to control developmental cell culling. Linker-cell-type death (LCD) is a morphologically conserved non-apoptotic cell death process operating in Caenorhabditis elegans and vertebrate development, and is therefore a compelling candidate process complementing apoptosis. However, the details of LCD execution are not known. Here we delineate a molecular-genetic pathway governing LCD in C. elegans. Redundant activities of antagonistic Wnt signals, a temporal control pathway, and mitogen-activated protein kinase kinase signaling control heat shock factor 1 (HSF-1), a conserved stress-activated transcription factor. Rather than protecting cells, HSF-1 promotes their demise by activating components of the ubiquitin proteasome system, including the E2 ligase LET-70/UBE2D2 functioning with E3 components CUL-3, RBX-1, BTBD-2, and SIAH-1. Our studies uncover design similarities between LCD and developmental apoptosis, and provide testable predictions for analyzing LCD in vertebrates.

Millimeter wave propagation modeling of inhomogeneous rain media for satellite communications systems

NASA Technical Reports Server (NTRS)

Persinger, R. R.; Stutzman, W. L.

1978-01-01

A theoretical propagation model that represents the scattering properties of an inhomogeneous rain often found on a satellite communications link is presented. The model includes the scattering effects of an arbitrary distribution of particle type (rain or ice), particle shape, particle size, and particle orientation within a given rain cell. An associated rain propagation prediction program predicts attenuation, isolation and phase shift as a function of ground rain rate. A frequency independent synthetic storm algorithm is presented that models nonuniform rain rates present on a satellite link. Antenna effects are included along with a discussion of rain reciprocity. The model is verified using the latest available multiple frequency data from the CTS and COMSTAR satellites. The data covers a wide range of frequencies, elevation angles, and ground site locations.

Inelastic response of metal matrix composites under biaxial loading

NASA Technical Reports Server (NTRS)

Mirzadeh, F.; Pindera, Marek-Jerzy; Herakovich, Carl T.

1990-01-01

Elements of the analytical/experimental program to characterize the response of silicon carbide titanium (SCS-6/Ti-15-3) composite tubes under biaxial loading are outlined. The analytical program comprises prediction of initial yielding and subsequent inelastic response of unidirectional and angle-ply silicon carbide titanium tubes using a combined micromechanics approach and laminate analysis. The micromechanics approach is based on the method of cells model and has the capability of generating the effective thermomechanical response of metal matrix composites in the linear and inelastic region in the presence of temperature and time-dependent properties of the individual constituents and imperfect bonding on the initial yield surfaces and inelastic response of (0) and (+ or - 45)sub s SCS-6/Ti-15-3 laminates loaded by different combinations of stresses. The generated analytical predictions will be compared with the experimental results. The experimental program comprises generation of initial yield surfaces, subsequent stress-strain curves and determination of failure loads of the SCS-6/Ti-15-3 tubes under selected loading conditions. The results of the analytical investigation are employed to define the actual loading paths for the experimental program. A brief overview of the experimental methodology is given. This includes the test capabilities of the Composite Mechanics Laboratory at the University of Virginia, the SCS-6/Ti-15-3 composite tubes secured from McDonnell Douglas Corporation, a text fixture specifically developed for combined axial-torsional loading, and the MTS combined axial-torsion loader that will be employed in the actual testing.

Clinical evaluation of compounds targeting PD-1/PD-L1 pathway for cancer immunotherapy.

PubMed

Lu, Jing; Lee-Gabel, Linda; Nadeau, Michelle C; Ferencz, Thomas M; Soefje, Scott A

2015-12-01

Significant enthusiasm currently exists for new immunotherapeutic strategies: blocking the interaction between programmed death-1 receptor on T-cells and programmed death-ligand 1 on tumor cells to boost immune system stimulation to fight cancer. Immunomodulation with the antiprogrammed death-1/programmed death-ligand 1 monoclonal antibodies has shown to mediate tumor shrinkage and extend overall survival from several pivotal phase I/II studies in melanoma, renal cell carcinoma, and non-small cell lung cancer. This has prompted multiple large ongoing phase III trials with the expectation for fast-track FDA approvals to satisfy unmet medical needs. Compounds targeting the programmed death-1 pathway that are in clinical trials fall into two major categories, namely antiprogrammed death-1 antibodies: Nivolumab, MK-3475, and pidilizumab; and antiprogrammed death-ligand 1 antibodies: MPDL3280A, BMS-936559, MEDI4736, and MSB0010718C. We reviewed the clinical efficacy and safety of each compound based upon major registered clinical trials and published clinical data. Overall, response rate of more than 20% is consistently seen across all these trials, with maximal response of approximately 50% achieved by certain single antiprogrammed death-1 agents or when used in combination with cytotoxic T-lymphocyte antigen-4 blockade. The responses seen are early, durable, and have continued after treatment discontinuation. Immune-related adverse events are the most common side effects seen in these clinical trials. Overall, the skin and gastrointestinal tract are the most common organ systems affected by these compounds while hepatic, endocrine, and neurologic events are less frequent. These side effects are low grade, manageable, and typically resolve within a relatively short time frame with a predictable resolution pattern given proper management. We therefore propose detailed guidelines for management of major immune-related adverse events that are anticipated with antiprogrammed death-1/programmed death-ligand 1 therapies based on general experience with other monoclonal antibodies and the established management algorithms for immune-related adverse events for cytotoxic T-lymphocyte antigen-4 blockade with ipilimumab. We anticipate that the antiprogrammed death-1 strategy will become a viable and crucial clinical strategy for cancer therapy. © The Author(s) 2014.

Biomarker Surrogates Do Not Accurately Predict Sputum Eosinophils and Neutrophils in Asthma

PubMed Central

Hastie, Annette T.; Moore, Wendy C.; Li, Huashi; Rector, Brian M.; Ortega, Victor E.; Pascual, Rodolfo M.; Peters, Stephen P.; Meyers, Deborah A.; Bleecker, Eugene R.

2013-01-01

Background Sputum eosinophils (Eos) are a strong predictor of airway inflammation, exacerbations, and aid asthma management, whereas sputum neutrophils (Neu) indicate a different severe asthma phenotype, potentially less responsive to TH2-targeted therapy. Variables such as blood Eos, total IgE, fractional exhaled nitric oxide (FeNO) or FEV1% predicted, may predict airway Eos, while age, FEV1%predicted, or blood Neu may predict sputum Neu. Availability and ease of measurement are useful characteristics, but accuracy in predicting airway Eos and Neu, individually or combined, is not established. Objectives To determine whether blood Eos, FeNO, and IgE accurately predict sputum eosinophils, and age, FEV1% predicted, and blood Neu accurately predict sputum neutrophils (Neu). Methods Subjects in the Wake Forest Severe Asthma Research Program (N=328) were characterized by blood and sputum cells, healthcare utilization, lung function, FeNO, and IgE. Multiple analytical techniques were utilized. Results Despite significant association with sputum Eos, blood Eos, FeNO and total IgE did not accurately predict sputum Eos, and combinations of these variables failed to improve prediction. Age, FEV1%predicted and blood Neu were similarly unsatisfactory for prediction of sputum Neu. Factor analysis and stepwise selection found FeNO, IgE and FEV1% predicted, but not blood Eos, correctly predicted 69% of sputum Eos

Sun Series program for the REEDA System. [predicting orbital lifetime using sunspot values

NASA Technical Reports Server (NTRS)

Shankle, R. W.

1980-01-01

Modifications made to data bases and to four programs in a series of computer programs (Sun Series) which run on the REEDA HP minicomputer system to aid NASA's solar activity predictions used in orbital life time predictions are described. These programs utilize various mathematical smoothing technique and perform statistical and graphical analysis of various solar activity data bases residing on the REEDA System.

Potential habitat distribution for the freshwater diatom Didymosphenia geminata in the continental US

USGS Publications Warehouse

Kumar, S.; Spaulding, S.A.; Stohlgren, T.J.; Hermann, K.A.; Schmidt, T.S.; Bahls, L.L.

2009-01-01

The diatom Didymosphenia geminata is a single-celled alga found in lakes, streams, and rivers. Nuisance blooms of D geminata affect the diversity, abundance, and productivity of other aquatic organisms. Because D geminata can be transported by humans on waders and other gear, accurate spatial prediction of habitat suitability is urgently needed for early detection and rapid response, as well as for evaluation of monitoring and control programs. We compared four modeling methods to predict D geminata's habitat distribution; two methods use presence-absence data (logistic regression and classification and regression tree [CART]), and two involve presence data (maximum entropy model [Maxent] and genetic algorithm for rule-set production [GARP]). Using these methods, we evaluated spatially explicit, bioclimatic and environmental variables as predictors of diatom distribution. The Maxent model provided the most accurate predictions, followed by logistic regression, CART, and GARP. The most suitable habitats were predicted to occur in the western US, in relatively cool sites, and at high elevations with a high base-flow index. The results provide insights into the factors that affect the distribution of D geminata and a spatial basis for the prediction of nuisance blooms. ?? The Ecological Society of America.

Development of a predictive program for Vibrio parahaemolyticus growth under various environmental conditions.

PubMed

Fujikawa, Hiroshi; Kimura, Bon; Fujii, Tateo

2009-09-01

In this study, we developed a predictive program for Vibrio parahaemolyticus growth under various environmental conditions. Raw growth data was obtained with a V. parahaemolyticus O3:K6 strain cultured at a variety of broth temperatures, pH, and salt concentrations. Data were analyzed with our logistic model and the parameter values of the model were analyzed with polynomial equations. A prediction program consisting of the growth model and the polynomial equations was then developed. After the range of the growth environments was modified, the program successfully predicted the growth for all environments tested. The program could be a useful tool to ensure the bacteriological safety of seafood.

A life prediction methodology for encapsulated solar cells

NASA Technical Reports Server (NTRS)

Coulbert, C. D.

1978-01-01

This paper presents an approach to the development of a life prediction methodology for encapsulated solar cells which are intended to operate for twenty years or more in a terrestrial environment. Such a methodology, or solar cell life prediction model, requires the development of quantitative intermediate relationships between local environmental stress parameters and the basic chemical mechanisms of encapsulant aging leading to solar cell failures. The use of accelerated/abbreviated testing to develop these intermediate relationships and in revealing failure modes is discussed. Current field and demonstration tests of solar cell arrays and the present laboratory tests to qualify solar module designs provide very little data applicable to predicting the long-term performance of encapsulated solar cells. An approach to enhancing the value of such field tests to provide data for life prediction is described.

Anti-PD-1/PD-L1 antibodies in non-small cell lung cancer: the era of immunotherapy.

PubMed

Valecha, Gautam Kishore; Vennepureddy, Adarsh; Ibrahim, Uroosa; Safa, Firas; Samra, Bachar; Atallah, Jean Paul

2017-01-01

Advanced non-small cell lung cancer (NSCLC) has been conventionally treated with cytotoxic chemotherapy with short-lived responses and significant toxicities. Monoclonal antibodies to programmed death-1 receptor (PD-1) and programmed death ligand 1 (PD-L1) have shown tremendous promise in the treatment of advanced NSCLC in various clinical trials. Areas covered: In this article, we will review the outcomes of various trials of anti-PD-1/anti-PD-L1 antibodies in the treatment of NSCLC. We will also discuss their mechanism of action and toxicities. Expert commentary: Anti-PD-1/PD-L1 antibodies offer several advantages including significant antitumor activity, induction of long lasting responses, and favorable safety profile. Several trials are now being conducted to evaluate their efficacy as first line agents as well as in combination with other agents. More research is also needed to identify other biomarkers, in addition to PD-L1 expression, that could more reliably predict response to these drugs, and aid in better patient selection.

Resolving Heart Regeneration by Replacement Histone Profiling.

PubMed

Goldman, Joseph Aaron; Kuzu, Guray; Lee, Nutishia; Karasik, Jaclyn; Gemberling, Matthew; Foglia, Matthew J; Karra, Ravi; Dickson, Amy L; Sun, Fei; Tolstorukov, Michael Y; Poss, Kenneth D

2017-02-27

Chromatin regulation is a principal mechanism governing animal development, yet it is unclear to what extent structural changes in chromatin underlie tissue regeneration. Non-mammalian vertebrates such as zebrafish activate cardiomyocyte (CM) division after tissue damage to regenerate lost heart muscle. Here, we generated transgenic zebrafish expressing a biotinylatable H3.3 histone variant in CMs and derived cell-type-specific profiles of histone replacement. We identified an emerging program of putative enhancers that revise H3.3 occupancy during regeneration, overlaid upon a genome-wide reduction of H3.3 from promoters. In transgenic reporter lines, H3.3-enriched elements directed gene expression in subpopulations of CMs. Other elements increased H3.3 enrichment and displayed enhancer activity in settings of injury- and/or Neuregulin1-elicited CM proliferation. Dozens of consensus sequence motifs containing predicted transcription factor binding sites were enriched in genomic regions with regeneration-responsive H3.3 occupancy. Thus, cell-type-specific regulatory programs of tissue regeneration can be revealed by genome-wide H3.3 profiling. Copyright © 2017 Elsevier Inc. All rights reserved.

Beach morphology monitoring in the Columbia River Littoral Cell: 1997-2005

USGS Publications Warehouse

Ruggiero, Peter; Eshleman, Jodi L.; Kingsley, Etienne; Thompson, David M.; Voigt, Brian; Kaminsky, George M.; Gelfenbaum, Guy

2007-01-01

This report describes methods used, data collected, and results of the Beach Morphology Monitoring Program in the Columbia River Littoral Cell (CRLC) from 1997 to 2005. A collaborative group primarily consisting of the US Geological Survey and the Washington State Department of Ecology performed this work. Beach Monitoring efforts consisted of collecting topographic and bathymetric horizontal and vertical position data using a Real Time Kinematic Differential Global Positioning System (RTK-DGPS). Sediment size distribution data was also collected as part of this effort. The monitoring program was designed to: 1) quantify the short- to medium-term (seasonal to interannual) beach change rates and morphological variability along the CRLC and assess the processes responsible for these changes; 2) collect beach state data (i.e., grain size, beach slope, and dune/sandbar height/position) to enhance the conceptual understanding of CRLC functioning and refine predictions of future coastal change and hazards; 3) compare and contrast the scales of environmental forcing and beach morphodynamics in the CRLC to other coastlines of the world; and 4) provide beach change data in a useful format to land use managers.

Teaching the Fundamentals of Cell Phones and Wireless Communications

NASA Astrophysics Data System (ADS)

Davids, Mark; Forrest, Rick; Pata, Don

2010-04-01

Wireless communications are ubiquitous. Students and teachers use iPhones®, BlackBerrys®, and other smart phones at home and at work. More than 275 million Americans had cell phones in June of 2009 and expanded access to broadband is predicted this year.2 Despite the plethora of users, most students and teachers do not understand "how they work." Over the past several years, three high school teachers have collaborated with engineers at Cingular, Motorola, and the University of Michigan to explore the underlying science and design a three-week, student-centered unit with a constructivist pedagogy consistent with the "Modeling in Physics" philosophy.3 This unique pilot program reinforces traditional physics topics including vibrations and waves, sound, light, electricity and magnetism, and also introduces key concepts in communications and information theory. This article will describe the motivation for our work, outline a few key concepts with the corresponding student activities, and provide a summary of the program that has been developed to engage and inspire the next generation of scientists, engineers, and citizens.

Levels of HIV1 gp120 3D B-cell epitopes mutability and variability: searching for possible vaccine epitopes.

PubMed

Khrustalev, Vladislav Victorovich

2010-01-01

We used a DiscoTope 1.2 (http://www.cbs.dtu.dk/services/DiscoTope/), Epitopia (http://epitopia.tau.ac.il/) and EPCES (http://www.t38.physik.tu-muenchen.de/programs.htm) algorithms to map discontinuous B-cell epitopes in HIV1 gp120. The most mutable nucleotides in HIV genes are guanine (because of G to A hypermutagenesis) and cytosine (because of C to U and C to A mutations). The higher is the level of guanine and cytosine usage in third (neutral) codon positions and the lower is their level in first and second codon positions of the coding region, the more stable should be an epitope encoded by this region. We compared guanine and cytosine usage in regions coding for five predicted 3D B-cell epitopes of gp120. To make this comparison we used GenBank resource: 385 sequences of env gene obtained from ten HIV1-infected individuals were studied (http://www.barkovsky.hotmail.ru/Data/Seqgp120.htm). The most protected from nonsynonymous nucleotide mutations of guanine and cytosine 3D B-cell epitope is situated in the first conserved region of gp120 (it is mapped from 66th to 86th amino acid residue). We applied a test of variability to confirm this finding. Indeed, the less mutable predicted B-cell epitope is the less variable one. MEGA4 (standard PAM matrix) was used for the alignments and "VVK Consensus" algorithm (http://www.barkovsky.hotmail.ru) was used for the calculations.

Space shuttle main engine plume radiation model

NASA Technical Reports Server (NTRS)

Reardon, J. E.; Lee, Y. C.

1978-01-01

The methods are described which are used in predicting the thermal radiation received by space shuttles, from the plumes of the main engines. Radiation to representative surface locations were predicted using the NASA gaseous plume radiation GASRAD program. The plume model is used with the radiative view factor (RAVFAC) program to predict sea level radiation at specified body points. The GASRAD program is described along with the predictions. The RAVFAC model is also discussed.

An animated landscape representation of CD4+ T-cell differentiation, variability, and plasticity: Insights into the behavior of populations versus cells

PubMed Central

Rebhahn, Jonathan A; Deng, Nan; Sharma, Gaurav; Livingstone, Alexandra M; Huang, Sui; Mosmann, Tim R

2014-01-01

Recent advances in understanding CD4+ T-cell differentiation suggest that previous models of a few distinct, stable effector phenotypes were too simplistic. Although several well-characterized phenotypes are still recognized, some states display plasticity, and intermediate phenotypes exist. As a framework for reexamining these concepts, we use Waddington's landscape paradigm, augmented with explicit consideration of stochastic variations. Our animation program “LAVA” visualizes T-cell differentiation as cells moving across a landscape of hills and valleys, leading to attractor basins representing stable or semistable differentiation states. The model illustrates several principles, including: (i) cell populations may behave more predictably than individual cells; (ii) analogous to reticulate evolution, differentiation may proceed through a network of interconnected states, rather than a single well-defined pathway; (iii) relatively minor changes in the barriers between attractor basins can change the stability or plasticity of a population; (iv) intrapopulation variability of gene expression may be an important regulator of differentiation, rather than inconsequential noise; (v) the behavior of some populations may be defined mainly by the behavior of outlier cells. While not a quantitative representation of actual differentiation, our model is intended to provoke discussion of T-cell differentiation pathways, particularly highlighting a probabilistic view of transitions between states. PMID:24945794

Computer programs to predict induced effects of jets exhausting into a crossflow

NASA Technical Reports Server (NTRS)

Perkins, S. C., Jr.; Mendenhall, M. R.

1984-01-01

A user's manual for two computer programs was developed to predict the induced effects of jets exhausting into a crossflow. Program JETPLT predicts pressures induced on an infinite flat plate by a jet exhausting at angles to the plate and Program JETBOD, in conjunction with a panel code, predicts pressures induced on a body of revolution by a jet exhausting normal to the surface. Both codes use a potential model of the jet and adjacent surface with empirical corrections for the viscous or nonpotential effects. This program manual contains a description of the use of both programs, instructions for preparation of input, descriptions of the output, limitations of the codes, and sample cases. In addition, procedures to extend both codes to include additional empirical correlations are described.

Multiscale modeling of mucosal immune responses

PubMed Central

2015-01-01

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

Multiscale modeling of mucosal immune responses.

PubMed

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

2015-01-01

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

Prediction of Response to Therapy and Clinical Outcome through a Pilot Study of Complete Genetic Assessment of Ovarian Cancer

DTIC Science & Technology

2015-12-01

Oncology program supported by this grant consented patients to 11-104. OncoPanel is a cancer genomic assay that detects somatic mutations, copy number...KMT2D, EP300, FANCD2 Sertoli Leydig cell DICER1 Copy number variants: In addition, 219 patients were analyzed for copy-number variations ( CNV ) in...OncoPanel genes. >12,000 total CNV were reported in the cohort (Figure 2). Single- copy deletions (n=5558) and copy-number gains (low amplification) (n

Search for Functional Flexible Regions in the G-protein Family: New Reading of the FoldUnfold Program.

PubMed

Galzitskaya, Oxana; Deryusheva, Eugenia; Machulin, Andrey; Nemashkalova, Ekaterina; Glyakina, Anna

2018-06-21

High prediction accuracy of flexible loops in different protein families is a challenge because of the crucial functions associated with these regions. Results of the currently available programs for prediction of loops vary from protein to protein. For prediction of flexible regions in the G-domain for 23 representatives of G-proteins with the known 3D structure we have used eight programs. The results of predictions demonstrate that the FoldUnfold program predicts better loop positions than the PONDR, RОNN, DisEMBL, IUPred, GlobPlot 2, FoldIndex, and MobiDB programs. When classifying the predicted loops (rigid/flexible) according to the Debye-Waller fluctuation factors, our data reveal the existing weak correlation between the B-factors and the average number of closed residues according to the FoldUnfold program; the percentage of overlapping characteristics (residue fold/unfold status) of the protein residues from the two methods is about 60-70%. According to the FoldUnfold program, for G-proteins with the posttranslational modifications, the surrounding binding site residues by disordered-promoting glycine and alanine residues conduces to a more flexible position of the binding sites for fatty acid, while methionine, cysteine and isoleucine residues provide more rigid binding sites. Thus, our research demonstrates additional possibilities of the FoldUnfold program for prediction of flexible regions and characteristics of individual residues in a different protein family. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Lack of the programmed death-1 receptor renders host susceptible to enteric microbial infection through impairing the production of the mucosal natural killer cell effector molecules.

PubMed

Solaymani-Mohammadi, Shahram; Lakhdari, Omar; Minev, Ivelina; Shenouda, Steve; Frey, Blake F; Billeskov, Rolf; Singer, Steven M; Berzofsky, Jay A; Eckmann, Lars; Kagnoff, Martin F

2016-03-01

The programmed death-1 receptor is expressed on a wide range of immune effector cells, including T cells, natural killer T cells, dendritic cells, macrophages, and natural killer cells. In malignancies and chronic viral infections, increased expression of programmed death-1 by T cells is generally associated with a poor prognosis. However, its role in early host microbial defense at the intestinal mucosa is not well understood. We report that programmed death-1 expression is increased on conventional natural killer cells but not on CD4(+), CD8(+) or natural killer T cells, or CD11b(+) or CD11c(+) macrophages or dendritic cells after infection with the mouse pathogen Citrobacter rodentium. Mice genetically deficient in programmed death-1 or treated with anti-programmed death-1 antibody were more susceptible to acute enteric and systemic infection with Citrobacter rodentium. Wild-type but not programmed death-1-deficient mice infected with Citrobacter rodentium showed significantly increased expression of the conventional mucosal NK cell effector molecules granzyme B and perforin. In contrast, natural killer cells from programmed death-1-deficient mice had impaired expression of those mediators. Consistent with programmed death-1 being important for intracellular expression of natural killer cell effector molecules, mice depleted of natural killer cells and perforin-deficient mice manifested increased susceptibility to acute enteric infection with Citrobacter rodentium. Our findings suggest that increased programmed death-1 signaling pathway expression by conventional natural killer cells promotes host protection at the intestinal mucosa during acute infection with a bacterial gut pathogen by enhancing the expression and production of important effectors of natural killer cell function. © Society for Leukocyte Biology.

Selection of optimal sensors for predicting performance of polymer electrolyte membrane fuel cell

NASA Astrophysics Data System (ADS)

Mao, Lei; Jackson, Lisa

2016-10-01

In this paper, sensor selection algorithms are investigated based on a sensitivity analysis, and the capability of optimal sensors in predicting PEM fuel cell performance is also studied using test data. The fuel cell model is developed for generating the sensitivity matrix relating sensor measurements and fuel cell health parameters. From the sensitivity matrix, two sensor selection approaches, including the largest gap method, and exhaustive brute force searching technique, are applied to find the optimal sensors providing reliable predictions. Based on the results, a sensor selection approach considering both sensor sensitivity and noise resistance is proposed to find the optimal sensor set with minimum size. Furthermore, the performance of the optimal sensor set is studied to predict fuel cell performance using test data from a PEM fuel cell system. Results demonstrate that with optimal sensors, the performance of PEM fuel cell can be predicted with good quality.

Aircraft Noise Prediction Program theoretical manual: Propeller aerodynamics and noise

NASA Technical Reports Server (NTRS)

Zorumski, W. E. (Editor); Weir, D. S. (Editor)

1986-01-01

The prediction sequence used in the aircraft noise prediction program (ANOPP) is described. The elements of the sequence are called program modules. The first group of modules analyzes the propeller geometry, the aerodynamics, including both potential and boundary-layer flow, the propeller performance, and the surface loading distribution. This group of modules is based entirely on aerodynamic strip theory. The next group of modules deals with the first group. Predictions of periodic thickness and loading noise are determined with time-domain methods. Broadband noise is predicted by a semiempirical method. Near-field predictions of fuselage surface pressrues include the effects of boundary layer refraction and scattering. Far-field predictions include atmospheric and ground effects.

The flow of plasma in the solar terrestrial environment

NASA Technical Reports Server (NTRS)

Schunk, Robert W.; Banks, P.; Barakat, A. R.; Crain, D. J.; Demars, H. G.; Lemaire, J.; Ma, T.-Z.; Rasmussen, C. E.; Richards, P.; Sica, R.

1990-01-01

The overall goal of our NASA Theory Program was to study the coupling, time delays, and feedback mechanisms between the various regions of the solar-terrestrial system in a self-consistent, quantitative manner. To accomplish this goal, it will eventually be necessary to have time-dependent macroscopic models of the different regions of the solar-terrestrial system and we are continually working toward this goal. However, with the funding from this NASA program, we concentrated on the near-earth plasma environment, including the ionosphere, the plasmasphere, and the polar wind. In this area, we developed unique global models that allowed us to study the coupling between the different regions. These results are highlighted in the next section. Another important aspect of our NASA Theory Program concerned the effect that localized 'structure' had on the macroscopic flow in the ionosphere, plasmasphere, thermosphere, and polar wind. The localized structure can be created by structured magnetospheric inputs (i.e., structured plasma convection, particle precipitation or Birkland current patterns) or time variations in these input due to storms and substorms. Also, some of the plasma flows that we predicted with our macroscopic models could be unstable, and another one of our goals was to examine the stability of our predicted flows. Because time-dependent, three-dimensional numerical models of the solar-terrestrial environment generally require extensive computer resources, they are usually based on relatively simple mathematical formulations (i.e., simple MHD or hydrodynamic formulations). Therefore, another goal of our NASA Theory Program was to study the conditions under which various mathematical formulations can be applied to specific solar-terrestrial regions. This could involve a detailed comparison of kinetic, semi-kinetic, and hydrodynamic predictions for a given polar wind scenario or it could involve the comparison of a small-scale particle-in-cell (PIC) simulation of a plasma expansion event with a similar macroscopic expansion event. The different mathematical formulations have different strengths and weaknesses and a careful comparison of model predictions for similar geophysical situations provides insight into when the various models can be used with confidence.

Virtual Interactomics of Proteins from Biochemical Standpoint

PubMed Central

Kubrycht, Jaroslav; Sigler, Karel; Souček, Pavel

2012-01-01

Virtual interactomics represents a rapidly developing scientific area on the boundary line of bioinformatics and interactomics. Protein-related virtual interactomics then comprises instrumental tools for prediction, simulation, and networking of the majority of interactions important for structural and individual reproduction, differentiation, recognition, signaling, regulation, and metabolic pathways of cells and organisms. Here, we describe the main areas of virtual protein interactomics, that is, structurally based comparative analysis and prediction of functionally important interacting sites, mimotope-assisted and combined epitope prediction, molecular (protein) docking studies, and investigation of protein interaction networks. Detailed information about some interesting methodological approaches and online accessible programs or databases is displayed in our tables. Considerable part of the text deals with the searches for common conserved or functionally convergent protein regions and subgraphs of conserved interaction networks, new outstanding trends and clinically interesting results. In agreement with the presented data and relationships, virtual interactomic tools improve our scientific knowledge, help us to formulate working hypotheses, and they frequently also mediate variously important in silico simulations. PMID:22928109

Anaplasia is rare and does not influence prognosis in adult medulloblastoma.

PubMed

Giordana, Maria Teresa; D'Agostino, Carla; Pollo, Bianca; Silvani, Antonio; Ferracini, Romano; Paiolo, Anna; Ghiglione, Paolo; Chiò, Adriano

2005-10-01

Histopathologic grading based on increasing anaplasia predicts clinical behavior of pediatric medulloblastomas. The present study was aimed at grading 86 medulloblastomas of adult patients (aged 18 and older) by anaplasia and analyzing the predictive power. Nodularity, desmoplasia, nuclear size, nuclear pleomorphism, necrosis, and endothelial proliferations have been evaluated. Morphometric analysis of nuclear size was performed using the Eclipse Net program. Patients treated with standard postoperative radiotherapy (35 Gy to craniospinal axis and 50 Gy to posterior fossa) were considered for correlation with survival. Pathologic data and total survival were compared by Kaplan-Meier and logrank analysis. No correlation was found between total survival duration and individual pathologic features. Cooccurrence of nuclear pleomorphism, large nuclear diameter, microvascular proliferations, and necroses did not predict outcome. Severe nuclear pleomorphism was found in 4 of 86 cases; the only large-cell medulloblastoma was from an 18-year-old patient. Histopathologic factors have no clinical use for stratification of patients in risk groups. The histologic spectrum of medulloblastoma in adults is different from that in children.

Identification of human microRNA targets from isolated argonaute protein complexes.

PubMed

Beitzinger, Michaela; Peters, Lasse; Zhu, Jia Yun; Kremmer, Elisabeth; Meister, Gunter

2007-06-01

MicroRNAs (miRNAs) constitute a class of small non-coding RNAs that regulate gene expression on the level of translation and/or mRNA stability. Mammalian miRNAs associate with members of the Argonaute (Ago) protein family and bind to partially complementary sequences in the 3' untranslated region (UTR) of specific target mRNAs. Computer algorithms based on factors such as free binding energy or sequence conservation have been used to predict miRNA target mRNAs. Based on such predictions, up to one third of all mammalian mRNAs seem to be under miRNA regulation. However, due to the low degree of complementarity between the miRNA and its target, such computer programs are often imprecise and therefore not very reliable. Here we report the first biochemical identification approach of miRNA targets from human cells. Using highly specific monoclonal antibodies against members of the Ago protein family, we co-immunoprecipitate Ago-bound mRNAs and identify them by cloning. Interestingly, most of the identified targets are also predicted by different computer programs. Moreover, we randomly analyzed six different target candidates and were able to experimentally validate five as miRNA targets. Our data clearly indicate that miRNA targets can be experimentally identified from Ago complexes and therefore provide a new tool to directly analyze miRNA function.

Molecular classification of gastric adenocarcinoma: translating new insights from the cancer genome atlas research network.

PubMed

Sunakawa, Yu; Lenz, Heinz-Josef

2015-04-01

Gastric cancer is a heterogenous cancer, which may be classified into several distinct subtypes based on pathology and epidemiology, each with different initiating pathological processes and each possibly having different tumor biology. A classification of gastric cancer should be important to select patients who can benefit from the targeted therapies or to precisely predict prognosis. The Cancer Genome Atlas (TCGA) study collaborated with previous reports regarding subtyping gastric cancer but also proposed a refined classification based on molecular characteristics. The addition of the new molecular classification strategy to a current classical subtyping may be a promising option, particularly stratification by Epstein-Barr virus (EBV) and microsatellite instability (MSI) statuses. According to TCGA study, EBV gastric cancer patients may benefit the programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) antibodies or phosphoinositide 3-kinase (PI3K) inhibitors which are now being developed. The discoveries of predictive biomarkers should improve patient care and individualized medicine in the management since the targeted therapies may have the potential to change the landscape of gastric cancer treatment, moreover leading to both better understanding of the heterogeneity and better outcomes. Patient enrichment by predictive biomarkers for new treatment strategies will be critical to improve clinical outcomes. Additionally, liquid biopsies will be able to enable us to monitor in real-time molecular escape mechanism, resulting in better treatment strategies.

SIM_ADJUST -- A computer code that adjusts simulated equivalents for observations or predictions

USGS Publications Warehouse

Poeter, Eileen P.; Hill, Mary C.

2008-01-01

This report documents the SIM_ADJUST computer code. SIM_ADJUST surmounts an obstacle that is sometimes encountered when using universal model analysis computer codes such as UCODE_2005 (Poeter and others, 2005), PEST (Doherty, 2004), and OSTRICH (Matott, 2005; Fredrick and others (2007). These codes often read simulated equivalents from a list in a file produced by a process model such as MODFLOW that represents a system of interest. At times values needed by the universal code are missing or assigned default values because the process model could not produce a useful solution. SIM_ADJUST can be used to (1) read a file that lists expected observation or prediction names and possible alternatives for the simulated values; (2) read a file produced by a process model that contains space or tab delimited columns, including a column of simulated values and a column of related observation or prediction names; (3) identify observations or predictions that have been omitted or assigned a default value by the process model; and (4) produce an adjusted file that contains a column of simulated values and a column of associated observation or prediction names. The user may provide alternatives that are constant values or that are alternative simulated values. The user may also provide a sequence of alternatives. For example, the heads from a series of cells may be specified to ensure that a meaningful value is available to compare with an observation located in a cell that may become dry. SIM_ADJUST is constructed using modules from the JUPITER API, and is intended for use on any computer operating system. SIM_ADJUST consists of algorithms programmed in Fortran90, which efficiently performs numerical calculations.

Near-roadway monitoring of vehicle emissions as a function of mode of operation for light-duty vehicles.

PubMed

Wen, Dongqi; Zhai, Wenjuan; Xiang, Sheng; Hu, Zhice; Wei, Tongchuan; Noll, Kenneth E

2017-11-01

Determination of the effect of vehicle emissions on air quality near roadways is important because vehicles are a major source of air pollution. A near-roadway monitoring program was undertaken in Chicago between August 4 and October 30, 2014, to measure ultrafine particles, carbon dioxide, carbon monoxide, traffic volume and speed, and wind direction and speed. The objective of this study was to develop a method to relate short-term changes in traffic mode of operation to air quality near roadways using data averaged over 5-min intervals to provide a better understanding of the processes controlling air pollution concentrations near roadways. Three different types of data analysis are provided to demonstrate the type of results that can be obtained from a near-roadway sampling program based on 5-min measurements: (1) development of vehicle emission factors (EFs) for ultrafine particles as a function of vehicle mode of operation, (2) comparison of measured and modeled CO 2 concentrations, and (3) application of dispersion models to determine concentrations near roadways. EFs for ultrafine particles are developed that are a function of traffic volume and mode of operation (free flow and congestion) for light-duty vehicles (LDVs) under real-world conditions. Two air quality models-CALINE4 (California Line Source Dispersion Model, version 4) and AERMOD (American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model)-are used to predict the ultrafine particulate concentrations near roadways for comparison with measured concentrations. When using CALINE4 to predict air quality levels in the mixing cell, changes in surface roughness and stability class have no effect on the predicted concentrations. However, when using AERMOD to predict air quality in the mixing cell, changes in surface roughness have a significant impact on the predicted concentrations. The paper provides emission factors (EFs) that are a function of traffic volume and mode of operation (free flow and congestion) for LDVs under real-world conditions. The good agreement between monitoring and modeling results indicates that high-resolution, simultaneous measurements of air quality and meteorological and traffic conditions can be used to determine real-world, fleet-wide vehicle EFs as a function of vehicle mode of operation under actual driving conditions.

COSIM: A Finite-Difference Computer Model to Predict Ternary Concentration Profiles Associated With Oxidation and Interdiffusion of Overlay-Coated Substrates

NASA Technical Reports Server (NTRS)

Nesbitt, James A.

2001-01-01

A finite-difference computer program (COSIM) has been written which models the one-dimensional, diffusional transport associated with high-temperature oxidation and interdiffusion of overlay-coated substrates. The program predicts concentration profiles for up to three elements in the coating and substrate after various oxidation exposures. Surface recession due to solute loss is also predicted. Ternary cross terms and concentration-dependent diffusion coefficients are taken into account. The program also incorporates a previously-developed oxide growth and spalling model to simulate either isothermal or cyclic oxidation exposures. In addition to predicting concentration profiles after various oxidation exposures, the program can also be used to predict coating life based on a concentration dependent failure criterion (e.g., surface solute content drops to 2%). The computer code is written in FORTRAN and employs numerous subroutines to make the program flexible and easily modifiable to other coating oxidation problems.

Using Predictive Analytics to Detect Major Problems in Department of Defense Acquisition Programs

DTIC Science & Technology

2012-03-01

research is focused on three questions. First, can we predict the contractor provided estimate at complete (EAC)? Second, can we use those predictions to...develop an algorithm to determine if a problem will occur in an acquisition program or sub-program? Lastly, can we provide the probability of a problem...more than doubling the probability of a problem occurrence compared to current tools in the cost community. Though program managers can use this

Model of inter-cell interference phenomenon in 10 nm magnetic tunnel junction with perpendicular anisotropy array due to oscillatory stray field from neighboring cells

NASA Astrophysics Data System (ADS)

Ohuchida, Satoshi; Endoh, Tetsuo

2018-06-01

In this paper, we propose a new model of inter-cell interference phenomenon in a 10 nm magnetic tunnel junction with perpendicular anisotropy (p-MTJ) array and investigated the interference effect between a program cell and unselected cells due to the oscillatory stray field from neighboring cells by Landau–Lifshitz–Gilbert micromagnetic simulation. We found that interference brings about a switching delay in a program cell and excitation of magnetization precession in unselected cells even when no programing current passes through. The origin of interference is ferromagnetic resonance between neighboring cells. During the interference period, the precession frequency of the program cell is 20.8 GHz, which synchronizes with that of the theoretical precession frequency f = γH eff in unselected cells. The disturbance strength of unselected cells decreased to be inversely proportional to the cube of the distance from the program cell, which is in good agreement with the dependence of stray field on the distance from the program cell calculated by the dipole approximation method.

Accelerated/abbreviated test methods for predicting life of solar cell encapsulants to Jet Propulsion Laboratory California Institute of Technology for the encapsulation task of the low-cost solar array project

NASA Technical Reports Server (NTRS)

Kolyer, J. M.

1978-01-01

An important principle is that encapsulants should be tested in a total array system allowing realistic interaction of components. Therefore, micromodule test specimens were fabricated with a variety of encapsulants, substrates, and types of circuitry. One common failure mode was corrosion of circuitry and solar cell metallization due to moisture penetration. Another was darkening and/or opacification of encapsulant. A test program plan was proposed. It includes multicondition accelerated exposure. Another method was hyperaccelerated photochemical exposure using a solar concentrator. It simulates 20 year of sunlight exposure in a short period of one to two weeks. The study was beneficial in identifying some cost effective encapsulants and array designs.

Chemotherapy treatment is associated with altered PD-L1 expression in lung cancer patients.

PubMed

Rojkó, Lívia; Reiniger, Lilla; Téglási, Vanda; Fábián, Katalin; Pipek, Orsolya; Vágvölgyi, Attila; Agócs, László; Fillinger, János; Kajdácsi, Zita; Tímár, József; Döme, Balázs; Szállási, Zoltán; Moldvay, Judit

2018-04-19

While the predictive value of programmed cell death ligand-1 (PD-L1) protein expression for immune checkpoint inhibitor therapy of lung cancer has been extensively studied, the impact of standard platinum-based chemotherapy on PD-L1 or programmed cell death-1 (PD-1) expression is unknown. The aim of this study was to determine the changes in PD-L1 expression of tumor cells (TC) and immune cells (IC), in PD-1 expression of IC, and in the amount of stromal mononuclear cell infiltration after platinum-based chemotherapy in patients with lung cancer. We determined the amount of stromal mononuclear cells and PD-L1/PD-1 expressions by immunohistochemistry in bronchoscopic biopsy samples including 20 adenocarcinomas (ADC), 15 squamous cell carcinomas (SCC), 2 other types of non-small cell lung cancer, and 4 small cell lung cancers together with their corresponding surgical resection tissues after platinum-based chemotherapy. PD-L1 expression of TC decreased in ten patients (24.4%) and increased in three patients (7.32%) after neoadjuvant chemotherapy (p = 0.051). The decrease in PD-L1 expression, however, was significant only in patients who received cisplatin-gemcitabine combination (p = 0.020), while in the carboplatin-paclitaxel group, no similar tendency could be observed (p = 0.432). There was no difference between ADC and SCC groups. Neither PD-1 expression nor the amount of stromal IC infiltration showed significant changes after chemotherapy. This is the first study, in which both PD-L1 and PD-1 expression were analyzed together with the amount of stromal IC infiltration in different histological subtypes of lung cancer before and after platinum-based chemotherapy. Our results confirm that chemotherapy decreases PD-L1 expression of TC in a subset of patients, therefore, rebiopsy and re-evaluation of PD-L1 expression may be necessary for the indication of immune checkpoint inhibitor therapy.

Optical coherence tomography spectral analysis for detecting apoptosis in vitro and in vivo

NASA Astrophysics Data System (ADS)

Farhat, Golnaz; Giles, Anoja; Kolios, Michael C.; Czarnota, Gregory J.

2015-12-01

Apoptosis is a form of programmed cell death characterized by a series of predictable morphological changes at the subcellular level, which modify the light-scattering properties of cells. We present a spectroscopic optical coherence tomography (OCT) technique to detect changes in subcellular morphology related to apoptosis in vitro and in vivo. OCT data were acquired from acute myeloid leukemia (AML) cells treated with cisplatin over a 48-h period. The backscatter spectrum of the OCT signal acquired from the cell samples was characterized by calculating its in vitro integrated backscatter (IB) and spectral slope (SS). The IB increased with treatment duration, while the SS decreased, with the most significant changes occurring after 24 to 48 h of treatment. These changes coincided with striking morphological transformations in the cells and their nuclei. Similar trends in the spectral parameter values were observed in vivo in solid tumors grown from AML cells in mice, which were treated with chemotherapy and radiation. Our results provide a strong foundation from which future experiments may be designed to further understand the effect of cellular morphology and kinetics of apoptosis on the OCT signal and demonstrate the feasibility of using this technique in vivo.

The flow of plasma in the solar terrestrial environment

NASA Technical Reports Server (NTRS)

Schunk, R. W.

1992-01-01

The overall goal of our NASA Theory Program is to study the coupling, time delays, and feedback mechanisms between the various regions of the solar-terrestrial system in a self-consistent, quantitative manner. To accomplish this goal, it will eventually be necessary to have time-dependent macroscopic models of the different regions of the solar-terrestrial system and we are continually working toward this goal. However, our immediate emphasis is on the near-earth plasma environment, including the ionosphere, the plasmasphere, and the polar wind. In this area, we have developed unique global models that allow us to study the coupling between the different regions. Another important aspect of our NASA Theory Program concerns the effect that localized structure has on the macroscopic flow in the ionosphere, plasmasphere, thermosphere, and polar wind. The localized structure can be created by structured magnetospheric inputs (i.e., structured plasma convection, particle precipitation or Birkeland current patterns) or time variations in these inputs due to storms and substorms. Also, some of the plasma flows that we predict with our macroscopic models may be unstable, and another one of our goals is to examine the stability of our predicted flows. Because time-dependent, three-dimensional numerical models of the solar-terrestrial environment generally require extensive computer resources, they are usually based on relatively simple mathematical formulations (i.e., simple MHD or hydrodynamic formulation). Therefore, another long-range goal of our NASA Theory Program is to study the conditions under which various mathematical formulations can be applied to specific solar-terrestrial regions. This may involve a detailed comparison of kinetic, semikinetic, and hydrodynamic predictions for a given polar wind scenario or it may involve the comparison of a small-scale particle-in-cell (PIC) simulation of a plasma expansion event with a similar macroscopic expansion event. The different mathematical formulations have different strengths and weaknesses and a careful comparison of model predictions for similar geophysical situations will provide insight into when the various models can be used with confidence.

The Use of Linear Programming for Prediction.

ERIC Educational Resources Information Center

Schnittjer, Carl J.

The purpose of the study was to develop a linear programming model to be used for prediction, test the accuracy of the predictions, and compare the accuracy with that produced by curvilinear multiple regression analysis. (Author)

Assessment of Automated Analyses of Cell Migration on Flat and Nanostructured Surfaces

PubMed Central

Grădinaru, Cristian; Łopacińska, Joanna M.; Huth, Johannes; Kestler, Hans A.; Flyvbjerg, Henrik; Mølhave, Kristian

2012-01-01

Motility studies of cells often rely on computer software that analyzes time-lapse recorded movies and establishes cell trajectories fully automatically. This raises the question of reproducibility of results, since different programs could yield significantly different results of such automated analysis. The fact that the segmentation routines of such programs are often challenged by nanostructured surfaces makes the question more pertinent. Here we illustrate how it is possible to track cells on bright field microscopy images with image analysis routines implemented in an open-source cell tracking program, PACT (Program for Automated Cell Tracking). We compare the automated motility analysis of three cell tracking programs, PACT, Autozell, and TLA, using the same movies as input for all three programs. We find that different programs track overlapping, but different subsets of cells due to different segmentation methods. Unfortunately, population averages based on such different cell populations, differ significantly in some cases. Thus, results obtained with one software package are not necessarily reproducible by other software. PMID:24688640

The Climate Variability & Predictability (CVP) Program at NOAA - Recent Program Advancements

NASA Astrophysics Data System (ADS)

Lucas, S. E.; Todd, J. F.

2015-12-01

The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International and U.S. Climate Variability and Predictability (CLIVAR/US CLIVAR) Program, and the U.S. Global Change Research Program (USGCRP). The CVP program sits within NOAA's Climate Program Office (http://cpo.noaa.gov/CVP). The CVP Program currently supports multiple projects in areas that are aimed at improved representation of physical processes in global models. Some of the topics that are currently funded include: i) Improved Understanding of Intraseasonal Tropical Variability - DYNAMO field campaign and post -field projects, and the new climate model improvement teams focused on MJO processes; ii) Climate Process Teams (CPTs, co-funded with NSF) with projects focused on Cloud macrophysical parameterization and its application to aerosol indirect effects, and Internal-Wave Driven Mixing in Global Ocean Models; iii) Improved Understanding of Tropical Pacific Processes, Biases, and Climatology; iv) Understanding Arctic Sea Ice Mechanism and Predictability;v) AMOC Mechanisms and Decadal Predictability Recent results from CVP-funded projects will be summarized. Additional information can be found at http://cpo.noaa.gov/CVP.

The predictive information obtained by testing multiple software versions

NASA Technical Reports Server (NTRS)

Lee, Larry D.

1987-01-01

Multiversion programming is a redundancy approach to developing highly reliable software. In applications of this method, two or more versions of a program are developed independently by different programmers and the versions are combined to form a redundant system. One variation of this approach consists of developing a set of n program versions and testing the versions to predict the failure probability of a particular program or a system formed from a subset of the programs. The precision that might be obtained, and also the effect of programmer variability if predictions are made over repetitions of the process of generating different program versions, are examined.

An analysis for high speed propeller-nacelle aerodynamic performance prediction. Volume 2: User's manual

NASA Technical Reports Server (NTRS)

Egolf, T. Alan; Anderson, Olof L.; Edwards, David E.; Landgrebe, Anton J.

1988-01-01

A user's manual for the computer program developed for the prediction of propeller-nacelle aerodynamic performance reported in, An Analysis for High Speed Propeller-Nacelle Aerodynamic Performance Prediction: Volume 1 -- Theory and Application, is presented. The manual describes the computer program mode of operation requirements, input structure, input data requirements and the program output. In addition, it provides the user with documentation of the internal program structure and the software used in the computer program as it relates to the theory presented in Volume 1. Sample input data setups are provided along with selected printout of the program output for one of the sample setups.

Cell-specific prediction and application of drug-induced gene expression profiles.

PubMed

Hodos, Rachel; Zhang, Ping; Lee, Hao-Chih; Duan, Qiaonan; Wang, Zichen; Clark, Neil R; Ma'ayan, Avi; Wang, Fei; Kidd, Brian; Hu, Jianying; Sontag, David; Dudley, Joel

2018-01-01

Gene expression profiling of in vitro drug perturbations is useful for many biomedical discovery applications including drug repurposing and elucidation of drug mechanisms. However, limited data availability across cell types has hindered our capacity to leverage or explore the cell-specificity of these perturbations. While recent efforts have generated a large number of drug perturbation profiles across a variety of human cell types, many gaps remain in this combinatorial drug-cell space. Hence, we asked whether it is possible to fill these gaps by predicting cell-specific drug perturbation profiles using available expression data from related conditions--i.e. from other drugs and cell types. We developed a computational framework that first arranges existing profiles into a three-dimensional array (or tensor) indexed by drugs, genes, and cell types, and then uses either local (nearest-neighbors) or global (tensor completion) information to predict unmeasured profiles. We evaluate prediction accuracy using a variety of metrics, and find that the two methods have complementary performance, each superior in different regions in the drug-cell space. Predictions achieve correlations of 0.68 with true values, and maintain accurate differentially expressed genes (AUC 0.81). Finally, we demonstrate that the predicted profiles add value for making downstream associations with drug targets and therapeutic classes.

Cell-specific prediction and application of drug-induced gene expression profiles

PubMed Central

Hodos, Rachel; Zhang, Ping; Lee, Hao-Chih; Duan, Qiaonan; Wang, Zichen; Clark, Neil R.; Ma'ayan, Avi; Wang, Fei; Kidd, Brian; Hu, Jianying; Sontag, David

2017-01-01

Gene expression profiling of in vitro drug perturbations is useful for many biomedical discovery applications including drug repurposing and elucidation of drug mechanisms. However, limited data availability across cell types has hindered our capacity to leverage or explore the cell-specificity of these perturbations. While recent efforts have generated a large number of drug perturbation profiles across a variety of human cell types, many gaps remain in this combinatorial drug-cell space. Hence, we asked whether it is possible to fill these gaps by predicting cell-specific drug perturbation profiles using available expression data from related conditions--i.e. from other drugs and cell types. We developed a computational framework that first arranges existing profiles into a three-dimensional array (or tensor) indexed by drugs, genes, and cell types, and then uses either local (nearest-neighbors) or global (tensor completion) information to predict unmeasured profiles. We evaluate prediction accuracy using a variety of metrics, and find that the two methods have complementary performance, each superior in different regions in the drug-cell space. Predictions achieve correlations of 0.68 with true values, and maintain accurate differentially expressed genes (AUC 0.81). Finally, we demonstrate that the predicted profiles add value for making downstream associations with drug targets and therapeutic classes. PMID:29218867

Advanced error-prediction LDPC with temperature compensation for highly reliable SSDs

NASA Astrophysics Data System (ADS)

Tokutomi, Tsukasa; Tanakamaru, Shuhei; Iwasaki, Tomoko Ogura; Takeuchi, Ken

2015-09-01

To improve the reliability of NAND Flash memory based solid-state drives (SSDs), error-prediction LDPC (EP-LDPC) has been proposed for multi-level-cell (MLC) NAND Flash memory (Tanakamaru et al., 2012, 2013), which is effective for long retention times. However, EP-LDPC is not as effective for triple-level cell (TLC) NAND Flash memory, because TLC NAND Flash has higher error rates and is more sensitive to program-disturb error. Therefore, advanced error-prediction LDPC (AEP-LDPC) has been proposed for TLC NAND Flash memory (Tokutomi et al., 2014). AEP-LDPC can correct errors more accurately by precisely describing the error phenomena. In this paper, the effects of AEP-LDPC are investigated in a 2×nm TLC NAND Flash memory with temperature characterization. Compared with LDPC-with-BER-only, the SSD's data-retention time is increased by 3.4× and 9.5× at room-temperature (RT) and 85 °C, respectively. Similarly, the acceptable BER is increased by 1.8× and 2.3×, respectively. Moreover, AEP-LDPC can correct errors with pre-determined tables made at higher temperatures to shorten the measurement time before shipping. Furthermore, it is found that one table can cover behavior over a range of temperatures in AEP-LDPC. As a result, the total table size can be reduced to 777 kBytes, which makes this approach more practical.

A minimally invasive methodology based on morphometric parameters for day 2 embryo quality assessment.

PubMed

Molina, Inmaculada; Lázaro-Ibáñez, Elisa; Pertusa, Jose; Debón, Ana; Martínez-Sanchís, Juan Vicente; Pellicer, Antonio

2014-10-01

The risk of multiple pregnancy to maternal-fetal health can be minimized by reducing the number of embryos transferred. New tools for selecting embryos with the highest implantation potential should be developed. The aim of this study was to evaluate the ability of morphological and morphometric variables to predict implantation by analysing images of embryos. This was a retrospective study of 135 embryo photographs from 112 IVF-ICSI cycles carried out between January and March 2011. The embryos were photographed immediately before transfer using Cronus 3 software. Their images were analysed using the public program ImageJ. Significant effects (P < 0.05), and higher discriminant power to predict implantation were observed for the morphometric embryo variables compared with morphological ones. The features for successfully implanted embryos were as follows: four cells on day 2 of development; all blastomeres with circular shape (roundness factor greater than 0.9), an average zona pellucida thickness of 13 µm and an average of 17695.1 µm² for the embryo area. Embryo size, which is described by its area and the average roundness factor for each cell, provides two objective variables to consider when predicting implantation. This approach should be further investigated for its potential ability to improve embryo scoring. Copyright © 2014 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

TP53, STK11 and EGFR Mutations Predict Tumor Immune Profile and the Response to anti-PD-1 in Lung Adenocarcinoma.

PubMed

Biton, Jerome; Mansuet-Lupo, Audrey; Pécuchet, Nicolas; Alifano, Marco; Ouakrim, Hanane; Arrondeau, Jennifer; Boudou-Rouquette, Pascaline; Goldwasser, Francois; Leroy, Karen; Goc, Jeremy; Wislez, Marie; Germain, Claire; Laurent-Puig, Pierre; Dieu-Nosjean, Marie-Caroline; Cremer, Isabelle; Herbst, Ronald; Blons, Hélène F; Damotte, Diane

2018-05-15

By unlocking anti-tumor immunity, antibodies targeting programmed cell death 1 (PD-1) exhibit impressive clinical results in non-small cell lung cancer, underlining the strong interactions between tumor and immune cells. However, factors that can robustly predict long-lasting responses are still needed. We performed in depth immune profiling of lung adenocarcinoma using an integrative analysis based on immunohistochemistry, flow-cytometry and transcriptomic data. Tumor mutational status was investigated using next-generation sequencing. The response to PD-1 blockers was analyzed from a prospective cohort according to tumor mutational profiles and to PD-L1 expression, and a public clinical database was used to validate the results obtained. We showed that distinct combinations of STK11 , EGFR and TP53 mutations, were major determinants of the tumor immune profile (TIP) and of the expression of PD-L1 by malignant cells. Indeed, the presence of TP53 mutations without co-occurring STK11 or EGFR alterations ( TP53 -mut/ STK11 - EGFR -WT), independently of KRAS mutations, identified the group of tumors with the highest CD8 T cell density and PD-L1 expression. In this tumor subtype, pathways related to T cell chemotaxis, immune cell cytotoxicity, and antigen processing were up-regulated. Finally, a prolonged progression-free survival (PFS: HR=0.32; 95% CI, 0.16-0.63, p <0.001) was observed in anti-PD-1 treated patients harboring TP53 -mut/ STK11 - EGFR -WT tumors. This clinical benefit was even more remarkable in patients with associated strong PD-L1 expression. Our study reveals that different combinations of TP53 , EGFR and STK11 mutations , together with PD-L1 expression by tumor cells, represent robust parameters to identify best responders to PD-1 blockade. Copyright ©2018, American Association for Cancer Research.

SRB-3D Solid Rocket Booster performance prediction program. Volume 3: Programmer's manual

NASA Technical Reports Server (NTRS)

Winkler, J. C.

1976-01-01

The programmer's manual for the Modified Solid Rocket Booster Performance Prediction Program (SRB-3D) describes the major control routines of SRB-3D, followed by a super index listing of the program and a cross-reference of the program variables.

Using a combined computational-experimental approach to predict antibody-specific B cell epitopes.

PubMed

Sela-Culang, Inbal; Benhnia, Mohammed Rafii-El-Idrissi; Matho, Michael H; Kaever, Thomas; Maybeno, Matt; Schlossman, Andrew; Nimrod, Guy; Li, Sheng; Xiang, Yan; Zajonc, Dirk; Crotty, Shane; Ofran, Yanay; Peters, Bjoern

2014-04-08

Antibody epitope mapping is crucial for understanding B cell-mediated immunity and required for characterizing therapeutic antibodies. In contrast to T cell epitope mapping, no computational tools are in widespread use for prediction of B cell epitopes. Here, we show that, utilizing the sequence of an antibody, it is possible to identify discontinuous epitopes on its cognate antigen. The predictions are based on residue-pairing preferences and other interface characteristics. We combined these antibody-specific predictions with results of cross-blocking experiments that identify groups of antibodies with overlapping epitopes to improve the predictions. We validate the high performance of this approach by mapping the epitopes of a set of antibodies against the previously uncharacterized D8 antigen, using complementary techniques to reduce method-specific biases (X-ray crystallography, peptide ELISA, deuterium exchange, and site-directed mutagenesis). These results suggest that antibody-specific computational predictions and simple cross-blocking experiments allow for accurate prediction of residues in conformational B cell epitopes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Genital infections and syndromic diagnosis among HIV-infected women in HIV care programs in Kenya

PubMed Central

Djomand, Gaston; Gao, Hongjiang; Singa, Benson; Hornston, Sureyya; Bennett, Eddas; Odek, James; McClelland, R. Scott; John-Stewart, Grace; Bock, Naomi

2015-01-01

Background Control of genital infections remains challenging in most regions. Despite advocacy by the World Health Organization (WHO) for syndromic case management, there are limited data on the syndromic approach, especially in HIV care settings. This study compared the syndromic approach against laboratory diagnosis among women in HIV care in Kenya. Methods A mobile team visited 39 large HIV care programs in Kenya and enrolled participants using population-proportionate sampling. Participants provided behavioral and clinical data with genital and blood specimens for lab testing. Results Among 1,063 women, 68.4% had been on antiretroviral therapy >1 year; 58.9% were using cotrimoxazole prophylaxis; 51 % had CD4+T-lymphocytes < 350 cells/mL. Most women (63.1%) reported at least one genital symptom. Clinical signs were found in 63% of women; and 30.8% had an etiological diagnosis. Bacterial vaginosis (17.4%), vaginal candidiasis (10.6%) and trichomoniasis (10.5%) were the most common diagnoses. Using laboratory diagnoses as gold standard, sensitivity and positive predictive value of the syndromic diagnosis for vaginal discharge were 47.6% and 52.7%, respectively, indicating a substantial amount of overtreatment. A systematic physical examination increased by 9.3% the positive predictive value for genital ulcer disease. Conclusions Women attending HIV care programs in Kenya have high rates of vaginal infections. Syndromic diagnosis was a poor predictor of those infections. PMID:25614522

Organizational Changes to Thyroid Regulation in Alligator mississippiensis: Evidence for Predictive Adaptive Responses

PubMed Central

Boggs, Ashley S. P.; Lowers, Russell H.; Cloy-McCoy, Jessica A.; Guillette, Louis J.

2013-01-01

During embryonic development, organisms are sensitive to changes in thyroid hormone signaling which can reset the hypothalamic-pituitary-thyroid axis. It has been hypothesized that this developmental programming is a ‘predictive adaptive response’, a physiological adjustment in accordance with the embryonic environment that will best aid an individual's survival in a similar postnatal environment. When the embryonic environment is a poor predictor of the external environment, the developmental changes are no longer adaptive and can result in disease states. We predicted that endocrine disrupting chemicals (EDCs) and environmentally-based iodide imbalance could lead to developmental changes to the thyroid axis. To explore whether iodide or EDCs could alter developmental programming, we collected American alligator eggs from an estuarine environment with high iodide availability and elevated thyroid-specific EDCs, a freshwater environment contaminated with elevated agriculturally derived EDCs, and a reference freshwater environment. We then incubated them under identical conditions. We examined plasma thyroxine and triiodothyronine concentrations, thyroid gland histology, plasma inorganic iodide, and somatic growth at one week (before external nutrition) and ten months after hatching (on identical diets). Neonates from the estuarine environment were thyrotoxic, expressing follicular cell hyperplasia (p = 0.01) and elevated plasma triiodothyronine concentrations (p = 0.0006) closely tied to plasma iodide concentrations (p = 0.003). Neonates from the freshwater contaminated site were hypothyroid, expressing thyroid follicular cell hyperplasia (p = 0.01) and depressed plasma thyroxine concentrations (p = 0.008). Following a ten month growth period under identical conditions, thyroid histology (hyperplasia p = 0.04; colloid depletion p = 0.01) and somatic growth (body mass p<0.0001; length p = 0.02) remained altered among the contaminated sites. This work supports the hypothesis that embryonic EDC exposure or iodide imbalance could induce adult metabolic disease states, thereby stressing the need to consider the multiple environmental variables present during development. PMID:23383213

Basal CD34+ Cell Count Predicts Peripheral Blood Stem Cell Mobilization in Healthy Donors after Administration of Granulocyte Colony-Stimulating Factor: A Longitudinal, Prospective, Observational, Single-Center, Cohort Study.

PubMed

Martino, Massimo; Gori, Mercedes; Pitino, Annalisa; Gentile, Massimo; Dattola, Antonia; Pontari, Antonella; Vigna, Ernesto; Moscato, Tiziana; Recchia, Anna Grazia; Barilla', Santina; Tripepi, Giovanni; Morabito, Fortunato

2017-07-01

A longitudinal, prospective, observational, single-center, cohort study on healthy donors (HDs) was designed to identify predictors of CD34 + cells on day 5 with emphasis on the predictive value of the basal CD34 + cell count. As potential predictors of mobilization, age, sex, body weight, height, blood volume as well as white blood cell count, peripheral blood (PB) mononuclear cells, platelet count, hematocrit, and hemoglobin levels were considered. Two different evaluations of CD34 + cell counts were determined for each donor: baseline (before granulocyte colony-stimulating factor [G-CSF] administration) and in PB after G-CSF administration on the morning of the fifth day (day 5). A total of 128 consecutive HDs (66 males) with a median age of 43 years were enrolled. CD34 + levels on day 5 displayed a non-normal distribution, with a median value of 75.5 cells/µL. To account for the non-normal distribution of the dependent variable, a quantile regression analysis to predict CD34 + on day 5 using the baseline value of CD34 + as the key predictor was performed. On crude analysis, a baseline value of CD34 + ranging from .5 cells/µL to 1 cells/µL predicts a median value of 50 cells/µL on day 5; a value of 2 cells/µL predicts a median value of 70.7 cells/µL; a value of 3 cells/µL to 4 cells/µL predicts a median value of 91.3 cells/µL, and a value ≥ 5 predicts a median value of 112 cells/µL. In conclusion, the baseline PB CD34 + cell count correlates with the effectiveness of allogeneic PB stem cell mobilization and could be useful to plan the collection. Copyright © 2017 The American Society for Blood and Marrow Transplantation. Published by Elsevier Inc. All rights reserved.

PD-L1 (CD274) promoter methylation predicts survival in colorectal cancer patients.

PubMed

Goltz, Diane; Gevensleben, Heidrun; Dietrich, Jörn; Dietrich, Dimo

2017-01-01

This study evaluates promoter methylation of the programmed cell death ligand 1 (PD-L1) as a biomarker in a cohort of 383 colorectal cancer patients. PD-L1 methylation (m PD-L1 ) was inversely correlated with PD-L1 mRNA expression ( p = 0.001) and was associated with significantly shorter overall survival (OS, p = 0.003) and recurrence-free survival (RFS, p < 0.001). In age-stratified multivariate Cox proportional hazards analyses including sex, tumor, nodal, distant metastasis categories, microsatellite instability (MSI)-status, and PD-L1 mRNA, m PD-L1 is classified as an independent prognostic factor (OS: p = 0.030; RFS: p < 0.001). Further studies are needed to evaluate PD-L1 methylation as a biomarker for response prediction of immunotherapies targeting the PD-1/PD-L1 axis.

Independent Predictors of Prognosis Based on Oral Cavity Squamous Cell Carcinoma Surgical Margins.

PubMed

Buchakjian, Marisa R; Ginader, Timothy; Tasche, Kendall K; Pagedar, Nitin A; Smith, Brian J; Sperry, Steven M

2018-05-01

Objective To conduct a multivariate analysis of a large cohort of oral cavity squamous cell carcinoma (OCSCC) cases for independent predictors of local recurrence (LR) and overall survival (OS), with emphasis on the relationship between (1) prognosis and (2) main specimen permanent margins and intraoperative tumor bed frozen margins. Study Design Retrospective cohort study. Setting Tertiary academic head and neck cancer program. Subjects and Methods This study included 426 patients treated with OCSCC resection between 2005 and 2014 at University of Iowa Hospitals and Clinics. Patients underwent excision of OCSCC with intraoperative tumor bed frozen margin sampling and main specimen permanent margin assessment. Multivariate analysis of the data set to predict LR and OS was performed. Results Independent predictors of LR included nodal involvement, histologic grade, and main specimen permanent margin status. Specifically, the presence of a positive margin (odds ratio, 6.21; 95% CI, 3.3-11.9) or <1-mm/carcinoma in situ margin (odds ratio, 2.41; 95% CI, 1.19-4.87) on the main specimen was an independent predictor of LR, whereas intraoperative tumor bed margins were not predictive of LR on multivariate analysis. Similarly, independent predictors of OS on multivariate analysis included nodal involvement, extracapsular extension, and a positive main specimen margin. Tumor bed margins did not independently predict OS. Conclusion The main specimen margin is a strong independent predictor of LR and OS on multivariate analysis. Intraoperative tumor bed frozen margins do not independently predict prognosis. We conclude that emphasis should be placed on evaluating the main specimen margins when estimating prognosis after OCSCC resection.

Predictive Bcl-2 Family Binding Models Rooted in Experiment or Structure

PubMed Central

DeBartolo, Joe; Dutta, Sanjib; Reich, Lothar; Keating, Amy E.

2013-01-01

Proteins of the Bcl-2 family either enhance or suppress programmed cell death and are centrally involved in cancer development and resistance to chemotherapy. BH3 (Bcl-2 homology 3)-only Bcl-2 proteins promote cell death by docking an α-helix into a hydrophobic groove on the surface of one or more of five pro-survival Bcl-2 receptor proteins. There is high structural homology within the pro-death and pro-survival families, yet a high degree of interaction specificity is nevertheless encoded, posing an interesting and important molecular recognition problem. Understanding protein features that dictate Bcl-2 interaction specificity is critical for designing peptide-based cancer therapeutics and diagnostics. In this study, we present peptide SPOT arrays and deep sequencing data from yeast display screening experiments that significantly expand the BH3 sequence space that has been experimentally tested for interaction with five human anti-apoptotic receptors. These data provide rich information about the determinants of Bcl-2 family specificity. To interpret and use the information, we constructed two simple data-based models that can predict affinity and specificity when evaluated on independent data sets within a limited sequence space. We also constructed a novel structure-based statistical potential, called STATIUM, which is remarkably good at predicting Bcl-2 affinity and specificity, especially considering it is not trained on experimental data. We compare the performance of our three models to each other and to alternative structure-based methods and discuss how such tools can guide prediction and design of new Bcl-2 family complexes. PMID:22617328

Genetic Programming as Alternative for Predicting Development Effort of Individual Software Projects

PubMed Central

Chavoya, Arturo; Lopez-Martin, Cuauhtemoc; Andalon-Garcia, Irma R.; Meda-Campaña, M. E.

2012-01-01

Statistical and genetic programming techniques have been used to predict the software development effort of large software projects. In this paper, a genetic programming model was used for predicting the effort required in individually developed projects. Accuracy obtained from a genetic programming model was compared against one generated from the application of a statistical regression model. A sample of 219 projects developed by 71 practitioners was used for generating the two models, whereas another sample of 130 projects developed by 38 practitioners was used for validating them. The models used two kinds of lines of code as well as programming language experience as independent variables. Accuracy results from the model obtained with genetic programming suggest that it could be used to predict the software development effort of individual projects when these projects have been developed in a disciplined manner within a development-controlled environment. PMID:23226305

A computer program for the prediction of near field noise of aircraft in cruising flight: User's guide

NASA Technical Reports Server (NTRS)

Tibbetts, J. G.

1980-01-01

Detailed instructions for using the near field cruise noise prediction program, a program listing, and a sample case with output are presented. The total noise for free field lossless conditions at selected observer locations is obtained by summing the contributions from up to nine acoustic sources. These noise sources, selected at the user's option, include the fan/compressor, turbine, core (combustion), jet, shock, and airframe (trailing edge and turbulent boundary layers). The effects of acoustic suppression materials such as engine inlet treatment may also be included in the noise prediction. The program is available for use on the NASA/Langley Research Center CDC computer. Comparisons of the program predictions with measured data are also given, and some possible reasons for their lack of agreement presented.

Pioneer factors, genetic competence, and inductive signaling: programming liver and pancreas progenitors from the endoderm.

PubMed

Zaret, K S; Watts, J; Xu, J; Wandzioch, E; Smale, S T; Sekiya, T

2008-01-01

The endoderm is a multipotent progenitor cell population in the embryo that gives rise to the liver, pancreas, and other cell types and provides paradigms for understanding cell-type specification. Studies of isolated embryo tissue cells and genetic approaches in vivo have defined fibroblast growth factor/mitogen-activated protein kinase (FGF/MAPK) and bone morphogenetic protein (BMP) signaling pathways that induce liver and pancreatic fates in the endoderm. In undifferentiated endoderm cells, the FoxA and GATA transcription factors are among the first to engage silent genes, helping to endow competence for cell-type specification. FoxA proteins can bind their target sites in highly compacted chromatin and open up the local region for other factors to bind; hence, they have been termed "pioneer factors." We recently found that FoxA proteins remain bound to chromatin in mitosis, as an epigenetic mark. In embryonic stem cells, which lack FoxA, FoxA target sites can be occupied by FoxD3, which in turn helps to maintain a local demethylation of chromatin. By these means, a cascade of Fox factors helps to endow progenitor cells with the competence to activate genes in response to tissue-inductive signals. Understanding such epigenetic mechanisms for transcriptional competence coupled with knowledge of the relevant signals for cell-type specification should greatly facilitate efforts to predictably differentiate stem cells to liver and pancreatic fates.

Performance analysis of a potassium-base AMTEC cell

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

Huang, C.; Hendricks, T.J.; Hunt, T.K.

1998-07-01

Sodium-BASE Alkali-Metal-Thermal-to-Electric-Conversion (AMTEC) cells have been receiving increased attention and funding from the Department of Energy, NASA and the United States Air Force. Recently, sodium-BASE (Na-BASE) AMTEC cells were selected for the Advanced Radioisotope Power System (ARPS) program for the next generation of deep-space missions and spacecraft. Potassium-BASE (K-BASE) AMTEC cells have not received as much attention to date, even though the vapor pressure of potassium is higher than that of sodium at the same temperature. So that, K-BASE AMTEC cells with potentially higher open circuit voltage and higher power output than Na-BASE AMTEC cells are possible. Because the surfacemore » tension of potassium is about half of the surface tension of sodium at the same temperature, the artery and evaporator design in a potassium AMTEC cell has much more challenging pore size requirements than designs using sodium. This paper uses a flexible thermal/fluid/electrical model to predict the performance of a K-BASE AMTEC cell. Pore sizes in the artery of K-BASE AMTEC cells must be smaller by an order of magnitude than in Na-BASE AMTEC cells. The performance of a K-BASE AMTEC cell was higher than a Na-BASE AMTEC cell at low voltages/high currents. K-BASE AMTEC cells also have the potential of much better electrode performance, thereby creating another avenue for potentially better performance in K-BASE AMTEC cells.« less

Comparison of two computer programs by predicting turbulent mixing of helium in a ducted supersonic airstream

NASA Technical Reports Server (NTRS)

Pan, Y. S.; Drummond, J. P.; Mcclinton, C. R.

1978-01-01

Two parabolic flow computer programs, SHIP (a finite-difference program) and COMOC (a finite-element program), are used for predicting three-dimensional turbulent reacting flow fields in supersonic combustors. The theoretical foundation of the two computer programs are described, and then the programs are applied to a three-dimensional turbulent mixing experiment. The cold (nonreacting) flow experiment was performed to study the mixing of helium jets with a supersonic airstream in a rectangular duct. Surveys of the flow field at an upstream were used as the initial data by programs; surveys at a downstream station provided comparison to assess program accuracy. Both computer programs predicted the experimental results and data trends reasonably well. However, the comparison between the computations from the two programs indicated that SHIP was more accurate in computation and more efficient in both computer storage and computing time than COMOC.

Computer prediction of three-dimensional potential flow fields in which aircraft propellers operate: Computer program description and users manual

NASA Technical Reports Server (NTRS)

Jumper, S. J.

1979-01-01

A method was developed for predicting the potential flow velocity field at the plane of a propeller operating under the influence of a wing-fuselage-cowl or nacelle combination. A computer program was written which predicts the three dimensional potential flow field. The contents of the program, its input data, and its output results are described.

Myeloid cell leukemia-1 is an important apoptotic survival factor in triple-negative breast cancer.

PubMed

Goodwin, C M; Rossanese, O W; Olejniczak, E T; Fesik, S W

2015-12-01

Breast cancer is the second-most frequently diagnosed malignancy in US women. The triple-negative breast cancer (TNBC) subtype, which lacks expression of the estrogen receptor, progesterone receptor and human epidermal growth factor receptor-2, afflicts 15% of patients and is refractory to current targeted therapies. Like many cancers, TNBC cells often deregulate programmed cell death by upregulating anti-apoptotic proteins of the B-cell CLL/lymphoma 2 (Bcl-2) family. One family member, myeloid cell leukemia-1 (Mcl-1), is commonly amplified in TNBC and correlates with a poor clinical prognosis. Here we show the effect of silencing Mcl-1 and Bcl-2-like protein 1 isoform 1 (Bcl-xL) expression on viability in a panel of seventeen TNBC cell lines. Cell death was observed in a subset upon Mcl-1 knockdown. In contrast, Bcl-xL knockdown only modestly reduced viability, indicating that Mcl-1 is a more important survival factor. However, dual silencing of both Mcl-1 and Bcl-xL reduced viability in most cell lines tested. These proliferation results were recapitulated by BH3 profiling experiments. Treatment with a Bcl-xL and Bcl-2 peptide had only a moderate effect on any of the TNBC cell lines, however, co-dosing an Mcl-1-selective peptide with a peptide that inhibits Bcl-xL and Bcl-2 was effective in each line tested. Similarly, the selective Bcl-xL inhibitor WEHI-539 was only weakly cytotoxic across the panel, but sensitization by Mcl-1 knockdown markedly improved its EC50. ABT-199, which selectively inhibits Bcl-2, did not synergize with Mcl-1 knockdown, indicating the relatively low importance of Bcl-2 in these lines. Mcl-1 sensitivity is not predicted by mRNA or protein levels of a single Bcl-2 family member, except for only a weak correlation for Bak and Bax protein expression. However, a more comprehensive index composed of Mcl-1, Bcl-xL, Bim, Bak and Noxa protein or mRNA expression correlates well with Mcl-1 sensitivity in TNBC and can also predict Mcl-1 dependency in non-small cell lung cancer cell lines.

Genomic signal processing: from matrix algebra to genetic networks.

PubMed

Alter, Orly

2007-01-01

DNA microarrays make it possible, for the first time, to record the complete genomic signals that guide the progression of cellular processes. Future discovery in biology and medicine will come from the mathematical modeling of these data, which hold the key to fundamental understanding of life on the molecular level, as well as answers to questions regarding diagnosis, treatment, and drug development. This chapter reviews the first data-driven models that were created from these genome-scale data, through adaptations and generalizations of mathematical frameworks from matrix algebra that have proven successful in describing the physical world, in such diverse areas as mechanics and perception: the singular value decomposition model, the generalized singular value decomposition model comparative model, and the pseudoinverse projection integrative model. These models provide mathematical descriptions of the genetic networks that generate and sense the measured data, where the mathematical variables and operations represent biological reality. The variables, patterns uncovered in the data, correlate with activities of cellular elements such as regulators or transcription factors that drive the measured signals and cellular states where these elements are active. The operations, such as data reconstruction, rotation, and classification in subspaces of selected patterns, simulate experimental observation of only the cellular programs that these patterns represent. These models are illustrated in the analyses of RNA expression data from yeast and human during their cell cycle programs and DNA-binding data from yeast cell cycle transcription factors and replication initiation proteins. Two alternative pictures of RNA expression oscillations during the cell cycle that emerge from these analyses, which parallel well-known designs of physical oscillators, convey the capacity of the models to elucidate the design principles of cellular systems, as well as guide the design of synthetic ones. In these analyses, the power of the models to predict previously unknown biological principles is demonstrated with a prediction of a novel mechanism of regulation that correlates DNA replication initiation with cell cycle-regulated RNA transcription in yeast. These models may become the foundation of a future in which biological systems are modeled as physical systems are today.

PDCD1 (PD-1) promoter methylation predicts outcome in head and neck squamous cell carcinoma patients

PubMed Central

Dietrich, Joern; Schroeck, Friederike; de Vos, Luka; Droege, Freya; Kristiansen, Glen; Schroeck, Andreas; Landsberg, Jennifer; Bootz, Friedrich; Dietrich, Dimo

2017-01-01

Background Biomarkers that facilitate the prediction of disease recurrence in head and neck squamous cell carcinoma (HNSCC) may enable physicians to personalize treatment. In the current study, DNA promoter methylation of programmed cell death 1 (PDCD1, PD-1) was evaluated as a prognostic biomarker in HNSCC patients. Results High PDCD1 methylation (mPDCD1) was associated with a significantly shorter overall survival after surgical resection in both the discovery (HR = 2.24 [95%CI: 1.08–4.64], p = 0.029) and the validation cohort (HR = 1.54 [95%CI: 1.08–2.21], p = 0.017). In multivariate Cox proportional hazards analysis, PDCD1 methylation remained a significant prognostic factor for HNSCC (HR = 2.14 [95%CI: 1.19–3.84], p = 0.011). Further, mPDCD1 was strongly associated with the human papilloma virus (HPV) status. Materials and Methods mPDCD1 was assessed retrospectively in a discovery cohort of 120 HNSCC patients treated at the University Hospital of Bonn and a validation cohort of 527 HNSCC cases analyzed by The Cancer Genome Atlas Research Network. Conclusions PDCD1 methylation might aid the identification of HNSCC patients potentially benefitting from a radical or alternative treatment, particularly in the context of immunotherapies targeting PD-1/PD-L1. PMID:28487502

Characterization of the space shuttle reaction control system engine

NASA Technical Reports Server (NTRS)

Wilson, M. S.; Stechman, R. C.; Edelman, R. B.; Fortune, O. F.; Economos, C.

1972-01-01

A computer program was developed and written in FORTRAN 5 which predicts the transient and steady state performance and heat transfer characteristics of a pulsing GO2/GH2 rocket engine. This program predicts the dynamic flow and ignition characteristics which, when combined in a quasi-steady state manner with the combustion and mixing analysis program, will provide the thrust and specific impulse of the engine as a function of time. The program also predicts the transient and steady state heat transfer characteristics of the engine using various cooling concepts. The computer program, test case, and documentation are presented. The program is applicable to any system capable of utilizing the FORTRAN 4 or FORTRAN 5 language.

POPISK: T-cell reactivity prediction using support vector machines and string kernels

PubMed Central

2011-01-01

Background Accurate prediction of peptide immunogenicity and characterization of relation between peptide sequences and peptide immunogenicity will be greatly helpful for vaccine designs and understanding of the immune system. In contrast to the prediction of antigen processing and presentation pathway, the prediction of subsequent T-cell reactivity is a much harder topic. Previous studies of identifying T-cell receptor (TCR) recognition positions were based on small-scale analyses using only a few peptides and concluded different recognition positions such as positions 4, 6 and 8 of peptides with length 9. Large-scale analyses are necessary to better characterize the effect of peptide sequence variations on T-cell reactivity and design predictors of a peptide's T-cell reactivity (and thus immunogenicity). The identification and characterization of important positions influencing T-cell reactivity will provide insights into the underlying mechanism of immunogenicity. Results This work establishes a large dataset by collecting immunogenicity data from three major immunology databases. In order to consider the effect of MHC restriction, peptides are classified by their associated MHC alleles. Subsequently, a computational method (named POPISK) using support vector machine with a weighted degree string kernel is proposed to predict T-cell reactivity and identify important recognition positions. POPISK yields a mean 10-fold cross-validation accuracy of 68% in predicting T-cell reactivity of HLA-A2-binding peptides. POPISK is capable of predicting immunogenicity with scores that can also correctly predict the change in T-cell reactivity related to point mutations in epitopes reported in previous studies using crystal structures. Thorough analyses of the prediction results identify the important positions 4, 6, 8 and 9, and yield insights into the molecular basis for TCR recognition. Finally, we relate this finding to physicochemical properties and structural features of the MHC-peptide-TCR interaction. Conclusions A computational method POPISK is proposed to predict immunogenicity with scores which are useful for predicting immunogenicity changes made by single-residue modifications. The web server of POPISK is freely available at http://iclab.life.nctu.edu.tw/POPISK. PMID:22085524

POPISK: T-cell reactivity prediction using support vector machines and string kernels.

PubMed

Tung, Chun-Wei; Ziehm, Matthias; Kämper, Andreas; Kohlbacher, Oliver; Ho, Shinn-Ying

2011-11-15

Accurate prediction of peptide immunogenicity and characterization of relation between peptide sequences and peptide immunogenicity will be greatly helpful for vaccine designs and understanding of the immune system. In contrast to the prediction of antigen processing and presentation pathway, the prediction of subsequent T-cell reactivity is a much harder topic. Previous studies of identifying T-cell receptor (TCR) recognition positions were based on small-scale analyses using only a few peptides and concluded different recognition positions such as positions 4, 6 and 8 of peptides with length 9. Large-scale analyses are necessary to better characterize the effect of peptide sequence variations on T-cell reactivity and design predictors of a peptide's T-cell reactivity (and thus immunogenicity). The identification and characterization of important positions influencing T-cell reactivity will provide insights into the underlying mechanism of immunogenicity. This work establishes a large dataset by collecting immunogenicity data from three major immunology databases. In order to consider the effect of MHC restriction, peptides are classified by their associated MHC alleles. Subsequently, a computational method (named POPISK) using support vector machine with a weighted degree string kernel is proposed to predict T-cell reactivity and identify important recognition positions. POPISK yields a mean 10-fold cross-validation accuracy of 68% in predicting T-cell reactivity of HLA-A2-binding peptides. POPISK is capable of predicting immunogenicity with scores that can also correctly predict the change in T-cell reactivity related to point mutations in epitopes reported in previous studies using crystal structures. Thorough analyses of the prediction results identify the important positions 4, 6, 8 and 9, and yield insights into the molecular basis for TCR recognition. Finally, we relate this finding to physicochemical properties and structural features of the MHC-peptide-TCR interaction. A computational method POPISK is proposed to predict immunogenicity with scores which are useful for predicting immunogenicity changes made by single-residue modifications. The web server of POPISK is freely available at http://iclab.life.nctu.edu.tw/POPISK.

Role of Protein Biomarkers in the Detection of High-Grade Disease in Cervical Cancer Screening Programs

PubMed Central

Brown, Charlotte A.; Bogers, Johnannes; Sahebali, Shaira; Depuydt, Christophe E.; De Prins, Frans; Malinowski, Douglas P.

2012-01-01

Since the Pap test was introduced in the 1940s, there has been an approximately 70% reduction in the incidence of squamous cell cervical cancers in many developed countries by the application of organized and opportunistic screening programs. The efficacy of the Pap test, however, is hampered by high interobserver variability and high false-negative and false-positive rates. The use of biomarkers has demonstrated the ability to overcome these issues, leading to improved positive predictive value of cervical screening results. In addition, the introduction of HPV primary screening programs will necessitate the use of a follow-up test with high specificity to triage the high number of HPV-positive tests. This paper will focus on protein biomarkers currently available for use in cervical cancer screening, which appear to improve the detection of women at greatest risk for developing cervical cancer, including Ki-67, p16INK4a, BD ProEx C, and Cytoactiv HPV L1. PMID:22481919

The status of lightweight photovoltaic space array technology based on amorphous silicon solar cells

NASA Astrophysics Data System (ADS)

Hanak, J. J.; Kaschmitter, J. L.

1991-05-01

An ultralight, flexible photovoltaic (PV) array of amorphous silicon (a-Si) has been identified as a potential low-cost power source for small satellites. We have conducted a survey of the status of the a-Si PV array technology with respect to present and future performance, availability, cost and risks. For existing, experimental array 'blankets' made of commercial cell material, utilizing metal foil substrates, the BOL performance at AM0 and 35 C includes total power up to 200 W, power per area of 64 W/sq m and power per weight of 258 W/kg. Doubling of power per weight occurs when polyimide substrates are used. Estimated EOL power output after 10 years in a nominal low-earth orbit would be 80 percent of BOL, the degradation being due to largely light-induced effects (minus 10 to minus 15 percent) and in part (minus 5 percent) to space radiation. Predictions for the year 1995 for flexible PV arrays, made on the basis of published results for rigid a-Si modules, indicate EOL power output per area and per weight of 105 W/sq m and 400 W/kg, respectively, while predictions for the late 1990s based on existing US national PV program goals indicate EOL values of 157 W/sq m and 600 W/kg. cost estimates by vendors for 200 W ultralight arrays in volume of over 1000 units range from $100/watt to $125/watt. Identified risks include the lack of flexible, space compatible encapsulant, the lack of space qualification effort, recent partial or full acquisitions of US manufacturers of a-Si cells by foreign firms, and the absence of a national commitment for a long-range development program toward developing of this important power source for space. One new US developer has emerged as a future potential supplier of a-Si PV devices on thin, polyimide substrates.

Computer program to predict noise of general aviation aircraft: User's guide

NASA Technical Reports Server (NTRS)

Mitchell, J. A.; Barton, C. K.; Kisner, L. S.; Lyon, C. A.

1982-01-01

Program NOISE predicts General Aviation Aircraft far-field noise levels at FAA FAR Part 36 certification conditions. It will also predict near-field and cabin noise levels for turboprop aircraft and static engine component far-field noise levels.

Mycobacterium leprae virulence-associated peptides are indicators of exposure to M. leprae in Brazil, Ethiopia and Nepal.

PubMed

Bobosha, Kidist; Tang, Sheila Tuyet; van der Ploeg-van Schip, Jolien J; Bekele, Yonas; Martins, Marcia V S B; Lund, Ole; Franken, Kees L M C; Khadge, Saraswoti; Pontes, Maria Araci de Andrade; Gonçalves, Heitor de Sá; Hussien, Jemal; Thapa, Pratibha; Kunwar, Chhatra B; Hagge, Deanna A; Aseffa, Abraham; Pessolani, Maria Cristina Vidal; Pereira, Geraldo M B; Ottenhoff, Tom H M; Geluk, Annemieke

2012-12-01

Silent transmission of Mycobacterium leprae, as evidenced by stable leprosy incidence rates in various countries, remains a health challenge despite the implementation of multidrug therapy worldwide. Therefore, the development of tools for the early diagnosis of M. leprae infection should be emphasised in leprosy research. As part of the continuing effort to identify antigens that have diagnostic potential, unique M. leprae peptides derived from predicted virulence-associated proteins (group IV.A) were identified using advanced genome pattern programs and bioinformatics. Based on human leukocyte antigen (HLA)-binding motifs, we selected 21 peptides that were predicted to be promiscuous HLA-class I T-cell epitopes and eight peptides that were predicted to be HLA-class II restricted T-cell epitopes for field-testing in Brazil, Ethiopia and Nepal. High levels of interferon (IFN)-γ were induced when peripheral blood mononuclear cells (PBMCs) from tuberculoid/borderline tuberculoid leprosy patients located in Brazil and Ethiopia were stimulated with the ML2055 p35 peptide. PBMCs that were isolated from healthy endemic controls living in areas with high leprosy prevalence (EChigh) in Ethiopia also responded to the ML2055 p35 peptide. The Brazilian EChigh group recognised the ML1358 p20 and ML1358 p24 peptides. None of the peptides were recognised by PBMCs from healthy controls living in non-endemic region. In Nepal, mixtures of these peptides induced the production of IFN-γ by the PBMCs of leprosy patients and EChigh. Therefore, the M. leprae virulence-associated peptides identified in this study may be useful for identifying exposure to M. leprae in population with differing HLA polymorphisms.

Twenty-four signature genes predict the prognosis of oral squamous cell carcinoma with high accuracy and repeatability

PubMed Central

Gao, Jianyong; Tian, Gang; Han, Xu; Zhu, Qiang

2018-01-01

Oral squamous cell carcinoma (OSCC) is the sixth most common type cancer worldwide, with poor prognosis. The present study aimed to identify gene signatures that could classify OSCC and predict prognosis in different stages. A training data set (GSE41613) and two validation data sets (GSE42743 and GSE26549) were acquired from the online Gene Expression Omnibus database. In the training data set, patients were classified based on the tumor-node-metastasis staging system, and subsequently grouped into low stage (L) or high stage (H). Signature genes between L and H stages were selected by disparity index analysis, and classification was performed by the expression of these signature genes. The established classification was compared with the L and H classification, and fivefold cross validation was used to evaluate the stability. Enrichment analysis for the signature genes was implemented by the Database for Annotation, Visualization and Integration Discovery. Two validation data sets were used to determine the precise of classification. Survival analysis was conducted followed each classification using the package ‘survival’ in R software. A set of 24 signature genes was identified based on the classification model with the Fi value of 0.47, which was used to distinguish OSCC samples in two different stages. Overall survival of patients in the H stage was higher than those in the L stage. Signature genes were primarily enriched in ‘ether lipid metabolism’ pathway and biological processes such as ‘positive regulation of adaptive immune response’ and ‘apoptotic cell clearance’. The results provided a novel 24-gene set that may be used as biomarkers to predict OSCC prognosis with high accuracy, which may be used to determine an appropriate treatment program for patients with OSCC in addition to the traditional evaluation index. PMID:29257303

Predictions of cell damage rates for Lifesat missions

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; Atwell, William; Hardy, Alva C.; Golightly, Michael J.; Wilson, John W.; Townsend, Lawrence W.; Shinn, Judy; Nealy, John E.; Katz, Robert

1990-01-01

The track model of Katz is used to make predictions of cell damage rates for possible Lifesat experiments. Contributions from trapped protons and electrons and galactic cosmic rays are considered for several orbits. Damage rates for survival and transformation of C3HT10-1/2 cells are predicted for various spacecraft shields.

Binding sites for interaction of peroxiredoxin 6 with surfactant protein A

PubMed Central

Krishnaiah, Saikumari Y; Dodia, Chandra; Sorokina, Elena M; Li, Haitao; Feinstein, Sheldon I; Fisher, Aron B

2016-01-01

Peroxiredoxin 6 (Prdx6) is a bifunctional enzyme with peroxidase and phospholipase A2 (PLA2) activities. This protein participates in the degradation and remodeling of internalized dipalmitoylphosphatidylcholine (DPPC), the major phospholipid component of lung surfactant. We have shown previously that the PLA2 activity of Prdx6 is inhibited by the lung surfactant-associated protein called surfactant protein A (SP-A) through direct protein-protein interaction. Docking of SPA and Prdx6 was modeled using the ZDOCK (zlab.bu.edu) program in order to predict molecular sites for binding of the two proteins. The predicted peptide sequences were evaluated for binding to the opposite protein using isothermal titration calorimetry and circular dichroism measurement followed by determination of the effect of the SP-A peptide on the PLA2 activity of Prdx6. The sequences 195EEEAKKLFPK204.in the Prdx6 helix and 83DEELQTELYEIKHQIL99 in SP-A were identified as the sites for hydrophobic interaction and H+-bonding between the 2 proteins. Treatment of mouse endothelial cells with the SP-A peptide inhibited their recovery from lipid peroxidation associated with oxidative stress indicating inhibition of Prdx6 activity by the peptide in the intact cell. PMID:26723227

Flow/Damage Surfaces for Fiber-Reinforced Metals Having Different Periodic Microstructures

NASA Technical Reports Server (NTRS)

Lissenden, Cliff J.; Arnold, Steven M.; Iyer, Saiganesh K.

1998-01-01

Flow/damage surfaces can be defined in terms of stress, inelastic strain rate, and internal variables using a thermodynamics framework. A macroscale definition relevant to thermodynamics and usable in an experimental program is employed to map out surfaces of constant inelastic power in various stress planes. The inelastic flow of a model silicon carbide/ titanium composite system having rectangular, hexagonal, and square diagonal fiber packing arrays subjected to biaxial stresses is quantified by flow/damage surfaces that are determined numerically from micromechanics, using both finite element analysis and the generalized method of cells. Residual stresses from processing are explicitly included and damage in the form of fiber-matrix debonding under transverse tensile and/or shear loading is represented by a simple interface model. The influence of microstructural architecture is largest whenever fiber-matrix debonding is not an issue; for example in the presence of transverse compressive stresses. Additionally, as the fiber volume fraction increases, so does the effect of microstructural architecture. With regard to the micromechanics analysis, the overall inelastic flow predicted by the generalized method of cells is in excellent agreement with that predicted using a large number of displacement-based finite elements.

Flow/Damage Surfaces for Fiber-Reinforced Metals having Different Periodic Microstructures

NASA Technical Reports Server (NTRS)

Lissenden, Cliff J.; Arnold, Steven M.; Iyer, Saiganesh K.

1998-01-01

Flow/damage surfaces can be defined in terms of stress, inelastic strain rate, and internal variables using a thermodynamics framework. A macroscale definition relevant to thermodynamics and usable in an experimental program is employed to map out surfaces of constant inelastic power in various stress planes. The inelastic flow of a model silicon carbide/ titanium composite system having rectangular, hexagonal, and square diagonal fiber packing, arrays subjected to biaxial stresses is quantified by flow/damage surfaces that are determined numerically from micromechanics. using both finite element analysis and the generalized method of cells. Residual stresses from processing are explicitly included and damage in the form of fiber-matrix debonding under transverse tensile and/or shear loading is represented by a simple interface model. The influence of microstructural architecture is largest whenever fiber-matrix debonding is not an issue, for example in the presence of transverse compressive stresses. Additionally, as the fiber volume fraction increases, so does the effect of microstructural architecture. With regard to the micromechanics analysis, the overall inelastic flow predicted by the generalized method of cells is in excellent agreement with that predicted using a large number of displacement-based finite elements.

Modeling invasive breast cancer: growth factors propel progression of HER2-positive premalignant lesions

PubMed Central

Pradeep, C-R; Zeisel, A; Köstler, WJ; Lauriola, M; Jacob-Hirsch, J; Haibe-Kains, B; Amariglio, N; Ben-Chetrit, N; Emde, A; Solomonov, I; Neufeld, G; Piccart, M; Sagi, I; Sotiriou, C; Rechavi, G; Domany, E; Desmedt, C; Yarden, Y

2013-01-01

The HER2/neu oncogene encodes a receptor-like tyrosine kinase whose overexpression in breast cancer predicts poor prognosis and resistance to conventional therapies. However, the mechanisms underlying aggressiveness of HER2 (human epidermal growth factor receptor 2)-overexpressing tumors remain incompletely understood. Because it assists epidermal growth factor (EGF) and neuregulin receptors, we overexpressed HER2 in MCF10A mammary cells and applied growth factors. HER2-overexpressing cells grown in extracellular matrix formed filled spheroids, which protruded outgrowths upon growth factor stimulation. Our transcriptome analyses imply a two-hit model for invasive growth: HER2-induced proliferation and evasion from anoikis generate filled structures, which are morphologically and transcriptionally analogous to preinvasive patients’ lesions. In the second hit, EGF escalates signaling and transcriptional responses leading to invasive growth. Consistent with clinical relevance, a gene expression signature based on the HER2/EGF-activated transcriptional program can predict poorer prognosis of a subgroup of HER2-overexpressing patients. In conclusion, the integration of a three-dimensional cellular model and clinical data attributes progression of HER2-overexpressing lesions to EGF-like growth factors acting in the context of the tumor's microenvironment. PMID:22139081

Program Predicts Time Courses of Human/Computer Interactions

NASA Technical Reports Server (NTRS)

Vera, Alonso; Howes, Andrew

2005-01-01

CPM X is a computer program that predicts sequences of, and amounts of time taken by, routine actions performed by a skilled person performing a task. Unlike programs that simulate the interaction of the person with the task environment, CPM X predicts the time course of events as consequences of encoded constraints on human behavior. The constraints determine which cognitive and environmental processes can occur simultaneously and which have sequential dependencies. The input to CPM X comprises (1) a description of a task and strategy in a hierarchical description language and (2) a description of architectural constraints in the form of rules governing interactions of fundamental cognitive, perceptual, and motor operations. The output of CPM X is a Program Evaluation Review Technique (PERT) chart that presents a schedule of predicted cognitive, motor, and perceptual operators interacting with a task environment. The CPM X program allows direct, a priori prediction of skilled user performance on complex human-machine systems, providing a way to assess critical interfaces before they are deployed in mission contexts.

Interior noise prediction methodology: ATDAC theory and validation

NASA Technical Reports Server (NTRS)

Mathur, Gopal P.; Gardner, Bryce K.

1992-01-01

The Acoustical Theory for Design of Aircraft Cabins (ATDAC) is a computer program developed to predict interior noise levels inside aircraft and to evaluate the effects of different aircraft configurations on the aircraft acoustical environment. The primary motivation for development of this program is the special interior noise problems associated with advanced turboprop (ATP) aircraft where there is a tonal, low frequency noise problem. Prediction of interior noise levels requires knowledge of the energy sources, the transmission paths, and the relationship between the energy variable and the sound pressure level. The energy sources include engine noise, both airborne and structure-borne; turbulent boundary layer noise; and interior noise sources such as air conditioner noise and auxiliary power unit noise. Since propeller and engine noise prediction programs are widely available, they are not included in ATDAC. Airborne engine noise from any prediction or measurement may be input to this program. This report describes the theory and equations implemented in the ATDAC program.

Interior noise prediction methodology: ATDAC theory and validation

NASA Astrophysics Data System (ADS)

Mathur, Gopal P.; Gardner, Bryce K.

1992-04-01

The Acoustical Theory for Design of Aircraft Cabins (ATDAC) is a computer program developed to predict interior noise levels inside aircraft and to evaluate the effects of different aircraft configurations on the aircraft acoustical environment. The primary motivation for development of this program is the special interior noise problems associated with advanced turboprop (ATP) aircraft where there is a tonal, low frequency noise problem. Prediction of interior noise levels requires knowledge of the energy sources, the transmission paths, and the relationship between the energy variable and the sound pressure level. The energy sources include engine noise, both airborne and structure-borne; turbulent boundary layer noise; and interior noise sources such as air conditioner noise and auxiliary power unit noise. Since propeller and engine noise prediction programs are widely available, they are not included in ATDAC. Airborne engine noise from any prediction or measurement may be input to this program. This report describes the theory and equations implemented in the ATDAC program.

COSIM: A Finite-Difference Computer Model to Predict Ternary Concentration Profiles Associated with Oxidation and Interdiffusion of Overlay-Coated Substrates

NASA Technical Reports Server (NTRS)

Nesbitt, James A.

2000-01-01

A finite-difference computer program (COSIM) has been written which models the one-dimensional, diffusional transport associated with high-temperature oxidation and interdiffusion of overlay-coated substrates. The program predicts concentration profiles for up to three elements in the coating and substrate after various oxidation exposures. Surface recession due to solute loss is also predicted. Ternary cross terms and concentration-dependent diffusion coefficients are taken into account. The program also incorporates a previously-developed oxide growth and spalling model to simulate either isothermal or cyclic oxidation exposures. In addition to predicting concentration profiles after various oxidation exposures, the program can also be used to predict coating fife based on a concentration dependent failure criterion (e.g., surface solute content drops to two percent). The computer code, written in an extension of FORTRAN 77, employs numerous subroutines to make the program flexible and easily modifiable to other coating oxidation problems.

Status and plans for the ANOPP/HSR prediction system

NASA Technical Reports Server (NTRS)

Nolan, Sandra K.

1992-01-01

ANOPP is a comprehensive prediction system which was developed and validated by NASA. Because ANOPP is a system prediction program, it allows aerospace industry researchers to create trade-off studies with a variety of aircraft noise problems. The extensive validation of ANOPP allows the program results to be used as a benchmark for testing other prediction codes.

Axi-symmetric patterns of active polar filaments on spherical and composite surfaces

NASA Astrophysics Data System (ADS)

Srivastava, Pragya; Rao, Madan

2014-03-01

Experiments performed on Fission Yeast cells of cylindrical and spherical shapes, rod-shaped bacteria and reconstituted cylindrical liposomes suggest the influence of cell geometry on patterning of cortical actin. A theoretical model based on active hydrodynamic description of cortical actin that includes curvature-orientation coupling predicts spontaneous formation of acto-myosin rings, cables and nodes on cylindrical and spherical geometries [P. Srivastava et al, PRL 110, 168104(2013)]. Stability and dynamics of these patterns is also affected by the cellular shape and has been observed in experiments performed on Fission Yeast cells of spherical shape. Motivated by this, we study the stability and dynamics of axi-symmetric patterns of active polar filaments on the surfaces of spherical, saddle shaped and conical geometry and classify the stable steady state patterns on these surfaces. Based on the analysis of the fluorescence images of Myosin-II during ring slippage we propose a simple mechanical model for ring-sliding based on force balance and make quantitative comparison with the experiments performed on Fission Yeast cells. NSF Grant DMR-1004789 and Syracuse Soft Matter Program.

Transient elevation of cytoplasmic calcium ion concentration at a single cell level precedes morphological changes of epidermal keratinocytes during cornification.

PubMed

Murata, Teruasa; Honda, Tetsuya; Egawa, Gyohei; Yamamoto, Yasuo; Ichijo, Ryo; Toyoshima, Fumiko; Dainichi, Teruki; Kabashima, Kenji

2018-04-26

Epidermal keratinocytes achieve sequential differentiation from basal to granular layers, and undergo a specific programmed cell death, cornification, to form an indispensable barrier of the body. Although elevation of the cytoplasmic calcium ion concentration ([Ca 2+ ] i ) is one of the factors predicted to regulate cornification, the dynamics of [Ca 2+ ] i in epidermal keratinocytes is largely unknown. Here using intravital imaging, we captured the dynamics of [Ca 2+ ] i in mouse skin. [Ca 2+ ] i was elevated in basal cells on the second time scale in three spatiotemporally distinct patterns. The transient elevation of [Ca 2+ ] i also occurred at the most apical granular layer at a single cell level, and lasted for approximately 40 min. The transient elevation of [Ca 2+ ] i at the granular layer was followed by cornification, which was completed within 10 min. This study demonstrates the tightly regulated elevation of [Ca 2+ ] i preceding the cornification of epidermal keratinocytes, providing possible clues to the mechanisms of cornification.

Programming Retinal Stem Cells into Cone Photoreceptors

DTIC Science & Technology

2015-12-01

AWARD NUMBER: W81XWH-14-1-0566 TITLE: Programming Retinal Stem Cells into Cone Photoreceptors PRINCIPAL INVESTIGATOR: Joseph A. Brzezinski IV...SUBTITLE 5a. CONTRACT NUMBER Programming Retinal Stem Cells into Cone Photoreceptors 5b. GRANT NUMBER W81XWH-14-1-0566 5c. PROGRAM ELEMENT NUMBER 6...to program human stem cells directly into cones. Using RNA-seq, we identified several genes that are upregulated in advance of the earliest

Helicopter main-rotor speed effects: A comparison of predicted ranges of detection from the aural detection program ICHIN and the electronic detection program ARCAS

NASA Technical Reports Server (NTRS)

Mueller, Arnold W.; Smith, Charles D.

1991-01-01

NASA LaRC personnel have conducted a strudy of the predicted acoustic detection ranges associated with reduced helicopter main rotor speeds. This was accomplished by providing identical input information to both the aural detection program ICHIN 6, (I Can Hear It Now, version 6) and the electronic acoustic detection program ARCAS (Assessment of Rotorcraft Detection by Acoustics Sensing). In this study, it was concluded that reducing the main rotor speed of the helicopter by 27 percent reduced both the predicted aural and electronic detection ranges by approximately 50 percent. Additionally, ARCAS was observed to function better with narrowband spectral input than with one-third octave band spectral inputs and the predicted electronic range of acoustic detection is greater than the predicted aural detection range.

Modeling and predictions of biphasic mechanosensitive cell migration altered by cell-intrinsic properties and matrix confinement.

PubMed

Pathak, Amit

2018-04-12

Motile cells sense the stiffness of their extracellular matrix (ECM) through adhesions and respond by modulating the generated forces, which in turn lead to varying mechanosensitive migration phenotypes. Through modeling and experiments, cell migration speed is known to vary with matrix stiffness in a biphasic manner, with optimal motility at an intermediate stiffness. Here, we present a two-dimensional cell model defined by nodes and elements, integrated with subcellular modeling components corresponding to mechanotransductive adhesion formation, force generation, protrusions and node displacement. On 2D matrices, our calculations reproduce the classic biphasic dependence of migration speed on matrix stiffness and predict that cell types with higher force-generating ability do not slow down on very stiff matrices, thus disabling the biphasic response. We also predict that cell types defined by lower number of total receptors require stiffer matrices for optimal motility, which also limits the biphasic response. For a cell type with robust biphasic migration on 2D surface, simulations in channel-like confined environments of varying width and height predict faster migration in more confined matrices. Simulations performed in shallower channels predict that the biphasic mechanosensitive cell migration response is more robust on 2D micro-patterns as compared to the channel-like 3D confinement. Thus, variations in the dimensionality of matrix confinement alters the way migratory cells sense and respond to the matrix stiffness. Our calculations reveal new phenotypes of stiffness- and topography-sensitive cell migration that critically depend on both cell-intrinsic and matrix properties. These predictions may inform our understanding of various mechanosensitive modes of cell motility that could enable tumor invasion through topographically heterogeneous microenvironments. © 2018 IOP Publishing Ltd.

Spherical roller bearing analysis. SKF computer program SPHERBEAN. Volume 3: Program correlation with full scale hardware tests

NASA Technical Reports Server (NTRS)

Kleckner, R. J.; Rosenlieb, J. W.; Dyba, G.

1980-01-01

The results of a series of full scale hardware tests comparing predictions of the SPHERBEAN computer program with measured data are presented. The SPHERBEAN program predicts the thermomechanical performance characteristics of high speed lubricated double row spherical roller bearings. The degree of correlation between performance predicted by SPHERBEAN and measured data is demonstrated. Experimental and calculated performance data is compared over a range in speed up to 19,400 rpm (0.8 MDN) under pure radial, pure axial, and combined loads.

Predicting CD4 count changes among patients on antiretroviral treatment: Application of data mining techniques.

PubMed

Kebede, Mihiretu; Zegeye, Desalegn Tigabu; Zeleke, Berihun Megabiaw

2017-12-01

To monitor the progress of therapy and disease progression, periodic CD4 counts are required throughout the course of HIV/AIDS care and support. The demand for CD4 count measurement is increasing as ART programs expand over the last decade. This study aimed to predict CD4 count changes and to identify the predictors of CD4 count changes among patients on ART. A cross-sectional study was conducted at the University of Gondar Hospital from 3,104 adult patients on ART with CD4 counts measured at least twice (baseline and most recent). Data were retrieved from the HIV care clinic electronic database and patients` charts. Descriptive data were analyzed by SPSS version 20. Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology was followed to undertake the study. WEKA version 3.8 was used to conduct a predictive data mining. Before building the predictive data mining models, information gain values and correlation-based Feature Selection methods were used for attribute selection. Variables were ranked according to their relevance based on their information gain values. J48, Neural Network, and Random Forest algorithms were experimented to assess model accuracies. The median duration of ART was 191.5 weeks. The mean CD4 count change was 243 (SD 191.14) cells per microliter. Overall, 2427 (78.2%) patients had their CD4 counts increased by at least 100 cells per microliter, while 4% had a decline from the baseline CD4 value. Baseline variables including age, educational status, CD8 count, ART regimen, and hemoglobin levels predicted CD4 count changes with predictive accuracies of J48, Neural Network, and Random Forest being 87.1%, 83.5%, and 99.8%, respectively. Random Forest algorithm had a superior performance accuracy level than both J48 and Artificial Neural Network. The precision, sensitivity and recall values of Random Forest were also more than 99%. Nearly accurate prediction results were obtained using Random Forest algorithm. This algorithm could be used in a low-resource setting to build a web-based prediction model for CD4 count changes. Copyright © 2017 Elsevier B.V. All rights reserved.

FrameD: A flexible program for quality check and gene prediction in prokaryotic genomes and noisy matured eukaryotic sequences.

PubMed

Schiex, Thomas; Gouzy, Jérôme; Moisan, Annick; de Oliveira, Yannick

2003-07-01

We describe FrameD, a program that predicts coding regions in prokaryotic and matured eukaryotic sequences. Initially targeted at gene prediction in bacterial GC rich genomes, the gene model used in FrameD also allows to predict genes in the presence of frameshifts and partially undetermined sequences which makes it also very suitable for gene prediction and frameshift correction in unfinished sequences such as EST and EST cluster sequences. Like recent eukaryotic gene prediction programs, FrameD also includes the ability to take into account protein similarity information both in its prediction and its graphical output. Its performances are evaluated on different bacterial genomes. The web site (http://genopole.toulouse.inra.fr/bioinfo/FrameD/FD) allows direct prediction, sequence correction and translation and the ability to learn new models for new organisms.

Documentation of the Benson Diesel Engine Simulation Program

NASA Technical Reports Server (NTRS)

Vangerpen, Jon

1988-01-01

This report documents the Benson Diesel Engine Simulation Program and explains how it can be used to predict the performance of diesel engines. The program was obtained from the Garrett Turbine Engine Company but has been extensively modified since. The program is a thermodynamic simulation of the diesel engine cycle which uses a single zone combustion model. It can be used to predict the effect of changes in engine design and operating parameters such as valve timing, speed and boost pressure. The most significan change made to this program is the addition of a more detailed heat transfer model to predict metal part temperatures. This report contains a description of the sub-models used in the Benson program, a description of the input parameters and sample program runs.

MultiP-Apo: A Multilabel Predictor for Identifying Subcellular Locations of Apoptosis Proteins

PubMed Central

Li, Hui; Wang, Rong; Gan, Yong

2017-01-01

Apoptosis proteins play an important role in the mechanism of programmed cell death. Predicting subcellular localization of apoptosis proteins is an essential step to understand their functions and identify drugs target. Many computational prediction methods have been developed for apoptosis protein subcellular localization. However, these existing works only focus on the proteins that have one location; proteins with multiple locations are either not considered or assumed as not existing when constructing prediction models, so that they cannot completely predict all the locations of the apoptosis proteins with multiple locations. To address this problem, this paper proposes a novel multilabel predictor named MultiP-Apo, which can predict not only apoptosis proteins with single subcellular location but also those with multiple subcellular locations. Specifically, given a query protein, GO-based feature extraction method is used to extract its feature vector. Subsequently, the GO feature vector is classified by a new multilabel classifier based on the label-specific features. It is the first multilabel predictor ever established for identifying subcellular locations of multilocation apoptosis proteins. As an initial study, MultiP-Apo achieves an overall accuracy of 58.49% by jackknife test, which indicates that our proposed predictor may become a very useful high-throughput tool in this area. PMID:28744305

MultiP-Apo: A Multilabel Predictor for Identifying Subcellular Locations of Apoptosis Proteins.

PubMed

Wang, Xiao; Li, Hui; Wang, Rong; Zhang, Qiuwen; Zhang, Weiwei; Gan, Yong

2017-01-01

Apoptosis proteins play an important role in the mechanism of programmed cell death. Predicting subcellular localization of apoptosis proteins is an essential step to understand their functions and identify drugs target. Many computational prediction methods have been developed for apoptosis protein subcellular localization. However, these existing works only focus on the proteins that have one location; proteins with multiple locations are either not considered or assumed as not existing when constructing prediction models, so that they cannot completely predict all the locations of the apoptosis proteins with multiple locations. To address this problem, this paper proposes a novel multilabel predictor named MultiP-Apo, which can predict not only apoptosis proteins with single subcellular location but also those with multiple subcellular locations. Specifically, given a query protein, GO-based feature extraction method is used to extract its feature vector. Subsequently, the GO feature vector is classified by a new multilabel classifier based on the label-specific features. It is the first multilabel predictor ever established for identifying subcellular locations of multilocation apoptosis proteins. As an initial study, MultiP-Apo achieves an overall accuracy of 58.49% by jackknife test, which indicates that our proposed predictor may become a very useful high-throughput tool in this area.

Circular RNA hsa_circ_0003575 regulates oxLDL induced vascular endothelial cells proliferation and angiogenesis.

PubMed

Li, Chen-Ye; Ma, Lan; Yu, Bo

2017-11-01

Circular RNAs (circRNAs) are a novel class of RNAs generated from back-splicing and characterized by covalently closed continuous loops. Recently, circRNAs have recently shown large regulation on cardiovascular system, including atherosclerosis. The present study aims to investigate the circRNA expression profile and identify their roles on vascular endothelial cells induced by oxLDL. Human circRNA microarray analysis revealed that total 943 differently expressed circRNAs were screened with 2 fold change. Hsa_circ_0003575 was validated to be significantly up-regulated in oxLDL induced HUVECs. Loss-of-function experiments indicated that hsa_circ_0003575 silencing promoted the proliferation and angiogenesis ability of HUVECs. Bioinformatics online programs predicted the potential circRNA-miRNA-mRNA network for hsa_circ_0003575. In summary, circRNA microarray analysis reveals the expression profiles of HUVECs and verifies the role of hsa_circ_0003575 on HUVECs, providing a therapeutic strategy for vascular endothelial cell injury of atherosclerosis. Copyright © 2017. Published by Elsevier Masson SAS.

Development of an energy consumption and cost data base for fuel cell total energy systems and conventional building energy systems

NASA Astrophysics Data System (ADS)

Pine, G. D.; Christian, J. E.; Mixon, W. R.; Jackson, W. L.

1980-07-01

The procedures and data sources used to develop an energy consumption and system cost data base for use in predicting the market penetration of phosphoric acid fuel cell total energy systems in the nonindustrial building market are described. A computer program was used to simulate the hourly energy requirements of six types of buildings; office buildings; retail stores; hotels and motels; schools; hospitals; and multifamily residences. The simulations were done by using hourly weather tapes for one city in each of the ten Department of Energy administrative regions. Two types of building construction were considered, one for existing buildings and one for new buildings. A fuel cell system combined with electrically driven heat pumps and one combined with a gas boiler and an electrically driven chiller were compared with similar conventional systems. The methods of system simulation, component sizing, and system cost estimation are described for each system.

Automated Deep Learning-Based System to Identify Endothelial Cells Derived from Induced Pluripotent Stem Cells.

PubMed

Kusumoto, Dai; Lachmann, Mark; Kunihiro, Takeshi; Yuasa, Shinsuke; Kishino, Yoshikazu; Kimura, Mai; Katsuki, Toshiomi; Itoh, Shogo; Seki, Tomohisa; Fukuda, Keiichi

2018-06-05

Deep learning technology is rapidly advancing and is now used to solve complex problems. Here, we used deep learning in convolutional neural networks to establish an automated method to identify endothelial cells derived from induced pluripotent stem cells (iPSCs), without the need for immunostaining or lineage tracing. Networks were trained to predict whether phase-contrast images contain endothelial cells based on morphology only. Predictions were validated by comparison to immunofluorescence staining for CD31, a marker of endothelial cells. Method parameters were then automatically and iteratively optimized to increase prediction accuracy. We found that prediction accuracy was correlated with network depth and pixel size of images to be analyzed. Finally, K-fold cross-validation confirmed that optimized convolutional neural networks can identify endothelial cells with high performance, based only on morphology. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Immune cell identity: perspective from a palimpsest

PubMed Central

Rothenberg, Ellen V.

2016-01-01

The immune system in mammals is composed of multiple different immune cell types that migrate through the body and are made continuously throughout life. Lymphocytes and myeloid cells interact with each other and depend upon each other, but are each highly diverse and specialized for different roles. Lymphocytes uniquely require developmentally programmed mutational changes in the genome itself for their maturation. Despite profound differences between their mechanisms of threat recognition and threat response, however, the developmental origins of lymphocytes and myeloid cells are interlinked, and important aspects of their response mechanisms remain shared. As the immune defense system has been elucidated in the past 50 years, it is notable that the chain of logic toward our current understanding was driven by strongly posited models that led to crucial discoveries even though these models ended up being partly wrong. It has been the predictive strength of these models and their success as guides to incisive experimental research that has also illuminated the limits of each model’s explanatory scope, beyond which another model needed to assume the lead. This brief review describes how a succession of distinct paradigms has helped to clarify a sophisticated picture of immune cell generation and control. PMID:26750603

Programmable single-cell mammalian biocomputers.

PubMed

Ausländer, Simon; Ausländer, David; Müller, Marius; Wieland, Markus; Fussenegger, Martin

2012-07-05

Synthetic biology has advanced the design of standardized control devices that program cellular functions and metabolic activities in living organisms. Rational interconnection of these synthetic switches resulted in increasingly complex designer networks that execute input-triggered genetic instructions with precision, robustness and computational logic reminiscent of electronic circuits. Using trigger-controlled transcription factors, which independently control gene expression, and RNA-binding proteins that inhibit the translation of transcripts harbouring specific RNA target motifs, we have designed a set of synthetic transcription–translation control devices that could be rewired in a plug-and-play manner. Here we show that these combinatorial circuits integrated a two-molecule input and performed digital computations with NOT, AND, NAND and N-IMPLY expression logic in single mammalian cells. Functional interconnection of two N-IMPLY variants resulted in bitwise intracellular XOR operations, and a combinatorial arrangement of three logic gates enabled independent cells to perform programmable half-subtractor and half-adder calculations. Individual mammalian cells capable of executing basic molecular arithmetic functions isolated or coordinated to metabolic activities in a predictable, precise and robust manner may provide new treatment strategies and bio-electronic interfaces in future gene-based and cell-based therapies.

Pembrolizumab in the treatment of metastatic non-small cell lung cancer: a review of current evidence

PubMed Central

Rihawi, Karim; Gelsomino, Francesco; Sperandi, Francesca; Melotti, Barbara; Fiorentino, Michelangelo; Casolari, Laura; Ardizzoni, Andrea

2017-01-01

Immune checkpoint inhibitors (ICPIs) are considered one of the most important breakthroughs in cancer treatment of the past decade; notably, different studies of programmed cell death protein 1 (PD-1) and programmed death-ligand 1 (PD-L1) inhibitors have reported impressive clinical activity and durable responses in patients with advanced non-small cell lung cancer (NSCLC). These findings have led to the changing of the current therapeutic algorithm of advanced NSCLC, adding a new standard first-line treatment option for patients with PD-L1-positive tumors. Pembrolizumab, a highly selective anti-PD-1 humanized monoclonal antibody, was approved by the United States Food and Drug Administration (US FDA) in October 2016 for previously untreated metastatic NSCLC patients whose tumors have high PD-L1 expression, tumor proportion score (TPS) ⩾ 50%, as well as for metastatic NSCLC patients whose tumors express PD-L1 with TPS ⩾ 1% progressing on or after platinum-based chemotherapy. However, many issues remain outstanding, mainly regarding the identification of an optimal biomarker which can help selecting patients more likely to respond to ICPIs. In this review, we discuss the clinical results obtained so far with the anti-PD-1 pembrolizumab in advanced NSCLC, commenting on the role of PD-L1 as a predictive factor and providing an update of the future perspectives. PMID:28818019

Photovoltaic prospects in Europe

NASA Astrophysics Data System (ADS)

Starr, M. R.

The economics of solar cells is reviewed with an eye to potential cost reductions in processing, and potential markets are explored. Current solar cell systems costs are noted to be on the road to achieving the U.S. DoE goals of $0.40/kWp by 1990. Continued progress will depend on technical developments in cheaper materials and processes, scaling up production, and the success of sales programs. Various consumer and professional markets are outlined, with a prediction that a 12 MWp deman will be reached as a steady state by 1995. Photovoltaic panels may conceivably replace conventional roofing materials, resulting in the projection that, if grid-supplied power continues to inflate in price, then all new European homes would be equipped with photovoltaics by the year 2000. Further, accomplishment of the cost goals could generate a 1 GWp/yr industrial market at the same time.

Student Use of Physics to Make Sense of Incomplete but Functional VPython Programs in a Lab Setting

NASA Astrophysics Data System (ADS)

Weatherford, Shawn A.

2011-12-01

Computational activities in Matter & Interactions, an introductory calculus-based physics course, have the instructional goal of providing students with the experience of applying the same set of a small number of fundamental principles to model a wide range of physical systems. However there are significant instructional challenges for students to build computer programs under limited time constraints, especially for students who are unfamiliar with programming languages and concepts. Prior attempts at designing effective computational activities were successful at having students ultimately build working VPython programs under the tutelage of experienced teaching assistants in a studio lab setting. A pilot study revealed that students who completed these computational activities had significant difficultly repeating the exact same tasks and further, had difficulty predicting the animation that would be produced by the example program after interpreting the program code. This study explores the interpretation and prediction tasks as part of an instructional sequence where students are asked to read and comprehend a functional, but incomplete program. Rather than asking students to begin their computational tasks with modifying program code, we explicitly ask students to interpret an existing program that is missing key lines of code. The missing lines of code correspond to the algebraic form of fundamental physics principles or the calculation of forces which would exist between analogous physical objects in the natural world. Students are then asked to draw a prediction of what they would see in the simulation produced by the VPython program and ultimately run the program to evaluate the students' prediction. This study specifically looks at how the participants use physics while interpreting the program code and creating a whiteboard prediction. This study also examines how students evaluate their understanding of the program and modification goals at the beginning of the modification task. While working in groups over the course of a semester, study participants were recorded while they completed three activities using these incomplete programs. Analysis of the video data showed that study participants had little difficulty interpreting physics quantities, generating a prediction, or determining how to modify the incomplete program. Participants did not base their prediction solely from the information from the incomplete program. When participants tried to predict the motion of the objects in the simulation, many turned to their knowledge of how the system would evolve if it represented an analogous real-world physical system. For example, participants attributed the real-world behavior of springs to helix objects even though the program did not include calculations for the spring to exert a force when stretched. Participants rarely interpreted lines of code in the computational loop during the first computational activity, but this changed during latter computational activities with most participants using their physics knowledge to interpret the computational loop. Computational activities in the Matter & Interactions curriculum were revised in light of these findings to include an instructional sequence of tasks to build a comprehension of the example program. The modified activities also ask students to create an additional whiteboard prediction for the time-evolution of the real-world phenomena which the example program will eventually model. This thesis shows how comprehension tasks identified by Palinscar and Brown (1984) as effective in improving reading comprehension are also effective in helping students apply their physics knowledge to interpret a computer program which attempts to model a real-world phenomena and identify errors in their understanding of the use, or omission, of fundamental physics principles in a computational model.

Rapid high-throughput characterisation, classification and selection of recombinant mammalian cell line phenotypes using intact cell MALDI-ToF mass spectrometry fingerprinting and PLS-DA modelling.

PubMed

Povey, Jane F; O'Malley, Christopher J; Root, Tracy; Martin, Elaine B; Montague, Gary A; Feary, Marc; Trim, Carol; Lang, Dietmar A; Alldread, Richard; Racher, Andrew J; Smales, C Mark

2014-08-20

Despite many advances in the generation of high producing recombinant mammalian cell lines over the last few decades, cell line selection and development is often slowed by the inability to predict a cell line's phenotypic characteristics (e.g. growth or recombinant protein productivity) at larger scale (large volume bioreactors) using data from early cell line construction at small culture scale. Here we describe the development of an intact cell MALDI-ToF mass spectrometry fingerprinting method for mammalian cells early in the cell line construction process whereby the resulting mass spectrometry data are used to predict the phenotype of mammalian cell lines at larger culture scale using a Partial Least Squares Discriminant Analysis (PLS-DA) model. Using MALDI-ToF mass spectrometry, a library of mass spectrometry fingerprints was generated for individual cell lines at the 96 deep well plate stage of cell line development. The growth and productivity of these cell lines were evaluated in a 10L bioreactor model of Lonza's large-scale (up to 20,000L) fed-batch cell culture processes. Using the mass spectrometry information at the 96 deep well plate stage and phenotype information at the 10L bioreactor scale a PLS-DA model was developed to predict the productivity of unknown cell lines at the 10L scale based upon their MALDI-ToF fingerprint at the 96 deep well plate scale. This approach provides the basis for the very early prediction of cell lines' performance in cGMP manufacturing-scale bioreactors and the foundation for methods and models for predicting other mammalian cell phenotypes from rapid, intact-cell mass spectrometry based measurements. Copyright © 2014 Elsevier B.V. All rights reserved.

Predicting the payload capability of cable logging systems including the effect of partial suspension

Treesearch

Gary D. Falk

1981-01-01

A systematic procedure for predicting the payload capability of running, live, and standing skylines is presented. Three hand-held calculator programs are used to predict payload capability that includes the effect of partial suspension. The programs allow for predictions for downhill yarding and for yarding away from the yarder. The equations and basic principles...

78 FR 44575 - Sickle Cell Disease Treatment Demonstration Program

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-24

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Health Resources and Services Administration Sickle Cell... Extension: Sickle Cell Disease Treatment Demonstration Program (U1E) Awards to Three Currently Funded... the Sickle Cell Disease Treatment Demonstration Program. Three of these awards will end on August 31...

Predicting network modules of cell cycle regulators using relative protein abundance statistics.

PubMed

Oguz, Cihan; Watson, Layne T; Baumann, William T; Tyson, John J

2017-02-28

Parameter estimation in systems biology is typically done by enforcing experimental observations through an objective function as the parameter space of a model is explored by numerical simulations. Past studies have shown that one usually finds a set of "feasible" parameter vectors that fit the available experimental data equally well, and that these alternative vectors can make different predictions under novel experimental conditions. In this study, we characterize the feasible region of a complex model of the budding yeast cell cycle under a large set of discrete experimental constraints in order to test whether the statistical features of relative protein abundance predictions are influenced by the topology of the cell cycle regulatory network. Using differential evolution, we generate an ensemble of feasible parameter vectors that reproduce the phenotypes (viable or inviable) of wild-type yeast cells and 110 mutant strains. We use this ensemble to predict the phenotypes of 129 mutant strains for which experimental data is not available. We identify 86 novel mutants that are predicted to be viable and then rank the cell cycle proteins in terms of their contributions to cumulative variability of relative protein abundance predictions. Proteins involved in "regulation of cell size" and "regulation of G1/S transition" contribute most to predictive variability, whereas proteins involved in "positive regulation of transcription involved in exit from mitosis," "mitotic spindle assembly checkpoint" and "negative regulation of cyclin-dependent protein kinase by cyclin degradation" contribute the least. These results suggest that the statistics of these predictions may be generating patterns specific to individual network modules (START, S/G2/M, and EXIT). To test this hypothesis, we develop random forest models for predicting the network modules of cell cycle regulators using relative abundance statistics as model inputs. Predictive performance is assessed by the areas under receiver operating characteristics curves (AUC). Our models generate an AUC range of 0.83-0.87 as opposed to randomized models with AUC values around 0.50. By using differential evolution and random forest modeling, we show that the model prediction statistics generate distinct network module-specific patterns within the cell cycle network.

The effect of solution nonideality on modeling transmembrane water transport and diffusion-limited intracellular ice formation during cryopreservation

NASA Astrophysics Data System (ADS)

Zhao, Gang; Takamatsu, Hiroshi; He, Xiaoming

2014-04-01

A new model was developed to predict transmembrane water transport and diffusion-limited ice formation in cells during freezing without the ideal-solution assumption that has been used in previous models. The model was applied to predict cell dehydration and intracellular ice formation (IIF) during cryopreservation of mouse oocytes and bovine carotid artery endothelial cells in aqueous sodium chloride (NaCl) solution with glycerol as the cryoprotectant or cryoprotective agent. A comparison of the predictions between the present model and the previously reported models indicated that the ideal-solution assumption results in under-prediction of the amount of intracellular ice at slow cooling rates (<50 K/min). In addition, the lower critical cooling rates for IIF that is lethal to cells predicted by the present model were much lower than those estimated with the ideal-solution assumption. This study represents the first investigation on how accounting for solution nonideality in modeling water transport across the cell membrane could affect the prediction of diffusion-limited ice formation in biological cells during freezing. Future studies are warranted to look at other assumptions alongside nonideality to further develop the model as a useful tool for optimizing the protocol of cell cryopreservation for practical applications.

The effect of solution nonideality on modeling transmembrane water transport and diffusion-limited intracellular ice formation during cryopreservation.

PubMed

Zhao, Gang; Takamatsu, Hiroshi; He, Xiaoming

2014-04-14

A new model was developed to predict transmembrane water transport and diffusion-limited ice formation in cells during freezing without the ideal-solution assumption that has been used in previous models. The model was applied to predict cell dehydration and intracellular ice formation (IIF) during cryopreservation of mouse oocytes and bovine carotid artery endothelial cells in aqueous sodium chloride (NaCl) solution with glycerol as the cryoprotectant or cryoprotective agent. A comparison of the predictions between the present model and the previously reported models indicated that the ideal-solution assumption results in under-prediction of the amount of intracellular ice at slow cooling rates (<50 K/min). In addition, the lower critical cooling rates for IIF that is lethal to cells predicted by the present model were much lower than those estimated with the ideal-solution assumption. This study represents the first investigation on how accounting for solution nonideality in modeling water transport across the cell membrane could affect the prediction of diffusion-limited ice formation in biological cells during freezing. Future studies are warranted to look at other assumptions alongside nonideality to further develop the model as a useful tool for optimizing the protocol of cell cryopreservation for practical applications.

Predictions of Performance in Career Education.

ERIC Educational Resources Information Center

Novick, M. R.; And Others

Prediction weights for educational programs in 22 vocational and technical fields are provided using ability scores from the American College Testing Program (ACT) Career Planning Profile and a Bayesian regression theory. The criterion variable studies was first-semester grade-point average. Each vocational-technical program analyzed was…

Verification of MICNOISE computer program for the prediction of highway noise

DOT National Transportation Integrated Search

1974-01-01

The objectives of this study were to verify the computer program used by the Virginia Department of Highways to predict highway sound pressure levels, to determine whether the accuracy and usefulness of the program could be improved, and to make reco...

Rsr1 Focuses Cdc42 Activity at Hyphal Tips and Promotes Maintenance of Hyphal Development in Candida albicans

PubMed Central

Pulver, Rebecca; Heisel, Timothy; Gonia, Sara; Robins, Robert; Norton, Jennifer; Haynes, Paula

2013-01-01

The extremely elongated morphology of fungal hyphae is dependent on the cell's ability to assemble and maintain polarized growth machinery over multiple cell cycles. The different morphologies of the fungus Candida albicans make it an excellent model organism in which to study the spatiotemporal requirements for constitutive polarized growth and the generation of different cell shapes. In C. albicans, deletion of the landmark protein Rsr1 causes defects in morphogenesis that are not predicted from study of the orthologous protein in the related yeast Saccharomyces cerevisiae, thus suggesting that Rsr1 has expanded functions during polarized growth in C. albicans. Here, we show that Rsr1 activity localizes to hyphal tips by the differential localization of the Rsr1 GTPase-activating protein (GAP), Bud2, and guanine nucleotide exchange factor (GEF), Bud5. In addition, we find that Rsr1 is needed to maintain the focused localization of hyphal polarity structures and proteins, including Bem1, a marker of the active GTP-bound form of the Rho GTPase, Cdc42. Further, our results indicate that tip-localized Cdc42 clusters are associated with the cell's ability to express a hyphal transcriptional program and that the ability to generate a focused Cdc42 cluster in early hyphae (germ tubes) is needed to maintain hyphal morphogenesis over time. We propose that in C. albicans, Rsr1 “fine-tunes” the distribution of Cdc42 activity and that self-organizing (Rsr1-independent) mechanisms of polarized growth are not sufficient to generate narrow cell shapes or to provide feedback to the transcriptional program during hyphal morphogenesis. PMID:23223038

Merkel Cell Carcinoma Therapeutic Update.

PubMed

Cassler, Nicole M; Merrill, Dean; Bichakjian, Christopher K; Brownell, Isaac

2016-07-01

Merkel cell carcinoma (MCC) is a rare and aggressive neuroendocrine tumor of the skin. Early-stage disease can be cured with surgical resection and radiotherapy (RT). Sentinel lymph node biopsy (SLNB) is an important staging tool, as a microscopic MCC is frequently identified. Adjuvant RT to the primary excision site and regional lymph node bed may improve locoregional control. However, newer studies confirm that patients with biopsy-negative sentinel lymph nodes may not benefit from regional RT. Advanced MCC currently lacks a highly effective treatment as responses to chemotherapy are not durable. Recent work suggests that immunotherapy targeting the programmed cell death receptor 1/programmed cell death ligand 1 (PD-1/PD-L1) checkpoint holds great promise in treating advanced MCC and may provide durable responses in a portion of patients. At the same time, high-throughput sequencing studies have demonstrated significant differences in the mutational profiles of tumors with and without the Merkel cell polyomavirus (MCV). An important secondary endpoint in the ongoing immunotherapy trials for MCC will be determining if there is a response difference between the virus-positive MCC tumors that typically lack a large mutational burden and the virus-negative tumors that have a large number of somatic mutations and predicted tumor neoantigens. Interestingly, sequencing studies have failed to identify a highly recurrent activated driver pathway in the majority of MCC tumors. This may explain why targeted therapies can demonstrate exceptional responses in case reports but fail when treating all comers with MCC. Ultimately, a precision medicine approach may be more appropriate for treating MCC, where identified driver mutations are used to direct targeted therapies. At a minimum, stratifying patients in future clinical trials based on tumor viral status should be considered as virus-negative tumors are more likely to harbor activating driver mutations.

The role of radiation hard solar cells in minimizing the costs of global satellite communication systems

NASA Technical Reports Server (NTRS)

Summers, Geoffrey P.; Walters, Robert J.; Messenger, Scott R.; Burke, Edward A.

1996-01-01

An analysis embodied in a PC computer program is presented, which quantitatively demonstrates how the availability of radiation hard solar cells can help minimize the cost of a global satellite communications system. An important distinction between the currently proposed systems, such as Iridium, Odyssey and Ellipsat, is the number of satellites employed and their operating altitudes. Analysis of the major costs associated with implementing these systems shows that operation at orbital altitudes within the earth's radiation belts (10(exp 3) to 10(exp 4)km) can reduce the total cost of a system by several hundred percent, so long as radiation hard components including solar cells can be used. A detailed evaluation of the predicted performance of photovoltaic arrays using several different planar solar cell technologies is given, including commercially available Si and GaAs/Ge, and InP/Si which is currently under development. Several examples of applying the program are given, which show that the end of life (EOL) power density of different technologies can vary by a factor of ten for certain missions. Therefore, although a relatively radiation-soft technology can usually provide the required EOL power by simply increasing the size of the array, the impact upon the total system budget could be unacceptable, due to increased launch and hardware costs. In aggregate, these factors can account for more than a 10% increase in the total system cost. Since the estimated total costs of proposed global-coverage systems range from $1B to $9B, the availability of radiation-hard solar cells could make a decisive difference in the selection of a particular constellation architecture.

Developing global regression models for metabolite concentration prediction regardless of cell line.

PubMed

André, Silvère; Lagresle, Sylvain; Da Sliva, Anthony; Heimendinger, Pierre; Hannas, Zahia; Calvosa, Éric; Duponchel, Ludovic

2017-11-01

Following the Process Analytical Technology (PAT) of the Food and Drug Administration (FDA), drug manufacturers are encouraged to develop innovative techniques in order to monitor and understand their processes in a better way. Within this framework, it has been demonstrated that Raman spectroscopy coupled with chemometric tools allow to predict critical parameters of mammalian cell cultures in-line and in real time. However, the development of robust and predictive regression models clearly requires many batches in order to take into account inter-batch variability and enhance models accuracy. Nevertheless, this heavy procedure has to be repeated for every new line of cell culture involving many resources. This is why we propose in this paper to develop global regression models taking into account different cell lines. Such models are finally transferred to any culture of the cells involved. This article first demonstrates the feasibility of developing regression models, not only for mammalian cell lines (CHO and HeLa cell cultures), but also for insect cell lines (Sf9 cell cultures). Then global regression models are generated, based on CHO cells, HeLa cells, and Sf9 cells. Finally, these models are evaluated considering a fourth cell line(HEK cells). In addition to suitable predictions of glucose and lactate concentration of HEK cell cultures, we expose that by adding a single HEK-cell culture to the calibration set, the predictive ability of the regression models are substantially increased. In this way, we demonstrate that using global models, it is not necessary to consider many cultures of a new cell line in order to obtain accurate models. Biotechnol. Bioeng. 2017;114: 2550-2559. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Use of a pretest strategy for physical therapist assistant programs to predict success rate on the national physical therapy exam.

PubMed

Sloas, Stacey B; Keith, Becky; Whitehead, Malcolm T

2013-01-01

This study investigated a pretest strategy that identified physical therapist assistant (PTA) students who were at risk of failure on the National Physical Therapy Examination (NPTE). Program assessment data from five cohorts of PTA students (2005-2009) were used to develop a stepwise multiple regression formula that predicted first-time NPTE licensure scores. Data used included the Nelson-Denny Reading Test, grades from eight core courses, grade point average upon admission to the program, and scores from three mock NPTE exams given during the program. Pearson correlation coefficients were calculated between each of the 15 variables and NPTE scores. Stepwise multiple regression analysis was performed using data collected at the ends of the first, second, and third (final) semesters of the program. Data from the class of 2010 were then used to validate the formula. The end-of-program formula accounted for the greatest variance (57%) in predicted scores. Those students scoring below a predicted scaled score of 620 were identified to be at risk of failure of the licensure exam. These students were counseled, and a remedial plan was developed based on regression predictions prior to them sitting for the licensure exam.

BIOPEP database and other programs for processing bioactive peptide sequences.

PubMed

Minkiewicz, Piotr; Dziuba, Jerzy; Iwaniak, Anna; Dziuba, Marta; Darewicz, Małgorzata

2008-01-01

This review presents the potential for application of computational tools in peptide science based on a sample BIOPEP database and program as well as other programs and databases available via the World Wide Web. The BIOPEP application contains a database of biologically active peptide sequences and a program enabling construction of profiles of the potential biological activity of protein fragments, calculation of quantitative descriptors as measures of the value of proteins as potential precursors of bioactive peptides, and prediction of bonds susceptible to hydrolysis by endopeptidases in a protein chain. Other bioactive and allergenic peptide sequence databases are also presented. Programs enabling the construction of binary and multiple alignments between peptide sequences, the construction of sequence motifs attributed to a given type of bioactivity, searching for potential precursors of bioactive peptides, and the prediction of sites susceptible to proteolytic cleavage in protein chains are available via the Internet as are other approaches concerning secondary structure prediction and calculation of physicochemical features based on amino acid sequence. Programs for prediction of allergenic and toxic properties have also been developed. This review explores the possibilities of cooperation between various programs.

PD-L1 Expression of Tumor Cells, Macrophages, and Immune Cells in Non-Small Cell Lung Cancer Patients with Malignant Pleural Effusion.

PubMed

Tseng, Yen-Han; Ho, Hsiang-Ling; Lai, Chiung-Ru; Luo, Yung-Hung; Tseng, Yen-Chiang; Whang-Peng, Jacqueline; Lin, Yi-Hsuan; Chou, Teh-Ying; Chen, Yuh-Min

2018-03-01

Whether immunohistochemical staining of programmed death ligand 1 (PD-L1) on cells of pleural effusion could be used to predict response to immunotherapy treatment has not been reported. We retrospectively enrolled patients who had undergone malignant pleural effusion drainage and had effusion cell block specimens from 2014 to 2016. Immunohistochemical staining for PD-L1 was performed with tumor cells, immune cells, and macrophages of all cell block specimens. Immunoactivity was scored as 0 for absence of staining and 1+ for faint, 2+ for moderate, and 3+ for intense membranous staining. Patients' clinicopathological characteristics were also collected. PD-L1 expression of pleural effusion tumor cells was associated with the PD-L1 expression of macrophages (p = 0.003) and immune cells (p < 0.001). However, the PD-L1 expression of immune cells was not associated with that of macrophages. The PD-L1 expression of tumor cells was correlated with sex (p = 0.012), smoking status (p = 0.032), and Eastern Cooperative Oncology Group performance status (p = 0.017). The PD-L1 expression of immune cells was associated with the overall survival of patients (p = 0.004). These results suggest that there might be an immune interaction between pleural effusion tumor cells and macrophages. The low intensity of PD-L1 expression in immune cells is associated with the poor survival of patients with lung cancer with malignant pleural effusion. Copyright © 2017 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

In Silico Prediction Analysis of Idiotope-Driven T–B Cell Collaboration in Multiple Sclerosis

PubMed Central

Høglund, Rune A.; Lossius, Andreas; Johansen, Jorunn N.; Homan, Jane; Benth, Jūratė Šaltytė; Robins, Harlan; Bogen, Bjarne; Bremel, Robert D.; Holmøy, Trygve

2017-01-01

Memory B cells acting as antigen-presenting cells are believed to be important in multiple sclerosis (MS), but the antigen they present remains unknown. We hypothesized that B cells may activate CD4+ T cells in the central nervous system of MS patients by presenting idiotopes from their own immunoglobulin variable regions on human leukocyte antigen (HLA) class II molecules. Here, we use bioinformatics prediction analysis of B cell immunoglobulin variable regions from 11 MS patients and 6 controls with other inflammatory neurological disorders (OINDs), to assess whether the prerequisites for such idiotope-driven T–B cell collaboration are present. Our findings indicate that idiotopes from the complementarity determining region (CDR) 3 of MS patients on average have high predicted affinities for disease associated HLA-DRB1*15:01 molecules and are predicted to be endosomally processed by cathepsin S and L in positions that allows such HLA binding to occur. Additionally, complementarity determining region 3 sequences from cerebrospinal fluid (CSF) B cells from MS patients contain on average more rare T cell-exposed motifs that could potentially escape tolerance and stimulate CD4+ T cells than CSF B cells from OIND patients. Many of these features were associated with preferential use of the IGHV4 gene family by CSF B cells from MS patients. This is the first study to combine high-throughput sequencing of patient immune repertoires with large-scale prediction analysis and provides key indicators for future in vitro and in vivo analyses. PMID:29038659

In Silico Prediction Analysis of Idiotope-Driven T-B Cell Collaboration in Multiple Sclerosis.

PubMed

Høglund, Rune A; Lossius, Andreas; Johansen, Jorunn N; Homan, Jane; Benth, Jūratė Šaltytė; Robins, Harlan; Bogen, Bjarne; Bremel, Robert D; Holmøy, Trygve

2017-01-01

Memory B cells acting as antigen-presenting cells are believed to be important in multiple sclerosis (MS), but the antigen they present remains unknown. We hypothesized that B cells may activate CD4 + T cells in the central nervous system of MS patients by presenting idiotopes from their own immunoglobulin variable regions on human leukocyte antigen (HLA) class II molecules. Here, we use bioinformatics prediction analysis of B cell immunoglobulin variable regions from 11 MS patients and 6 controls with other inflammatory neurological disorders (OINDs), to assess whether the prerequisites for such idiotope-driven T-B cell collaboration are present. Our findings indicate that idiotopes from the complementarity determining region (CDR) 3 of MS patients on average have high predicted affinities for disease associated HLA-DRB1*15:01 molecules and are predicted to be endosomally processed by cathepsin S and L in positions that allows such HLA binding to occur. Additionally, complementarity determining region 3 sequences from cerebrospinal fluid (CSF) B cells from MS patients contain on average more rare T cell-exposed motifs that could potentially escape tolerance and stimulate CD4 + T cells than CSF B cells from OIND patients. Many of these features were associated with preferential use of the IGHV4 gene family by CSF B cells from MS patients. This is the first study to combine high-throughput sequencing of patient immune repertoires with large-scale prediction analysis and provides key indicators for future in vitro and in vivo analyses.

Cytolytic Activity Score to Assess Anticancer Immunity in Colorectal Cancer.

PubMed

Narayanan, Sumana; Kawaguchi, Tsutomu; Yan, Li; Peng, Xuan; Qi, Qianya; Takabe, Kazuaki

2018-05-16

Elevated tumor-infiltrating lymphocytes (TILs) within the tumor microenvironment is a known positive prognostic factor in colorectal cancer (CRC). We hypothesized that since cytotoxic T cells release cytolytic proteins such as perforin (PRF1) and pro-apoptotic granzymes (GZMA) to attack cancer cells, a cytolytic activity score (CYT) would be a useful tool to assess anticancer immunity. Genomic expression data were obtained from 456 patients from The Cancer Genome Atlas (TCGA). CYT was defined by GZMA and PRF1 expression, and CIBERSORT was used to evaluate intratumoral immune cell composition. High CYT was associated with high microsatellite instability (MSI-H), as well as high levels of activated memory CD4+T cells, gamma-delta T cells, and M1 macrophages. CYT-high CRC patients had improved overall survival (p = 0.019) and disease-free survival (p = 0.016) compared with CYT-low CRC patients, especially in TIL-positive tumors. Multivariate analysis demonstrated that CYT- high associates with improved survival independently after controlling for age, lymphovascular invasion, colonic location, microsatellite instability, and TIL positivity. The levels of immune checkpoint molecules (ICMs)-programmed death-1 (PD-1), programmed death-ligand 1 (PD-L1), cytotoxic T-lymphocyte-associated protein 4 (CTLA4), lymphocyte-activation gene 3 (LAG3), T cell immunoglobulin and mucin domain 3 (TIM3), and indoleamine 2,3-dioxygenase 1 (IDO1)-correlated significantly with CYT (p < 0.0001); with improved survival in CYT-high and ICM-low patients, and poorer survival in ICM-high patients. High CYT within CRC is associated with improved survival, likely due to increased immunity and cytolytic activity of T cells and M1 macrophages. High CYT is also associated with high expression of ICMs; thus, further studies to elucidate the role of CYT as a predictive biomarker of the efficacy of immune checkpoint blockade are warranted.

Human pluripotent stem cells as tools for neurodegenerative and neurodevelopmental disease modeling and drug discovery.

PubMed

Corti, Stefania; Faravelli, Irene; Cardano, Marina; Conti, Luciano

2015-06-01

Although intensive efforts have been made, effective treatments for neurodegenerative and neurodevelopmental diseases have not been yet discovered. Possible reasons for this include the lack of appropriate disease models of human neurons and a limited understanding of the etiological and neurobiological mechanisms. Recent advances in pluripotent stem cell (PSC) research have now opened the path to the generation of induced pluripotent stem cells (iPSCs) starting from somatic cells, thus offering an unlimited source of patient-specific disease-relevant neuronal cells. In this review, the authors focus on the use of human PSC-derived cells in modeling neurological disorders and discovering of new drugs and provide their expert perspectives on the field. The advent of human iPSC-based disease models has fuelled renewed enthusiasm and enormous expectations for insights of disease mechanisms and identification of more disease-relevant and novel molecular targets. Human PSCs offer a unique tool that is being profitably exploited for high-throughput screening (HTS) platforms. This process can lead to the identification and optimization of molecules/drugs and thus move forward new pharmacological therapies for a wide range of neurodegenerative and neurodevelopmental conditions. It is predicted that improvements in the production of mature neuronal subtypes, from patient-specific human-induced pluripotent stem cells and their adaptation to culture, to HTS platforms will allow the increased exploitation of human pluripotent stem cells in drug discovery programs.

A modular cell-based biosensor using engineered genetic logic circuits to detect and integrate multiple environmental signals

PubMed Central

Wang, Baojun; Barahona, Mauricio; Buck, Martin

2013-01-01

Cells perceive a wide variety of cellular and environmental signals, which are often processed combinatorially to generate particular phenotypic responses. Here, we employ both single and mixed cell type populations, pre-programmed with engineered modular cell signalling and sensing circuits, as processing units to detect and integrate multiple environmental signals. Based on an engineered modular genetic AND logic gate, we report the construction of a set of scalable synthetic microbe-based biosensors comprising exchangeable sensory, signal processing and actuation modules. These cellular biosensors were engineered using distinct signalling sensory modules to precisely identify various chemical signals, and combinations thereof, with a quantitative fluorescent output. The genetic logic gate used can function as a biological filter and an amplifier to enhance the sensing selectivity and sensitivity of cell-based biosensors. In particular, an Escherichia coli consortium-based biosensor has been constructed that can detect and integrate three environmental signals (arsenic, mercury and copper ion levels) via either its native two-component signal transduction pathways or synthetic signalling sensors derived from other bacteria in combination with a cell-cell communication module. We demonstrate how a modular cell-based biosensor can be engineered predictably using exchangeable synthetic gene circuit modules to sense and integrate multiple-input signals. This study illustrates some of the key practical design principles required for the future application of these biosensors in broad environmental and healthcare areas. PMID:22981411

Catching on it early: Bodily and brain anticipatory mechanisms for excellence in sport.

PubMed

Abreu, Ana M; Candidi, Matteo; Aglioti, Salvatore M

2017-01-01

Programming and executing a subsequent move is inherently linked to the ability to anticipate the actions of others when interacting. Such fundamental social ability is particularly important in sport. Here, we discuss the possible mechanisms behind the highly sophisticated anticipation skills that characterize experts. We contend that prediction in sports might rely on a finely tuned perceptual system that endows experts with a fast, partially unconscious, pickup of relevant cues. Furthermore, we discuss the role of the multimodal, perceptuomotor, multiple-duty cells (mirror neurons) that play an important function in action anticipation by means of an inner motor simulation process. Finally, we suggest the role of predictive coding, interoception, and the enteric nervous system as the processual and biological support for intuition and "gut feelings" in sports-the missing link that might explain outstanding expert performance based on action anticipation. © 2017 Elsevier B.V. All rights reserved.

A genetic programming approach to oral cancer prognosis.

PubMed

Tan, Mei Sze; Tan, Jing Wei; Chang, Siow-Wee; Yap, Hwa Jen; Abdul Kareem, Sameem; Zain, Rosnah Binti

2016-01-01

The potential of genetic programming (GP) on various fields has been attained in recent years. In bio-medical field, many researches in GP are focused on the recognition of cancerous cells and also on gene expression profiling data. In this research, the aim is to study the performance of GP on the survival prediction of a small sample size of oral cancer prognosis dataset, which is the first study in the field of oral cancer prognosis. GP is applied on an oral cancer dataset that contains 31 cases collected from the Malaysia Oral Cancer Database and Tissue Bank System (MOCDTBS). The feature subsets that is automatically selected through GP were noted and the influences of this subset on the results of GP were recorded. In addition, a comparison between the GP performance and that of the Support Vector Machine (SVM) and logistic regression (LR) are also done in order to verify the predictive capabilities of the GP. The result shows that GP performed the best (average accuracy of 83.87% and average AUROC of 0.8341) when the features selected are smoking, drinking, chewing, histological differentiation of SCC, and oncogene p63. In addition, based on the comparison results, we found that the GP outperformed the SVM and LR in oral cancer prognosis. Some of the features in the dataset are found to be statistically co-related. This is because the accuracy of the GP prediction drops when one of the feature in the best feature subset is excluded. Thus, GP provides an automatic feature selection function, which chooses features that are highly correlated to the prognosis of oral cancer. This makes GP an ideal prediction model for cancer clinical and genomic data that can be used to aid physicians in their decision making stage of diagnosis or prognosis.

Rocket exhaust effluent modeling for tropospheric air quality and environmental assessments

NASA Technical Reports Server (NTRS)

Stephens, J. B.; Stewart, R. B.

1977-01-01

The various techniques for diffusion predictions to support air quality predictions and environmental assessments for aerospace applications are discussed in terms of limitations imposed by atmospheric data. This affords an introduction to the rationale behind the selection of the National Aeronautics and Space Administration (NASA)/Marshall Space Flight Center (MSFC) Rocket Exhaust Effluent Diffusion (REED) program. The models utilized in the NASA/MSFC REED program are explained. This program is then evaluated in terms of some results from a joint MSFC/Langley Research Center/Kennedy Space Center Titan Exhaust Effluent Prediction and Monitoring Program.

Longitudinal Aerodynamic Modeling of the Adaptive Compliant Trailing Edge Flaps on a GIII Airplane and Comparisons to Flight Data

NASA Technical Reports Server (NTRS)

Smith, Mark S.; Bui, Trong T.; Garcia, Christian A.; Cumming, Stephen B.

2016-01-01

A pair of compliant trailing edge flaps was flown on a modified GIII airplane. Prior to flight test, multiple analysis tools of various levels of complexity were used to predict the aerodynamic effects of the flaps. Vortex lattice, full potential flow, and full Navier-Stokes aerodynamic analysis software programs were used for prediction, in addition to another program that used empirical data. After the flight-test series, lift and pitching moment coefficient increments due to the flaps were estimated from flight data and compared to the results of the predictive tools. The predicted lift increments matched flight data well for all predictive tools for small flap deflections. All tools over-predicted lift increments for large flap deflections. The potential flow and Navier-Stokes programs predicted pitching moment coefficient increments better than the other tools.

Programmed Cell Death During Caenorhabditis elegans Development

PubMed Central

Conradt, Barbara; Wu, Yi-Chun; Xue, Ding

2016-01-01

Programmed cell death is an integral component of Caenorhabditis elegans development. Genetic and reverse genetic studies in C. elegans have led to the identification of many genes and conserved cell death pathways that are important for the specification of which cells should live or die, the activation of the suicide program, and the dismantling and removal of dying cells. Molecular, cell biological, and biochemical studies have revealed the underlying mechanisms that control these three phases of programmed cell death. In particular, the interplay of transcriptional regulatory cascades and networks involving multiple transcriptional regulators is crucial in activating the expression of the key death-inducing gene egl-1 and, in some cases, the ced-3 gene in cells destined to die. A protein interaction cascade involving EGL-1, CED-9, CED-4, and CED-3 results in the activation of the key cell death protease CED-3, which is tightly controlled by multiple positive and negative regulators. The activation of the CED-3 caspase then initiates the cell disassembly process by cleaving and activating or inactivating crucial CED-3 substrates; leading to activation of multiple cell death execution events, including nuclear DNA fragmentation, mitochondrial elimination, phosphatidylserine externalization, inactivation of survival signals, and clearance of apoptotic cells. Further studies of programmed cell death in C. elegans will continue to advance our understanding of how programmed cell death is regulated, activated, and executed in general. PMID:27516615

Prediction of B-cell linear epitopes with a combination of support vector machine classification and amino acid propensity identification.

PubMed

Wang, Hsin-Wei; Lin, Ya-Chi; Pai, Tun-Wen; Chang, Hao-Teng

2011-01-01

Epitopes are antigenic determinants that are useful because they induce B-cell antibody production and stimulate T-cell activation. Bioinformatics can enable rapid, efficient prediction of potential epitopes. Here, we designed a novel B-cell linear epitope prediction system called LEPS, Linear Epitope Prediction by Propensities and Support Vector Machine, that combined physico-chemical propensity identification and support vector machine (SVM) classification. We tested the LEPS on four datasets: AntiJen, HIV, a newly generated PC, and AHP, a combination of these three datasets. Peptides with globally or locally high physicochemical propensities were first identified as primitive linear epitope (LE) candidates. Then, candidates were classified with the SVM based on the unique features of amino acid segments. This reduced the number of predicted epitopes and enhanced the positive prediction value (PPV). Compared to four other well-known LE prediction systems, the LEPS achieved the highest accuracy (72.52%), specificity (84.22%), PPV (32.07%), and Matthews' correlation coefficient (10.36%).

Assessment of programmed death-ligand 1 expression and tumor-associated immune cells in pediatric cancer tissues.

PubMed

Majzner, Robbie G; Simon, Jason S; Grosso, Joseph F; Martinez, Daniel; Pawel, Bruce R; Santi, Mariarita; Merchant, Melinda S; Geoerger, Birgit; Hezam, Imene; Marty, Virginie; Vielh, Phillippe; Daugaard, Mads; Sorensen, Poul H; Mackall, Crystal L; Maris, John M

2017-10-01

Programmed death 1 (PD-1) signaling in the tumor microenvironment dampens immune responses to cancer, and blocking this axis induces antitumor effects in several malignancies. Clinical studies of PD-1 blockade are only now being initiated in pediatric patients, and little is known regarding programmed death-ligand 1 (PD-L1) expression in common childhood cancers. The authors characterized PD-L1 expression and tumor-associated immune cells (TAICs) (lymphocytes and macrophages) in common pediatric cancers. Whole slide sections and tissue microarrays were evaluated by immunohistochemistry for PD-L1 expression and for the presence of TAICs. TAICs were also screened for PD-L1 expression. Thirty-nine of 451 evaluable tumors (9%) expressed PD-L1 in at least 1% of tumor cells. The highest frequency histotypes comprised Burkitt lymphoma (80%; 8 of 10 tumors), glioblastoma multiforme (36%; 5 of 14 tumors), and neuroblastoma (14%; 17 of 118 tumors). PD-L1 staining was associated with inferior survival among patients with neuroblastoma (P = .004). Seventy-four percent of tumors contained lymphocytes and/or macrophages. Macrophages were significantly more likely to be identified in PD-L1-positive versus PD-L1-negative tumors (P < .001). A subset of diagnostic pediatric cancers exhibit PD-L1 expression, whereas a much larger fraction demonstrates infiltration with tumor-associated lymphocytes. PD-L1 expression may be a biomarker for poor outcome in neuroblastoma. Further preclinical and clinical investigation will define the predictive nature of PD-L1 expression in childhood cancers both at diagnosis and after exposure to chemoradiotherapy. Cancer 2017;123:3807-3815. © 2017 American Cancer Society. © 2017 American Cancer Society.

A Transcriptional Program for Arbuscule Degeneration during AM Symbiosis Is Regulated by MYB1.

PubMed

Floss, Daniela S; Gomez, S Karen; Park, Hee-Jin; MacLean, Allyson M; Müller, Lena M; Bhattarai, Kishor K; Lévesque-Tremblay, Veronique; Maldonado-Mendoza, Ignacio E; Harrison, Maria J

2017-04-24

During the endosymbiosis formed between plants and arbuscular mycorrhizal (AM) fungi, the root cortical cells are colonized by branched hyphae called arbuscules, which function in nutrient exchange with the plant [1]. Despite their positive function, arbuscules are ephemeral structures, and their development is followed by a degeneration phase, in which the arbuscule and surrounding periarbuscular membrane and matrix gradually disappear from the root cell [2, 3]. Currently, the root cell's role in this process and the underlying regulatory mechanisms are unknown. Here, by using a Medicago truncatula pt4 mutant in which arbuscules degenerate prematurely [4], we identified arbuscule degeneration-associated genes, of which 38% are predicted to encode secreted hydrolases, suggesting a role in disassembly of the arbuscule and interface. Through RNAi and analysis of an insertion mutant, we identified a symbiosis-specific MYB-like transcription factor (MYB1) that suppresses arbuscule degeneration in mtpt4. In myb1, expression of several degeneration-associated genes is reduced. Conversely, in roots constitutively overexpressing MYB1, expression of degeneration-associated genes is increased and subsequent development of symbiosis is impaired. MYB1-regulated gene expression is enhanced by DELLA proteins and is dependent on NSP1 [5], but not NSP2 [6]. Furthermore, MYB1 interacts with DELLA and NSP1. Our data identify a transcriptional program for arbuscule degeneration and reveal that its regulators include MYB1 in association with two transcriptional regulators, NSP1 and DELLA, both of which function in preceding phases of the symbiosis. We propose that the combinatorial use of transcription factors enables the sequential expression of transcriptional programs for arbuscule development and degeneration. Copyright © 2017 Elsevier Ltd. All rights reserved.

Herpes Simplex Virus 1 (HSV-1) and HSV-2 Mediate Species-Specific Modulations of Programmed Necrosis through the Viral Ribonucleotide Reductase Large Subunit R1

PubMed Central

Yu, Xiaoliang; Li, Yun; Chen, Qin; Su, Chenhe; Zhang, Zili; Yang, Chengkui; Hu, Zhilin; Hou, Jue; Zhou, Jinying; Gong, Ling; Jiang, Xuejun

2015-01-01

ABSTRACT Receptor-interacting protein kinase 3 (RIP3) and its substrate mixed-lineage kinase domain-like protein (MLKL) are core regulators of programmed necrosis. The elimination of pathogen-infected cells by programmed necrosis acts as an important host defense mechanism. Here, we report that human herpes simplex virus 1 (HSV-1) and HSV-2 had opposite impacts on programmed necrosis in human cells versus their impacts in mouse cells. Similar to HSV-1, HSV-2 infection triggered programmed necrosis in mouse cells. However, neither HSV-1 nor HSV-2 infection was able to induce programmed necrosis in human cells. Moreover, HSV-1 or HSV-2 infection in human cells blocked tumor necrosis factor (TNF)-induced necrosis by preventing the induction of an RIP1/RIP3 necrosome. The HSV ribonucleotide reductase large subunit R1 was sufficient to suppress TNF-induced necrosis, and its RIP homotypic interaction motif (RHIM) domain was required to disrupt the RIP1/RIP3 complex in human cells. Therefore, this study provides evidence that HSV has likely evolved strategies to evade the host defense mechanism of programmed necrosis in human cells. IMPORTANCE This study demonstrated that infection with HSV-1 and HSV-2 blocked TNF-induced necrosis in human cells while these viruses directly activated programmed necrosis in mouse cells. Expression of HSV R1 suppressed TNF-induced necrosis of human cells. The RHIM domain of R1 was essential for its association with human RIP3 and RIP1, leading to disruption of the RIP1/RIP3 complex. This study provides new insights into the species-specific modulation of programmed necrosis by HSV. PMID:26559832

Herpes Simplex Virus 1 (HSV-1) and HSV-2 Mediate Species-Specific Modulations of Programmed Necrosis through the Viral Ribonucleotide Reductase Large Subunit R1.

PubMed

Yu, Xiaoliang; Li, Yun; Chen, Qin; Su, Chenhe; Zhang, Zili; Yang, Chengkui; Hu, Zhilin; Hou, Jue; Zhou, Jinying; Gong, Ling; Jiang, Xuejun; Zheng, Chunfu; He, Sudan

2016-01-15

Receptor-interacting protein kinase 3 (RIP3) and its substrate mixed-lineage kinase domain-like protein (MLKL) are core regulators of programmed necrosis. The elimination of pathogen-infected cells by programmed necrosis acts as an important host defense mechanism. Here, we report that human herpes simplex virus 1 (HSV-1) and HSV-2 had opposite impacts on programmed necrosis in human cells versus their impacts in mouse cells. Similar to HSV-1, HSV-2 infection triggered programmed necrosis in mouse cells. However, neither HSV-1 nor HSV-2 infection was able to induce programmed necrosis in human cells. Moreover, HSV-1 or HSV-2 infection in human cells blocked tumor necrosis factor (TNF)-induced necrosis by preventing the induction of an RIP1/RIP3 necrosome. The HSV ribonucleotide reductase large subunit R1 was sufficient to suppress TNF-induced necrosis, and its RIP homotypic interaction motif (RHIM) domain was required to disrupt the RIP1/RIP3 complex in human cells. Therefore, this study provides evidence that HSV has likely evolved strategies to evade the host defense mechanism of programmed necrosis in human cells. This study demonstrated that infection with HSV-1 and HSV-2 blocked TNF-induced necrosis in human cells while these viruses directly activated programmed necrosis in mouse cells. Expression of HSV R1 suppressed TNF-induced necrosis of human cells. The RHIM domain of R1 was essential for its association with human RIP3 and RIP1, leading to disruption of the RIP1/RIP3 complex. This study provides new insights into the species-specific modulation of programmed necrosis by HSV. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Air Force Ni-Cd cell qualification program update

NASA Technical Reports Server (NTRS)

Hall, Steve; Brown, Harry; Collins, G.; Hwang, W.; Bui, Q.

1993-01-01

The generic qualification of aerospace nickel-cadmium cells is discussed. The test program includes the following: all available manufacturers, all available designs, cells from the previous program, and high and low orbit life cycling. It is the purpose of this program to characterize the beginning of life performance.

BAX Inhibitor-1, an ancient cell death suppressor in animals and plants with prokaryotic relatives.

PubMed

Hückelhoven, R

2004-05-01

BAX Inhibitor-1 (BI-1) was originally described as testis enhanced gene transcript in mammals. Functional screening in yeast for human proteins that can inhibit the cell death provoking function of BAX, a proapoptotic Bcl-2 family member, led to functional characterisation and renaming of BI-1. The identification of functional homologues of BI-1 in plants and yeast widened the understanding of BI-1 function as an ancient suppressor of programmed cell death. BI-1 is one of the few cell death suppressors conserved in animals and plants. Computer predictions and experimental data together suggest that BI-1 is a membrane spanning protein with 6 to 7 transmembrane domains and a cytoplasmic C-terminus sticking in the endoplasmatic reticulum and nuclear envelope. Proteins similar to BI-1 are present in other eukaryotes, bacteria, and even viruses encode BI-1 like proteins. BI-1 is involved in development, response to biotic and abiotic stress and probably represents an indispensable cell protectant. BI-1 appears to suppress cell death induced by mitochondrial dysfunction, reactive oxygen species or elevated cytosolic Ca(2+) levels. This review focuses on the present understanding about BI-1 and suggests potential directions for further analyses of this increasingly noticed protein.

Long terms trends in CD4+ cell counts, CD8+ cell counts, and the CD4+ : CD8+ ratio

PubMed Central

Hughes, Rachael A.; May, Margaret T.; Tilling, Kate; Taylor, Ninon; Wittkop, Linda; Reiss, Peter; Gill, John; Schommers, Philipp; Costagliola, Dominique; Guest, Jodie L.; Lima, Viviane D.; d’Arminio Monforte, Antonella; Smith, Colette; Cavassini, Matthias; Saag, Michael; Castilho, Jessica L.; Sterne, Jonathan A.C.

2018-01-01

Objective: Model trajectories of CD4+ and CD8+ cell counts after starting combination antiretroviral therapy (ART) and use the model to predict trends in these counts and the CD4+ : CD8+ ratio. Design: Cohort study of antiretroviral-naïve HIV-positive adults who started ART after 1997 (ART Cohort Collaboration) with more than 6 months of follow-up data. Methods: We jointly estimated CD4+ and CD8+ cell count trends and their correlation using a bivariate random effects model, with linear splines describing their population trends, and predicted the CD4+ : CD8+ ratio trend from this model. We assessed whether CD4+ and CD8+ cell count trends and the CD4+ : CD8+ ratio trend varied according to CD4+ cell count at start of ART (baseline), and, whether these trends differed in patients with and without virological failure more than 6 months after starting ART. Results: A total of 39 979 patients were included (median follow-up was 53 months). Among patients with baseline CD4+ cell count at least 50 cells/μl, predicted mean CD8+ cell counts continued to decrease between 3 and 15 years post-ART, partly driving increases in the predicted mean CD4+ : CD8+ ratio. During 15 years of follow-up, normalization of the predicted mean CD4+ : CD8+ ratio (to >1) was only observed among patients with baseline CD4+ cell count at least 200 cells/μl. A higher baseline CD4+ cell count predicted a shorter time to normalization. Conclusion: Declines in CD8+ cell count and increases in CD4+ : CD8+ ratio occurred up to 15 years after starting ART. The likelihood of normalization of the CD4+ : CD8+ ratio is strongly related to baseline CD4+ cell count. PMID:29851663

Cell Culture as an Alternative in Education.

ERIC Educational Resources Information Center

Nardone, Roland M.

1990-01-01

Programs that are intended to inform and provide "hands-on" experience for students and to facilitate the introduction of cell culture-based laboratory exercises into the high school and college laboratory are examined. The components of the CellServ Program and the Cell Culture Toxicology Training Programs are described. (KR)

High fat programming of beta cell compensation, exhaustion, death and dysfunction.

PubMed

Cerf, Marlon E

2015-03-01

Programming refers to events during critical developmental windows that shape progeny health outcomes. Fetal programming refers to the effects of intrauterine (in utero) events. Lactational programming refers to the effects of events during suckling (weaning). Developmental programming refers to the effects of events during both fetal and lactational life. Postnatal programming refers to the effects of events either from birth (lactational life) to adolescence or from weaning (end of lactation) to adolescence. Islets are most plastic during the early life course; hence programming during fetal and lactational life is most potent. High fat (HF) programming is the maintenance on a HF diet (HFD) during critical developmental life stages that alters progeny metabolism and physiology. HF programming induces variable diabetogenic phenotypes dependent on the timing and duration of the dietary insult. Maternal obesity reinforces HF programming effects in progeny. HF programming, through acute hyperglycemia, initiates beta cell compensation. However, HF programming eventually leads to chronic hyperglycemia that triggers beta cell exhaustion, death and dysfunction. In HF programming, beta cell dysfunction often co-presents with insulin resistance. Balanced, healthy nutrition during developmental windows is critical for preserving beta cell structure and function. Thus early positive nutritional interventions that coincide with the development of beta cells may reduce the overwhelming burden of diabetes and metabolic disease. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

BEST: Improved Prediction of B-Cell Epitopes from Antigen Sequences

PubMed Central

Gao, Jianzhao; Faraggi, Eshel; Zhou, Yaoqi; Ruan, Jishou; Kurgan, Lukasz

2012-01-01

Accurate identification of immunogenic regions in a given antigen chain is a difficult and actively pursued problem. Although accurate predictors for T-cell epitopes are already in place, the prediction of the B-cell epitopes requires further research. We overview the available approaches for the prediction of B-cell epitopes and propose a novel and accurate sequence-based solution. Our BEST (B-cell Epitope prediction using Support vector machine Tool) method predicts epitopes from antigen sequences, in contrast to some method that predict only from short sequence fragments, using a new architecture based on averaging selected scores generated from sliding 20-mers by a Support Vector Machine (SVM). The SVM predictor utilizes a comprehensive and custom designed set of inputs generated by combining information derived from the chain, sequence conservation, similarity to known (training) epitopes, and predicted secondary structure and relative solvent accessibility. Empirical evaluation on benchmark datasets demonstrates that BEST outperforms several modern sequence-based B-cell epitope predictors including ABCPred, method by Chen et al. (2007), BCPred, COBEpro, BayesB, and CBTOPE, when considering the predictions from antigen chains and from the chain fragments. Our method obtains a cross-validated area under the receiver operating characteristic curve (AUC) for the fragment-based prediction at 0.81 and 0.85, depending on the dataset. The AUCs of BEST on the benchmark sets of full antigen chains equal 0.57 and 0.6, which is significantly and slightly better than the next best method we tested. We also present case studies to contrast the propensity profiles generated by BEST and several other methods. PMID:22761950

Cell-size distribution in epithelial tissue formation and homeostasis

PubMed Central

Primo, Luca; Celani, Antonio

2017-01-01

How cell growth and proliferation are orchestrated in living tissues to achieve a given biological function is a central problem in biology. During development, tissue regeneration and homeostasis, cell proliferation must be coordinated by spatial cues in order for cells to attain the correct size and shape. Biological tissues also feature a notable homogeneity of cell size, which, in specific cases, represents a physiological need. Here, we study the temporal evolution of the cell-size distribution by applying the theory of kinetic fragmentation to tissue development and homeostasis. Our theory predicts self-similar probability density function (PDF) of cell size and explains how division times and redistribution ensure cell size homogeneity across the tissue. Theoretical predictions and numerical simulations of confluent non-homeostatic tissue cultures show that cell size distribution is self-similar. Our experimental data confirm predictions and reveal that, as assumed in the theory, cell division times scale like a power-law of the cell size. We find that in homeostatic conditions there is a stationary distribution with lognormal tails, consistently with our experimental data. Our theoretical predictions and numerical simulations show that the shape of the PDF depends on how the space inherited by apoptotic cells is redistributed and that apoptotic cell rates might also depend on size. PMID:28330988

Cell-size distribution in epithelial tissue formation and homeostasis.

PubMed

Puliafito, Alberto; Primo, Luca; Celani, Antonio

2017-03-01

How cell growth and proliferation are orchestrated in living tissues to achieve a given biological function is a central problem in biology. During development, tissue regeneration and homeostasis, cell proliferation must be coordinated by spatial cues in order for cells to attain the correct size and shape. Biological tissues also feature a notable homogeneity of cell size, which, in specific cases, represents a physiological need. Here, we study the temporal evolution of the cell-size distribution by applying the theory of kinetic fragmentation to tissue development and homeostasis. Our theory predicts self-similar probability density function (PDF) of cell size and explains how division times and redistribution ensure cell size homogeneity across the tissue. Theoretical predictions and numerical simulations of confluent non-homeostatic tissue cultures show that cell size distribution is self-similar. Our experimental data confirm predictions and reveal that, as assumed in the theory, cell division times scale like a power-law of the cell size. We find that in homeostatic conditions there is a stationary distribution with lognormal tails, consistently with our experimental data. Our theoretical predictions and numerical simulations show that the shape of the PDF depends on how the space inherited by apoptotic cells is redistributed and that apoptotic cell rates might also depend on size. © 2017 The Author(s).

Factors leading to different viability predictions for a grizzly bear data set

USGS Publications Warehouse

Mills, L.S.; Hayes, S.G.; Wisdom, M.J.; Citta, J.; Mattson, D.J.; Murphy, K.

1996-01-01

Population viability analysis programs are being used increasingly in research and management applications, but there has not been a systematic study of the congruence of different program predictions based on a single data set. We performed such an analysis using four population viability analysis computer programs: GAPPS, INMAT, RAMAS/AGE, and VORTEX. The standardized demographic rates used in all programs were generalized from hypothetical increasing and decreasing grizzly bear (Ursus arctos horribilis) populations. Idiosyncracies of input format for each program led to minor differences in intrinsic growth rates that translated into striking differences in estimates of extinction rates and expected population size. In contrast, the addition of demographic stochasticity, environmental stochasticity, and inbreeding costs caused only a small divergence in viability predictions. But, the addition of density dependence caused large deviations between the programs despite our best attempts to use the same density-dependent functions. Population viability programs differ in how density dependence is incorporated, and the necessary functions are difficult to parameterize accurately. Thus, we recommend that unless data clearly suggest a particular density-dependent model, predictions based on population viability analysis should include at least one scenario without density dependence. Further, we describe output metrics that may differ between programs; development of future software could benefit from standardized input and output formats across different programs.

Predicting subcellular location of apoptosis proteins based on wavelet transform and support vector machine.

PubMed

Qiu, Jian-Ding; Luo, San-Hua; Huang, Jian-Hua; Sun, Xing-Yu; Liang, Ru-Ping

2010-04-01

Apoptosis proteins have a central role in the development and homeostasis of an organism. These proteins are very important for understanding the mechanism of programmed cell death. As a result of genome and other sequencing projects, the gap between the number of known apoptosis protein sequences and the number of known apoptosis protein structures is widening rapidly. Because of this extremely unbalanced state, it would be worthwhile to develop a fast and reliable method to identify their subcellular locations so as to gain better insight into their biological functions. In view of this, a new method, in which the support vector machine combines with discrete wavelet transform, has been developed to predict the subcellular location of apoptosis proteins. The results obtained by the jackknife test were quite promising, and indicated that the proposed method can remarkably improve the prediction accuracy of subcellular locations, and might also become a useful high-throughput tool in characterizing other attributes of proteins, such as enzyme class, membrane protein type, and nuclear receptor subfamily according to their sequences.

Embryonic transcription factor expression in mice predicts medial amygdala neuronal identity and sex-specific responses to innate behavioral cues

PubMed Central

Lischinsky, Julieta E; Sokolowski, Katie; Li, Peijun; Esumi, Shigeyuki; Kamal, Yasmin; Goodrich, Meredith; Oboti, Livio; Hammond, Timothy R; Krishnamoorthy, Meera; Feldman, Daniel; Huntsman, Molly; Liu, Judy; Corbin, Joshua G

2017-01-01

The medial subnucleus of the amygdala (MeA) plays a central role in processing sensory cues required for innate behaviors. However, whether there is a link between developmental programs and the emergence of inborn behaviors remains unknown. Our previous studies revealed that the telencephalic preoptic area (POA) embryonic niche is a novel source of MeA destined progenitors. Here, we show that the POA is comprised of distinct progenitor pools complementarily marked by the transcription factors Dbx1 and Foxp2. As determined by molecular and electrophysiological criteria this embryonic parcellation predicts postnatal MeA inhibitory neuronal subtype identity. We further find that Dbx1-derived and Foxp2+ cells in the MeA are differentially activated in response to innate behavioral cues in a sex-specific manner. Thus, developmental transcription factor expression is predictive of MeA neuronal identity and sex-specific neuronal responses, providing a potential developmental logic for how innate behaviors could be processed by different MeA neuronal subtypes. DOI: http://dx.doi.org/10.7554/eLife.21012.001 PMID:28244870

Towards Engineering Biological Systems in a Broader Context.

PubMed

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

2016-02-27

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

Individual Factors Predicting Mental Health Court Diversion Outcome

ERIC Educational Resources Information Center

Verhaaff, Ashley; Scott, Hannah

2015-01-01

Objective: This study examined which individual factors predict mental health court diversion outcome among a sample of persons with mental illness participating in a postcharge diversion program. Method: The study employed secondary analysis of existing program records for 419 persons with mental illness in a court diversion program. Results:…

Plasmonic Light Trapping in Thin-Film Solar Cells: Impact of Modeling on Performance Prediction

PubMed Central

Micco, Alberto; Pisco, Marco; Ricciardi, Armando; Mercaldo, Lucia V.; Usatii, Iurie; La Ferrara, Vera; Delli Veneri, Paola; Cutolo, Antonello; Cusano, Andrea

2015-01-01

We present a comparative study on numerical models used to predict the absorption enhancement in thin-film solar cells due to the presence of structured back-reflectors exciting, at specific wavelengths, hybrid plasmonic-photonic resonances. To evaluate the effectiveness of the analyzed models, they have been applied in a case study: starting from a U-shaped textured glass thin-film, µc-Si:H solar cells have been successfully fabricated. The fabricated cells, with different intrinsic layer thicknesses, have been morphologically, optically and electrically characterized. The experimental results have been successively compared with the numerical predictions. We have found that, in contrast to basic models based on the underlying schematics of the cell, numerical models taking into account the real morphology of the fabricated device, are able to effectively predict the cells performances in terms of both optical absorption and short-circuit current values.

Coiled-coil protein composition of 22 proteomes--differences and common themes in subcellular infrastructure and traffic control.

PubMed

Rose, Annkatrin; Schraegle, Shannon J; Stahlberg, Eric A; Meier, Iris

2005-11-16

Long alpha-helical coiled-coil proteins are involved in diverse organizational and regulatory processes in eukaryotic cells. They provide cables and networks in the cyto- and nucleoskeleton, molecular scaffolds that organize membrane systems and tissues, motors, levers, rotating arms, and possibly springs. Mutations in long coiled-coil proteins have been implemented in a growing number of human diseases. Using the coiled-coil prediction program MultiCoil, we have previously identified all long coiled-coil proteins from the model plant Arabidopsis thaliana and have established a searchable Arabidopsis coiled-coil protein database. Here, we have identified all proteins with long coiled-coil domains from 21 additional fully sequenced genomes. Because regions predicted to form coiled-coils interfere with sequence homology determination, we have developed a sequence comparison and clustering strategy based on masking predicted coiled-coil domains. Comparing and grouping all long coiled-coil proteins from 22 genomes, the kingdom-specificity of coiled-coil protein families was determined. At the same time, a number of proteins with unknown function could be grouped with already characterized proteins from other organisms. MultiCoil predicts proteins with extended coiled-coil domains (more than 250 amino acids) to be largely absent from bacterial genomes, but present in archaea and eukaryotes. The structural maintenance of chromosomes proteins and their relatives are the only long coiled-coil protein family clearly conserved throughout all kingdoms, indicating their ancient nature. Motor proteins, membrane tethering and vesicle transport proteins are the dominant eukaryote-specific long coiled-coil proteins, suggesting that coiled-coil proteins have gained functions in the increasingly complex processes of subcellular infrastructure maintenance and trafficking control of the eukaryotic cell.

Coiled-coil protein composition of 22 proteomes – differences and common themes in subcellular infrastructure and traffic control

PubMed Central

Rose, Annkatrin; Schraegle, Shannon J; Stahlberg, Eric A; Meier, Iris

2005-01-01

Background Long alpha-helical coiled-coil proteins are involved in diverse organizational and regulatory processes in eukaryotic cells. They provide cables and networks in the cyto- and nucleoskeleton, molecular scaffolds that organize membrane systems and tissues, motors, levers, rotating arms, and possibly springs. Mutations in long coiled-coil proteins have been implemented in a growing number of human diseases. Using the coiled-coil prediction program MultiCoil, we have previously identified all long coiled-coil proteins from the model plant Arabidopsis thaliana and have established a searchable Arabidopsis coiled-coil protein database. Results Here, we have identified all proteins with long coiled-coil domains from 21 additional fully sequenced genomes. Because regions predicted to form coiled-coils interfere with sequence homology determination, we have developed a sequence comparison and clustering strategy based on masking predicted coiled-coil domains. Comparing and grouping all long coiled-coil proteins from 22 genomes, the kingdom-specificity of coiled-coil protein families was determined. At the same time, a number of proteins with unknown function could be grouped with already characterized proteins from other organisms. Conclusion MultiCoil predicts proteins with extended coiled-coil domains (more than 250 amino acids) to be largely absent from bacterial genomes, but present in archaea and eukaryotes. The structural maintenance of chromosomes proteins and their relatives are the only long coiled-coil protein family clearly conserved throughout all kingdoms, indicating their ancient nature. Motor proteins, membrane tethering and vesicle transport proteins are the dominant eukaryote-specific long coiled-coil proteins, suggesting that coiled-coil proteins have gained functions in the increasingly complex processes of subcellular infrastructure maintenance and trafficking control of the eukaryotic cell. PMID:16288662

The Coastal Ocean Prediction Systems program: Understanding and managing our coastal ocean

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

Eden, H.F.; Mooers, C.N.K.

1990-06-01

The goal of COPS is to couple a program of regular observations to numerical models, through techniques of data assimilation, in order to provide a predictive capability for the US coastal ocean including the Great Lakes, estuaries, and the entire Exclusive Economic Zone (EEZ). The objectives of the program include: determining the predictability of the coastal ocean and the processes that govern the predictability; developing efficient prediction systems for the coastal ocean based on the assimilation of real-time observations into numerical models; and coupling the predictive systems for the physical behavior of the coastal ocean to predictive systems for biological,more » chemical, and geological processes to achieve an interdisciplinary capability. COPS will provide the basis for effective monitoring and prediction of coastal ocean conditions by optimizing the use of increased scientific understanding, improved observations, advanced computer models, and computer graphics to make the best possible estimates of sea level, currents, temperatures, salinities, and other properties of entire coastal regions.« less

MLITemp: A computer program to predict the thermal effects associated with hypervelocity impact damage to space station MLI

NASA Technical Reports Server (NTRS)

Rule, W. K.; Giridharan, V.

1991-01-01

A family of user-friendly, DOS PC based, Microsoft BASIC programs written to provide spacecraft designers with empirical predictions of space debris damage to orbiting spacecraft are described. Spacecraft wall temperatures and condensate formation is also predicted. The spacecraft wall configuration is assumed to consist of multilayered insulation (MLI) placed between a Whipple style bumper and the pressure wall. Impact damage predictions are based on data sets of experimental results obtained from simulating debris impacts on spacecraft using light gas guns on earth. A module of the program facilitates the creation of the database of experimental results that is used by the damage prediction modules to predict damage to the bumper, the MLI, and the pressure wall. A finite difference technique is used to predict temperature distributions in the pressure wall, the MLI, and the bumper. Condensate layer thickness is predicted for the case where the pressure wall temperature drops below the dew point temperature of the spacecraft atmosphere.

Predictive markers for the response to 5-fluorouracil therapy in cancer cells: Constant-field gel electrophoresis as a tool for prediction of response to 5-fluorouracil-based chemotherapy

PubMed Central

SALEH, E. M.; EL-AWADY, R. A.; ANIS, N.

2013-01-01

The prediction of response or severe toxicity and therapy individualisation are extremely important in cancer chemotherapy. There are few tools to predict chemoresponse or toxicity in cancer patients. We investigated the correlation between the induction and repair of DNA double-strand breaks (DSBs) using constant-field gel electrophoresis (CFGE) and evaluating cell cycle progression and the sensitivity of four cancer cell lines to 5-fluorouracil (5FU). Using a sulphorhodamine-B assay, colon carcinoma cells (HCT116) were found to be the most sensitive to 5FU, followed by liver carcinoma cells (HepG2) and breast carcinoma cells (MCF-7). Cervical carcinoma cells (HeLa) were the most resistant. As measured by CFGE, DSB induction, but not residual DSBs, exhibited a significant correlation with the sensitivity of the cell lines to 5FU. Flow cytometric cell cycle analysis revealed that 14% of HCT116 or HepG2 cells and 2% of MCF-7 cells shifted to sub-G1 phase after a 96-h incubation with 5FU. Another 5FU-induced cell cycle change in HCT116, HepG2 and MCF-7 cells was the mild arrest of cells in G1 and/or G2/M phases of the cell cycle. In addition, 5FU treatment resulted in the accumulation of HeLa cells in the S and G2/M phases. Determination of Fas ligand (Fas-L) and caspase 9 as representative markers for the extrinsic and intrinsic pathways of apoptosis, respectively, revealed that 5FU-induced apoptosis in HCT116 and HepG2 results from the expression of Fas-L (extrinsic pathway). Therefore, the induction of DNA DSBs by 5FU, detected using CFGE, and the induction of apoptosis are candidate predictive markers that may distinguish cancer cells which are likely to benefit from 5FU treatment and the measurement of DSBs using CFGE may aid the prediction of clinical outcome. PMID:23255942

Hierarchical maintenance of MLL myeloid leukemia stem cells employs a transcriptional program shared with embryonic rather than adult stem cells

PubMed Central

Somervaille, Tim C. P.; Matheny, Christina J.; Spencer, Gary J.; Iwasaki, Masayuki; Rinn, John L.; Witten, Daniela M.; Chang, Howard Y.; Shurtleff, Sheila A.; Downing, James R.; Cleary, Michael L.

2009-01-01

Summary The genetic programs that promote retention of self-renewing leukemia stem cells (LSCs) at the apex of cellular hierarchies in acute myeloid leukemia (AML) are not known. In a mouse model of human AML, LSCs exhibit variable frequencies that correlate with the initiating MLL oncogene and are maintained in a self-renewing state by a transcriptional sub-program more akin to that of embryonic stem cells (ESCs) than adult stem cells. The transcription/chromatin regulatory factors Myb, Hmgb3 and Cbx5 are critical components of the program and suffice for Hoxa/Meis-independent immortalization of myeloid progenitors when co-expressed, establishing the cooperative and essential role of an ESC-like LSC maintenance program ancillary to the leukemia initiating MLL/Hox/Meis program. Enriched expression of LSC maintenance and ESC-like program genes in normal myeloid progenitors and poor prognosis human malignancies links the frequency of aberrantly self-renewing progenitor-like cancer stem cells to prognosis in human cancer. PMID:19200802

Androgen-induced programs for prostate epithelial growth and invasion arise in embryogenesis and are reactivated in cancer

PubMed Central

Schaeffer, EM; Marchionni, L; Huang, Z; Simons, B; Blackman, A; Yu, W; Parmigiani, G; Berman, DM

2008-01-01

Cancer cells differentiate along specific lineages that largely determine their clinical and biologic behavior. Distinct cancer phenotypes from different cells and organs likely result from unique gene expression repertoires established in the embryo and maintained after malignant transformation. We used comprehensive gene expression analysis to examine this concept in the prostate, an organ with a tractable developmental program and a high propensity for cancer. We focused on gene expression in the murine prostate rudiment at three time points during the first 48 h of exposure to androgen, which initiates proliferation and invasion of prostate epithelial buds into surrounding urogenital sinus mesenchyme. Here, we show that androgen exposure regulates genes previously implicated in prostate carcinogenesis comprising pathways for the phosphatase and tensin homolog (PTEN), fibroblast growth factor (FGF)/mitogen-activated protein kinase (MAPK), and Wnt signaling along with cellular programs regulating such ‘hallmarks’ of cancer as angiogenesis, apoptosis, migration and proliferation. We found statistically significant evidence for novel androgeninduced gene regulation events that establish and/or maintain prostate cell fate. These include modulation of gene expression through microRNAs, expression of specific transcription factors, and regulation of their predicted targets. By querying public gene expression databases from other tissues, we found that rather than generally characterizing androgen exposure or epithelial budding, the early prostate development program more closely resembles the program for human prostate cancer. Most importantly, early androgen-regulated genes and functional themes associated with prostate development were highly enriched in contrasts between increasingly lethal forms of prostate cancer, confirming a ‘reactivation’ of embryonic pathways for proliferation and invasion in prostate cancer progression. Among the genes with the most significant links to the development and cancer, we highlight coordinate induction of the transcription factor Sox9 and suppression of the proapoptotic phospholipid-binding protein Annexin A1 that link early prostate development to early prostate carcinogenesis. These results credential early prostate development as a reliable and valid model system for the investigation of genes and pathways that drive prostate cancer. PMID:18794802

Synergistic binding of transcription factors to cell-specific enhancers programs motor neuron identity

PubMed Central

Mazzoni, Esteban O; Mahony, Shaun; Closser, Michael; Morrison, Carolyn A; Nedelec, Stephane; Williams, Damian J; An, Disi; Gifford, David K; Wichterle, Hynek

2013-01-01

Efficient transcriptional programming promises to open new frontiers in regenerative medicine. However, mechanisms by which programming factors transform cell fate are unknown, preventing more rational selection of factors to generate desirable cell types. Three transcription factors, Ngn2, Isl1 and Lhx3, were sufficient to program rapidly and efficiently spinal motor neuron identity when expressed in differentiating mouse embryonic stem cells. Replacement of Lhx3 by Phox2a led to specification of cranial, rather than spinal, motor neurons. Chromatin immunoprecipitation–sequencing analysis of Isl1, Lhx3 and Phox2a binding sites revealed that the two cell fates were programmed by the recruitment of Isl1-Lhx3 and Isl1-Phox2a complexes to distinct genomic locations characterized by a unique grammar of homeodomain binding motifs. Our findings suggest that synergistic interactions among transcription factors determine the specificity of their recruitment to cell type–specific binding sites and illustrate how a single transcription factor can be repurposed to program different cell types. PMID:23872598

Evaluation of solar cells and arrays for potential solar power satellite applications

NASA Technical Reports Server (NTRS)

Almgren, D. W.; Csigi, K.; Gaudet, A. D.

1978-01-01

Proposed solar array designs and manufacturing methods are evaluated to identify options which show the greatest promise of leading up to the develpment of a cost-effective SPS solar cell array design. The key program elements which have to be accomplished as part of an SPS solar cell array development program are defined. The issues focussed on are: (1) definition of one or more designs of a candidate SPS solar array module, using results from current system studies; (2) development of the necessary manufacturing requirements for the candidate SPS solar cell arrays and an assessment of the market size, timing, and industry infrastructure needed to produce the arrays for the SPS program; (3) evaluation of current DOE, NASA and DOD photovoltaic programs to determine the impacts of recent advances in solar cell materials, array designs and manufacturing technology on the candidate SPS solar cell arrays; and (4) definition of key program elements for the development of the most promising solar cell arrays for the SPS program.

A coupled diffusion-fluid pressure model to predict cell density distribution for cells encapsulated in a porous hydrogel scaffold under mechanical loading.

PubMed

Zhao, Feihu; Vaughan, Ted J; Mc Garrigle, Myles J; McNamara, Laoise M

2017-10-01

Tissue formation within tissue engineering (TE) scaffolds is preceded by growth of the cells throughout the scaffold volume and attachment of cells to the scaffold substrate. It is known that mechanical stimulation, in the form of fluid perfusion or mechanical strain, enhances cell differentiation and overall tissue formation. However, due to the complex multi-physics environment of cells within TE scaffolds, cell transport under mechanical stimulation is not fully understood. Therefore, in this study, we have developed a coupled multiphysics model to predict cell density distribution in a TE scaffold. In this model, cell transport is modelled as a thermal conduction process, which is driven by the pore fluid pressure under applied loading. As a case study, the model is investigated to predict the cell density patterns of pre-osteoblasts MC3T3-e1 cells under a range of different loading regimes, to obtain an understanding of desirable mechanical stimulation that will enhance cell density distribution within TE scaffolds. The results of this study have demonstrated that fluid perfusion can result in a higher cell density in the scaffold region closed to the outlet, while cell density distribution under mechanical compression was similar with static condition. More importantly, the study provides a novel computational approach to predict cell distribution in TE scaffolds under mechanical loading. Copyright © 2017 Elsevier Ltd. All rights reserved.

EP-DNN: A Deep Neural Network-Based Global Enhancer Prediction Algorithm.

PubMed

Kim, Seong Gon; Harwani, Mrudul; Grama, Ananth; Chaterji, Somali

2016-12-08

We present EP-DNN, a protocol for predicting enhancers based on chromatin features, in different cell types. Specifically, we use a deep neural network (DNN)-based architecture to extract enhancer signatures in a representative human embryonic stem cell type (H1) and a differentiated lung cell type (IMR90). We train EP-DNN using p300 binding sites, as enhancers, and TSS and random non-DHS sites, as non-enhancers. We perform same-cell and cross-cell predictions to quantify the validation rate and compare against two state-of-the-art methods, DEEP-ENCODE and RFECS. We find that EP-DNN has superior accuracy with a validation rate of 91.6%, relative to 85.3% for DEEP-ENCODE and 85.5% for RFECS, for a given number of enhancer predictions and also scales better for a larger number of enhancer predictions. Moreover, our H1 → IMR90 predictions turn out to be more accurate than IMR90 → IMR90, potentially because H1 exhibits a richer signature set and our EP-DNN model is expressive enough to extract these subtleties. Our work shows how to leverage the full expressivity of deep learning models, using multiple hidden layers, while avoiding overfitting on the training data. We also lay the foundation for exploration of cross-cell enhancer predictions, potentially reducing the need for expensive experimentation.

EP-DNN: A Deep Neural Network-Based Global Enhancer Prediction Algorithm

NASA Astrophysics Data System (ADS)

Kim, Seong Gon; Harwani, Mrudul; Grama, Ananth; Chaterji, Somali

2016-12-01

We present EP-DNN, a protocol for predicting enhancers based on chromatin features, in different cell types. Specifically, we use a deep neural network (DNN)-based architecture to extract enhancer signatures in a representative human embryonic stem cell type (H1) and a differentiated lung cell type (IMR90). We train EP-DNN using p300 binding sites, as enhancers, and TSS and random non-DHS sites, as non-enhancers. We perform same-cell and cross-cell predictions to quantify the validation rate and compare against two state-of-the-art methods, DEEP-ENCODE and RFECS. We find that EP-DNN has superior accuracy with a validation rate of 91.6%, relative to 85.3% for DEEP-ENCODE and 85.5% for RFECS, for a given number of enhancer predictions and also scales better for a larger number of enhancer predictions. Moreover, our H1 → IMR90 predictions turn out to be more accurate than IMR90 → IMR90, potentially because H1 exhibits a richer signature set and our EP-DNN model is expressive enough to extract these subtleties. Our work shows how to leverage the full expressivity of deep learning models, using multiple hidden layers, while avoiding overfitting on the training data. We also lay the foundation for exploration of cross-cell enhancer predictions, potentially reducing the need for expensive experimentation.

Prediction of Microbial Infection of Cultured Cells Using DNA Microarray Gene-Expression Profiles of Host Responses

PubMed Central

Park, Yu Rang; Chung, Tae Su; Lee, Young Joo; Song, Yeong Wook; Lee, Eun Young; Sohn, Yeo Won; Song, Sukgil; Park, Woong Yang

2012-01-01

Infection by microorganisms may cause fatally erroneous interpretations in the biologic researches based on cell culture. The contamination by microorganism in the cell culture is quite frequent (5% to 35%). However, current approaches to identify the presence of contamination have many limitations such as high cost of time and labor, and difficulty in interpreting the result. In this paper, we propose a model to predict cell infection, using a microarray technique which gives an overview of the whole genome profile. By analysis of 62 microarray expression profiles under various experimental conditions altering cell type, source of infection and collection time, we discovered 5 marker genes, NM_005298, NM_016408, NM_014588, S76389, and NM_001853. In addition, we discovered two of these genes, S76389, and NM_001853, are involved in a Mycolplasma-specific infection process. We also suggest models to predict the source of infection, cell type or time after infection. We implemented a web based prediction tool in microarray data, named Prediction of Microbial Infection (http://www.snubi.org/software/PMI). PMID:23091307

Improved Method for Linear B-Cell Epitope Prediction Using Antigen’s Primary Sequence

PubMed Central

Raghava, Gajendra P. S.

2013-01-01

One of the major challenges in designing a peptide-based vaccine is the identification of antigenic regions in an antigen that can stimulate B-cell’s response, also called B-cell epitopes. In the past, several methods have been developed for the prediction of conformational and linear (or continuous) B-cell epitopes. However, the existing methods for predicting linear B-cell epitopes are far from perfection. In this study, an attempt has been made to develop an improved method for predicting linear B-cell epitopes. We have retrieved experimentally validated B-cell epitopes as well as non B-cell epitopes from Immune Epitope Database and derived two types of datasets called Lbtope_Variable and Lbtope_Fixed length datasets. The Lbtope_Variable dataset contains 14876 B-cell epitope and 23321 non-epitopes of variable length where as Lbtope_Fixed length dataset contains 12063 B-cell epitopes and 20589 non-epitopes of fixed length. We also evaluated the performance of models on above datasets after removing highly identical peptides from the datasets. In addition, we have derived third dataset Lbtope_Confirm having 1042 epitopes and 1795 non-epitopes where each epitope or non-epitope has been experimentally validated in at least two studies. A number of models have been developed to discriminate epitopes and non-epitopes using different machine-learning techniques like Support Vector Machine, and K-Nearest Neighbor. We achieved accuracy from ∼54% to 86% using diverse s features like binary profile, dipeptide composition, AAP (amino acid pair) profile. In this study, for the first time experimentally validated non B-cell epitopes have been used for developing method for predicting linear B-cell epitopes. In previous studies, random peptides have been used as non B-cell epitopes. In order to provide service to scientific community, a web server LBtope has been developed for predicting and designing B-cell epitopes (http://crdd.osdd.net/raghava/lbtope/). PMID:23667458

The simulation model of growth and cell divisions for the root apex with an apical cell in application to Azolla pinnata.

PubMed

Piekarska-Stachowiak, Anna; Nakielski, Jerzy

2013-12-01

In contrast to seed plants, the roots of most ferns have a single apical cell which is the ultimate source of all cells in the root. The apical cell has a tetrahedral shape and divides asymmetrically. The root cap derives from the distal division face, while merophytes derived from three proximal division faces contribute to the root proper. The merophytes are produced sequentially forming three sectors along a helix around the root axis. During development, they divide and differentiate in a predictable pattern. Such growth causes cell pattern of the root apex to be remarkably regular and self-perpetuating. The nature of this regularity remains unknown. This paper shows the 2D simulation model for growth of the root apex with the apical cell in application to Azolla pinnata. The field of growth rates of the organ, prescribed by the model, is of a tensor type (symplastic growth) and cells divide taking principal growth directions into account. The simulations show how the cell pattern in a longitudinal section of the apex develops in time. The virtual root apex grows realistically and its cell pattern is similar to that observed in anatomical sections. The simulations indicate that the cell pattern regularity results from cell divisions which are oriented with respect to principal growth directions. Such divisions are essential for maintenance of peri-anticlinal arrangement of cell walls and coordinated growth of merophytes during the development. The highly specific division program that takes place in merophytes prior to differentiation seems to be regulated at the cellular level.

Abstracts of Presentations at Workshop on Unsteady and Two-Phase-Flows, Held in London, England on June 28-29, 1990

DTIC Science & Technology

1990-06-29

has been found to be a modification of the STAN’ program from Crawford and Kays2. An important characteristic of any boundary layer prediction program...function of freestream turbulence intensity, helped in predicting heat transfer rates between the hot gases and the b’arie surface. a Professor...be a modulator of transition to turbulence and the boundary layer prediction programs currently available have a poor performance in such flows

Using the brain's fight-or-flight response for predicting mental illness on the human space flight program

NASA Astrophysics Data System (ADS)

Losik, L.

A predictive medicine program allows disease and illness including mental illness to be predicted using tools created to identify the presence of accelerated aging (a.k.a. disease) in electrical and mechanical equipment. When illness and disease can be predicted, actions can be taken so that the illness and disease can be prevented and eliminated. A predictive medicine program uses the same tools and practices from a prognostic and health management program to process biological and engineering diagnostic data provided in analog telemetry during prelaunch readiness and space exploration missions. The biological and engineering diagnostic data necessary to predict illness and disease is collected from the pre-launch spaceflight readiness activities and during space flight for the ground crew to perform a prognostic analysis on the results from a diagnostic analysis. The diagnostic, biological data provided in telemetry is converted to prognostic (predictive) data using the predictive algorithms. Predictive algorithms demodulate telemetry behavior. They illustrate the presence of accelerated aging/disease in normal appearing systems that function normally. Mental illness can predicted using biological diagnostic measurements provided in CCSDS telemetry from a spacecraft such as the ISS or from a manned spacecraft in deep space. The measurements used to predict mental illness include biological and engineering data from an astronaut's circadian and ultranian rhythms. This data originates deep in the brain that is also damaged from the long-term exposure to cortisol and adrenaline anytime the body's fight or flight response is activated. This paper defines the brain's FOFR; the diagnostic, biological and engineering measurements needed to predict mental illness, identifies the predictive algorithms necessary to process the behavior in CCSDS analog telemetry to predict and thus prevent mental illness from occurring on human spaceflight missions.

Comparison of the Walz Nomogram and Presence of Secondary Circulating Prostate Cells for Predicting Early Biochemical Failure after Radical Prostatectomy for Prostate Cancer in Chilean Men.

PubMed

Murray, Nigel P; Reyes, Eduardo; Orellana, Nelson; Fuentealba, Cynthia; Jacob, Omar

2015-01-01

To determine the utility of secondary circulating prostate cells for predicting early biochemical failure after radical prostatectomy for prostate cancer and compare the results with the Walz nomagram. A single centre, prospective study of men with prostate cancer treated with radical prostatectomy between 2004 and 2014 was conducted, with registration of clinical-pathological details, total serum PSA pre-surgery, Gleason score, extracapsular extension, positive surgical margins, infiltration of lymph nodes, seminal vesicles and pathological stage. Secondary circulating prostate cells were obtained using differential gel centrifugation and assessed using standard immunocytochemistry with anti-PSA. Biochemical failure was defined as a PSA >0.2ng/ml, predictive values werecalculated using the Walz nomagram and CPC detection. A total of 326 men participated, with a median follow up of 5 years; 64 had biochemical failure within two years. Extracapsular extension, positive surgical margins, pathological stage, Gleason score ≥ 8, infiltration of seminal vesicles and lymph nodes were all associated with higher risk of biochemical failure. The discriminative value for the nomogram and circulating prostate cells was high (AUC >0.80), predictive values were higher for circulating prostate cell detection, with a negative predictive value of 99%, sensitivity of 96% and specificity of 75%. The nomagram had good predictive power to identify men with a high risk of biochemical failure within two years. The presence of circulating prostate cells had the same predictive power, with a higher sensitivity and negative predictive value. The presence of secondary circulating prostate cells identifies a group of men with a high risk of early biochemical failure. Those negative for secondary CPCs have a very low risk of early biochemical failure.

Validation and Use of a Predictive Modeling Tool: Employing Scientific Findings to Improve Responsible Conduct of Research Education.

PubMed

Mulhearn, Tyler J; Watts, Logan L; Todd, E Michelle; Medeiros, Kelsey E; Connelly, Shane; Mumford, Michael D

2017-01-01

Although recent evidence suggests ethics education can be effective, the nature of specific training programs, and their effectiveness, varies considerably. Building on a recent path modeling effort, the present study developed and validated a predictive modeling tool for responsible conduct of research education. The predictive modeling tool allows users to enter ratings in relation to a given ethics training program and receive instantaneous evaluative information for course refinement. Validation work suggests the tool's predicted outcomes correlate strongly (r = 0.46) with objective course outcomes. Implications for training program development and refinement are discussed.

Prediction of Combustion Gas Deposit Compositions

NASA Technical Reports Server (NTRS)

Kohl, F. J.; Mcbride, B. J.; Zeleznik, F. J.; Gordon, S.

1985-01-01

Demonstrated procedure used to predict accurately chemical compositions of complicated deposit mixtures. NASA Lewis Research Center's Computer Program for Calculation of Complex Chemical Equilibrium Compositions (CEC) used in conjunction with Computer Program for Calculation of Ideal Gas Thermodynamic Data (PAC) and resulting Thermodynamic Data Base (THDATA) to predict deposit compositions from metal or mineral-seeded combustion processes.

Multi-scale computation methods: Their applications in lithium-ion battery research and development

NASA Astrophysics Data System (ADS)

Siqi, Shi; Jian, Gao; Yue, Liu; Yan, Zhao; Qu, Wu; Wangwei, Ju; Chuying, Ouyang; Ruijuan, Xiao

2016-01-01

Based upon advances in theoretical algorithms, modeling and simulations, and computer technologies, the rational design of materials, cells, devices, and packs in the field of lithium-ion batteries is being realized incrementally and will at some point trigger a paradigm revolution by combining calculations and experiments linked by a big shared database, enabling accelerated development of the whole industrial chain. Theory and multi-scale modeling and simulation, as supplements to experimental efforts, can help greatly to close some of the current experimental and technological gaps, as well as predict path-independent properties and help to fundamentally understand path-independent performance in multiple spatial and temporal scales. Project supported by the National Natural Science Foundation of China (Grant Nos. 51372228 and 11234013), the National High Technology Research and Development Program of China (Grant No. 2015AA034201), and Shanghai Pujiang Program, China (Grant No. 14PJ1403900).

Sinusoidal voltage protocols for rapid characterisation of ion channel kinetics.

PubMed

Beattie, Kylie A; Hill, Adam P; Bardenet, Rémi; Cui, Yi; Vandenberg, Jamie I; Gavaghan, David J; de Boer, Teun P; Mirams, Gary R

2018-03-24

Ion current kinetics are commonly represented by current-voltage relationships, time constant-voltage relationships and subsequently mathematical models fitted to these. These experiments take substantial time, which means they are rarely performed in the same cell. Rather than traditional square-wave voltage clamps, we fitted a model to the current evoked by a novel sum-of-sinusoids voltage clamp that was only 8 s long. Short protocols that can be performed multiple times within a single cell will offer many new opportunities to measure how ion current kinetics are affected by changing conditions. The new model predicts the current under traditional square-wave protocols well, with better predictions of underlying currents than literature models. The current under a novel physiologically relevant series of action potential clamps is predicted extremely well. The short sinusoidal protocols allow a model to be fully fitted to individual cells, allowing us to examine cell-cell variability in current kinetics for the first time. Understanding the roles of ion currents is crucial to predict the action of pharmaceuticals and mutations in different scenarios, and thereby to guide clinical interventions in the heart, brain and other electrophysiological systems. Our ability to predict how ion currents contribute to cellular electrophysiology is in turn critically dependent on our characterisation of ion channel kinetics - the voltage-dependent rates of transition between open, closed and inactivated channel states. We present a new method for rapidly exploring and characterising ion channel kinetics, applying it to the hERG potassium channel as an example, with the aim of generating a quantitatively predictive representation of the ion current. We fitted a mathematical model to currents evoked by a novel 8 second sinusoidal voltage clamp in CHO cells overexpressing hERG1a. The model was then used to predict over 5 minutes of recordings in the same cell in response to further protocols: a series of traditional square step voltage clamps, and also a novel voltage clamp comprising a collection of physiologically relevant action potentials. We demonstrate that we can make predictive cell-specific models that outperform the use of averaged data from a number of different cells, and thereby examine which changes in gating are responsible for cell-cell variability in current kinetics. Our technique allows rapid collection of consistent and high quality data, from single cells, and produces more predictive mathematical ion channel models than traditional approaches. © 2018 The Authors. The Journal of Physiology published by John Wiley & Sons Ltd on behalf of The Physiological Society.

The Marr and Albus Theories of the Cerebellum: Two Eary Models of Associative Memory

NASA Technical Reports Server (NTRS)

Albus, James S.

1989-01-01

The Marr and Albus theories of the cerebellum are compared and contrasted. They are shown to be similar in their analysis of the function of the mossy fibers, granule cells, Golgi cells, and Purkinje cells. They both predict motor learning in the parallel fiber synapses on the Purkinje dendrites mediated by concurrent climbing fiber input. This prediction has been confirmed by experimental evidence. In contrast, Marr predicts these synapses would be facilitated by learning, while Albus predicts they would be weakened. Experimental evidence confirms synaptic weakening.

Stress Management in Cyst-Forming Free-Living Protists: Programmed Cell Death and/or Encystment

PubMed Central

Khan, Naveed Ahmed; Iqbal, Junaid

2015-01-01

In the face of harsh conditions and given a choice, a cell may (i) undergo programmed cell death, (ii) transform into a cancer cell, or (iii) enclose itself into a cyst form. In metazoans, the available evidence suggests that cellular machinery exists only to execute or avoid programmed cell death, while the ability to form a cyst was either lost or never developed. For cyst-forming free-living protists, here we pose the question whether the ability to encyst was gained at the expense of the programmed cell death or both functions coexist to counter unfavorable environmental conditions with mutually exclusive phenotypes. PMID:25648302

[A prediction model for internet game addiction in adolescents: using a decision tree analysis].

PubMed

Kim, Ki Sook; Kim, Kyung Hee

2010-06-01

This study was designed to build a theoretical frame to provide practical help to prevent and manage adolescent internet game addiction by developing a prediction model through a comprehensive analysis of related factors. The participants were 1,318 students studying in elementary, middle, and high schools in Seoul and Gyeonggi Province, Korea. Collected data were analyzed using the SPSS program. Decision Tree Analysis using the Clementine program was applied to build an optimum and significant prediction model to predict internet game addiction related to various factors, especially parent related factors. From the data analyses, the prediction model for factors related to internet game addiction presented with 5 pathways. Causative factors included gender, type of school, siblings, economic status, religion, time spent alone, gaming place, payment to Internet café, frequency, duration, parent's ability to use internet, occupation (mother), trust (father), expectations regarding adolescent's study (mother), supervising (both parents), rearing attitude (both parents). The results suggest preventive and managerial nursing programs for specific groups by path. Use of this predictive model can expand the role of school nurses, not only in counseling addicted adolescents but also, in developing and carrying out programs with parents and approaching adolescents individually through databases and computer programming.

Application of First Principles Model to Spacecraft Operations

NASA Technical Reports Server (NTRS)

Timmerman, Paul; Bugga, Ratnakumar; DiStefano, Salvidor

1996-01-01

Previous models use a single phase reaction; cycled cell predicts cannot be met with a single phase; interphase conversion provides means for film aging; aging cells predictions display typical behaviors: pressure changes in NiH² cells; voltage fading upon cycling; second plateau on discharge of cycled cells; negative limited behavior for Ni-Cds.

FLOCK cluster analysis of mast cell event clustering by high-sensitivity flow cytometry predicts systemic mastocytosis.

PubMed

Dorfman, David M; LaPlante, Charlotte D; Pozdnyakova, Olga; Li, Betty

2015-11-01

In our high-sensitivity flow cytometric approach for systemic mastocytosis (SM), we identified mast cell event clustering as a new diagnostic criterion for the disease. To objectively characterize mast cell gated event distributions, we performed cluster analysis using FLOCK, a computational approach to identify cell subsets in multidimensional flow cytometry data in an unbiased, automated fashion. FLOCK identified discrete mast cell populations in most cases of SM (56/75 [75%]) but only a minority of non-SM cases (17/124 [14%]). FLOCK-identified mast cell populations accounted for 2.46% of total cells on average in SM cases and 0.09% of total cells on average in non-SM cases (P < .0001) and were predictive of SM, with a sensitivity of 75%, a specificity of 86%, a positive predictive value of 76%, and a negative predictive value of 85%. FLOCK analysis provides useful diagnostic information for evaluating patients with suspected SM, and may be useful for the analysis of other hematopoietic neoplasms. Copyright© by the American Society for Clinical Pathology.

Multi-Node Thermal System Model for Lithium-Ion Battery Packs: Preprint

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

Shi, Ying; Smith, Kandler; Wood, Eric

Temperature is one of the main factors that controls the degradation in lithium ion batteries. Accurate knowledge and control of cell temperatures in a pack helps the battery management system (BMS) to maximize cell utilization and ensure pack safety and service life. In a pack with arrays of cells, a cells temperature is not only affected by its own thermal characteristics but also by its neighbors, the cooling system and pack configuration, which increase the noise level and the complexity of cell temperatures prediction. This work proposes to model lithium ion packs thermal behavior using a multi-node thermal network model,more » which predicts the cell temperatures by zones. The model was parametrized and validated using commercial lithium-ion battery packs. neighbors, the cooling system and pack configuration, which increase the noise level and the complexity of cell temperatures prediction. This work proposes to model lithium ion packs thermal behavior using a multi-node thermal network model, which predicts the cell temperatures by zones. The model was parametrized and validated using commercial lithium-ion battery packs.« less

Simulated selection responses for breeding programs including resistance and resilience to parasites in Creole goats.

PubMed

Gunia, M; Phocas, F; Gourdine, J-L; Bijma, P; Mandonnet, N

2013-02-01

The Creole goat is a local breed used for meat production in Guadeloupe (French West Indies). As in other tropical countries, improvement of parasite resistance is needed. In this study, we compared predicted selection responses for alternative breeding programs with or without parasite resistance and resilience traits. The overall breeding goal included traits for production, reproduction, and parasite resilience and resistance to ensure a balanced selection outcome. The production traits were BW and dressing percentage (DP). The reproduction trait was fertility (FER), which was the number of doe kiddings per mating. The resistance trait was worm fecal egg count (FEC), which is a measurement of the number of gastro-intestinal parasite eggs found in the feces. The resilience trait was the packed cell volume (PCV), which is a measurement of the volume of red blood cells in the blood. Dressing percentage, BW, and FEC were measured at 11 mo of age, which is the mating or selling age. Fertility and PCV were measured on females at each kidding period. The breeding program accounting for the overall breeding goal and a selection index including all traits gave annual selection responses of 800 g for BW, 3.75% for FER, 0.08% for DP, -0.005 ln(eggs/g) for FEC, and 0.28% for PCV. The expected selection responses for BW and DP in this breeding program were reduced by 2% and 6%, respectively, compared with a breeding program not accounting for FEC and PCV. The overall breeding program, proposed for the Creole breed, offers the best breeding strategy in terms of expected selection responses, making it possible to improve all traits together. It offers a good balance between production and adaptation traits and may present some interest for the selection of other goat breeds in the tropics.

Influence of antiretroviral therapy on programmed death-1 (CD279) expression on T cells in lymph nodes of human immunodeficiency virus-infected individuals.

PubMed

Ehrhard, Simone; Wernli, Marion; Dürmüller, Ursula; Battegay, Manuel; Gudat, Fred; Erb, Peter

2009-10-01

Human immunodeficiency virus infection leads to T-cell exhaustion and involution of lymphoid tissue. Recently, the programmed death-1 pathway was found to be crucial for virus-specific T-cell exhaustion during human immunodeficiency virus infection. Programmed death-1 expression was elevated on human immunodeficiency virus-specific peripheral blood CD8+ and CD4+ T cells and correlated with disease severity. During human immunodeficiency infection, lymphoid tissue acts as a major viral reservoir and is an important site for viral replication, but it is also essential for regulatory processes important for immune recovery. We compared programmed death-1 expression in 2 consecutive inguinal lymph nodes of 14 patients, excised before antiretroviral therapy (antiretroviral therapy as of 1997-1999) and 16 to 20 months under antiretroviral therapy. In analogy to lymph nodes of human immunodeficiency virus-negative individuals, in all treated patients, the germinal center area decreased, whereas the number of germinal centers did not significantly change. Programmed death-1 expression was mostly found in germinal centers. The absolute extent of programmed death 1 expression per section was not significantly altered after antiretroviral therapy resulting in a significant-relative increase of programmed death 1 per shrunken germinal center. In colocalization studies, CD45R0+ cells that include helper/inducer T cells strongly expressed programmed death-1 before and during therapy, whereas CD8+ T cells, fewer in numbers, showed a weak expression for programmed death-1. Thus, although antiretroviral therapy seems to reduce the number of programmed death-1-positive CD8+ T lymphocytes within germinal centers, it does not down-regulate programmed death-1 expression on the helper/inducer T-cell subset that may remain exhausted and therefore unable to trigger immune recovery.

Upgrade to the Cryogenic Hydrogen Gas Target Monitoring System

NASA Astrophysics Data System (ADS)

Slater, Michael; Tribble, Robert

2013-10-01

The cryogenic hydrogen gas target at Texas A&M is a vital component for creating a secondary radioactive beam that is then used in experiments in the Momentum Achromat Recoil Spectrometer (MARS). A stable beam from the K500 superconducting cyclotron enters the gas cell and some incident particles are transmuted by a nuclear reaction into a radioactive beam, which are separated from the primary beam and used in MARS experiments. The pressure in the target chamber is monitored so that a predictable isotope production rate can be assured. A ``black box'' received the analog pressure data and sent RS232 serial data through an outdated serial connection to an outdated Visual Basic 6 (VB6) program, which plotted the chamber pressure continuously. The black box has been upgraded to an Arduino UNO microcontroller [Atmel Inc.], which can receive the pressure data and output via USB to a computer. It has been programmed to also accept temperature data for future upgrade. A new computer program, with updated capabilities, has been written in Python. The software can send email alerts, create audible alarms through the Arduino, and plot pressure and temperature. The program has been designed to better fit the needs of the users. Funded by DOE and NSF-REU Program.

Genome-wide prediction of vaccine targets for human herpes simplex viruses using Vaxign reverse vaccinology

PubMed Central

2013-01-01

Herpes simplex virus (HSV) types 1 and 2 (HSV-1 and HSV-2) are the most common infectious agents of humans. No safe and effective HSV vaccines have been licensed. Reverse vaccinology is an emerging and revolutionary vaccine development strategy that starts with the prediction of vaccine targets by informatics analysis of genome sequences. Vaxign (http://www.violinet.org/vaxign) is the first web-based vaccine design program based on reverse vaccinology. In this study, we used Vaxign to analyze 52 herpesvirus genomes, including 3 HSV-1 genomes, one HSV-2 genome, 8 other human herpesvirus genomes, and 40 non-human herpesvirus genomes. The HSV-1 strain 17 genome that contains 77 proteins was used as the seed genome. These 77 proteins are conserved in two other HSV-1 strains (strain F and strain H129). Two envelope glycoproteins gJ and gG do not have orthologs in HSV-2 or 8 other human herpesviruses. Seven HSV-1 proteins (including gJ and gG) do not have orthologs in all 40 non-human herpesviruses. Nineteen proteins are conserved in all human herpesviruses, including capsid scaffold protein UL26.5 (NP_044628.1). As the only HSV-1 protein predicted to be an adhesin, UL26.5 is a promising vaccine target. The MHC Class I and II epitopes were predicted by the Vaxign Vaxitop prediction program and IEDB prediction programs recently installed and incorporated in Vaxign. Our comparative analysis found that the two programs identified largely the same top epitopes but also some positive results predicted from one program might not be positive from another program. Overall, our Vaxign computational prediction provides many promising candidates for rational HSV vaccine development. The method is generic and can also be used to predict other viral vaccine targets. PMID:23514126

Methodology for Software Reliability Prediction. Volume 2.

DTIC Science & Technology

1987-11-01

The overall acquisition ,z program shall include the resources, schedule, management, structure , and controls necessary to ensure that specified AD...Independent Verification/Validation - Programming Team Structure - Educational Level of Team Members - Experience Level of Team Members * Methods Used...Prediction or Estimation Parameter Supported: Software - Characteristics 3. Objectives: Structured programming studies and Government Ur.’.. procurement

CELLFS: TAKING THE "DMA" OUT OF CELL PROGRAMMING

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

IONKOV, LATCHESAR A.; MIRTCHOVSKI, ANDREY A.; NYRHINEN, AKI M.

In this paper we present a new programming model for the Cell BE architecture of scalar multiprocessors. They call this programming model CellFS. CellFS aims at simplifying the task of managing I/O between the local store of the processing units and main memory. The CellFS support library provides the means for transferring data via simple file I/O operations between the PPU and the SPU.

Glutamine Synthetase Is a Genetic Determinant of Cell Type–Specific Glutamine Independence in Breast Epithelia

PubMed Central

Kung, Hsiu-Ni; Marks, Jeffrey R.; Chi, Jen-Tsan

2011-01-01

Although significant variations in the metabolic profiles exist among different cells, little is understood in terms of genetic regulations of such cell type–specific metabolic phenotypes and nutrient requirements. While many cancer cells depend on exogenous glutamine for survival to justify the therapeutic targeting of glutamine metabolism, the mechanisms of glutamine dependence and likely response and resistance of such glutamine-targeting strategies among cancers are largely unknown. In this study, we have found a systematic variation in the glutamine dependence among breast tumor subtypes associated with mammary differentiation: basal- but not luminal-type breast cells are more glutamine-dependent and may be susceptible to glutamine-targeting therapeutics. Glutamine independence of luminal-type cells is associated mechanistically with lineage-specific expression of glutamine synthetase (GS). Luminal cells can also rescue basal cells in co-culture without glutamine, indicating a potential for glutamine symbiosis within breast ducts. The luminal-specific expression of GS is directly induced by GATA3 and represses glutaminase expression. Such distinct glutamine dependency and metabolic symbiosis is coupled with the acquisition of the GS and glutamine independence during the mammary differentiation program. Understanding the genetic circuitry governing distinct metabolic patterns is relevant to many symbiotic relationships among different cells and organisms. In addition, the ability of GS to predict patterns of glutamine metabolism and dependency among tumors is also crucial in the rational design and application of glutamine and other metabolic pathway targeted therapies. PMID:21852960

A neural network based computational model to predict the output power of different types of photovoltaic cells.

PubMed

Xiao, WenBo; Nazario, Gina; Wu, HuaMing; Zhang, HuaMing; Cheng, Feng

2017-01-01

In this article, we introduced an artificial neural network (ANN) based computational model to predict the output power of three types of photovoltaic cells, mono-crystalline (mono-), multi-crystalline (multi-), and amorphous (amor-) crystalline. The prediction results are very close to the experimental data, and were also influenced by numbers of hidden neurons. The order of the solar generation power output influenced by the external conditions from smallest to biggest is: multi-, mono-, and amor- crystalline silicon cells. In addition, the dependences of power prediction on the number of hidden neurons were studied. For multi- and amorphous crystalline cell, three or four hidden layer units resulted in the high correlation coefficient and low MSEs. For mono-crystalline cell, the best results were achieved at the hidden layer unit of 8.

Performance predictions for an SSME configuration with an enlarged throat

NASA Technical Reports Server (NTRS)

Nickerson, G. R.; Dang, L. D.

1985-01-01

The Two Dimensional Kinetics (TDK) computer program that was recently developed for NASA was used to predict the performance of a Large Throat Configuration of the Space Shuttle Main Engine (SSME). Calculations indicate that the current design SSME contains a shock wave that is induced by the nozzle wall shape. In the Large Throat design an even stronger shock wave is predicted. Because of the presence of this shock wave, earlier performance predictions that have neglected shock wave effects have been questioned. The JANNAF thrust chamber performance prediction procedures given in a reference were applied. The analysis includes the effects of two dimensional reacting flow with a shock wave. The effects of the boundary layer with a regenatively cooled wall are also included. A Purdue computer program was used to compute axially symmetric supersonic nozzle flows with an induced shock, but is restricted to flows with a constant ratio of specific heats. Thus, the TDK program was also run with ths assumption and the results of the two programs were compared.

Transcription Factor Binding Profiles Reveal Cyclic Expression of Human Protein-coding Genes and Non-coding RNAs

PubMed Central

Cheng, Chao; Ung, Matthew; Grant, Gavin D.; Whitfield, Michael L.

2013-01-01

Cell cycle is a complex and highly supervised process that must proceed with regulatory precision to achieve successful cellular division. Despite the wide application, microarray time course experiments have several limitations in identifying cell cycle genes. We thus propose a computational model to predict human cell cycle genes based on transcription factor (TF) binding and regulatory motif information in their promoters. We utilize ENCODE ChIP-seq data and motif information as predictors to discriminate cell cycle against non-cell cycle genes. Our results show that both the trans- TF features and the cis- motif features are predictive of cell cycle genes, and a combination of the two types of features can further improve prediction accuracy. We apply our model to a complete list of GENCODE promoters to predict novel cell cycle driving promoters for both protein-coding genes and non-coding RNAs such as lincRNAs. We find that a similar percentage of lincRNAs are cell cycle regulated as protein-coding genes, suggesting the importance of non-coding RNAs in cell cycle division. The model we propose here provides not only a practical tool for identifying novel cell cycle genes with high accuracy, but also new insights on cell cycle regulation by TFs and cis-regulatory elements. PMID:23874175

An experimental and theoretical investigation of deposition patterns from an agricultural airplane

NASA Technical Reports Server (NTRS)

Morris, D. J.; Croom, C. C.; Vandam, C. P.; Holmes, B. J.

1984-01-01

A flight test program has been conducted with a representative agricultural airplane to provide data for validating a computer program model which predicts aerially applied particle deposition. Test procedures and the data from this test are presented and discussed. The computer program features are summarized, and comparisons of predicted and measured particle deposition are presented. Applications of the computer program for spray pattern improvement are illustrated.

Aggregating Data for Computational Toxicology Applications ...

EPA Pesticide Factsheets

Computational toxicology combines data from high-throughput test methods, chemical structure analyses and other biological domains (e.g., genes, proteins, cells, tissues) with the goals of predicting and understanding the underlying mechanistic causes of chemical toxicity and for predicting toxicity of new chemicals and products. A key feature of such approaches is their reliance on knowledge extracted from large collections of data and data sets in computable formats. The U.S. Environmental Protection Agency (EPA) has developed a large data resource called ACToR (Aggregated Computational Toxicology Resource) to support these data-intensive efforts. ACToR comprises four main repositories: core ACToR (chemical identifiers and structures, and summary data on hazard, exposure, use, and other domains), ToxRefDB (Toxicity Reference Database, a compilation of detailed in vivo toxicity data from guideline studies), ExpoCastDB (detailed human exposure data from observational studies of selected chemicals), and ToxCastDB (data from high-throughput screening programs, including links to underlying biological information related to genes and pathways). The EPA DSSTox (Distributed Structure-Searchable Toxicity) program provides expert-reviewed chemical structures and associated information for these and other high-interest public inventories. Overall, the ACToR system contains information on about 400,000 chemicals from 1100 different sources. The entire system is built usi

NOAA Climate Program Office Contributions to National ESPC

NASA Astrophysics Data System (ADS)

Higgins, W.; Huang, J.; Mariotti, A.; Archambault, H. M.; Barrie, D.; Lucas, S. E.; Mathis, J. T.; Legler, D. M.; Pulwarty, R. S.; Nierenberg, C.; Jones, H.; Cortinas, J. V., Jr.; Carman, J.

2016-12-01

NOAA is one of five federal agencies (DOD, DOE, NASA, NOAA, and NSF) which signed an updated charter in 2016 to partner on the National Earth System Prediction Capability (ESPC). Situated within NOAA's Office of Oceanic and Atmospheric Research (OAR), NOAA Climate Program Office (CPO) programs contribute significantly to the National ESPC goals and activities. This presentation will provide an overview of CPO contributions to National ESPC. First, we will discuss selected CPO research and transition activities that directly benefit the ESPC coupled model prediction capability, including The North American Multi-Model Ensemble (NMME) seasonal prediction system The Subseasonal Experiment (SubX) project to test real-time subseasonal ensemble prediction systems. Improvements to the NOAA operational Climate Forecast System (CFS), including software infrastructure and data assimilation. Next, we will show how CPO's foundational research activities are advancing future ESPC capabilities. Highlights will include: The Tropical Pacific Observing System (TPOS) to provide the basis for predicting climate on subseasonal to decadal timescales. Subseasonal-to-Seasonal (S2S) processes and predictability studies to improve understanding, modeling and prediction of the MJO. An Arctic Research Program to address urgent needs for advancing monitoring and prediction capabilities in this major area of concern. Advances towards building an experimental multi-decadal prediction system through studies on the Atlantic Meridional Overturning Circulation (AMOC). Finally, CPO has embraced Integrated Information Systems (IIS's) that build on the innovation of programs such as the National Integrated Drought Information System (NIDIS) to develop and deliver end to end environmental information for key societal challenges (e.g. extreme heat; coastal flooding). These contributions will help the National ESPC better understand and address societal needs and decision support requirements.

An object programming based environment for protein secondary structure prediction.

PubMed

Giacomini, M; Ruggiero, C; Sacile, R

1996-01-01

The most frequently used methods for protein secondary structure prediction are empirical statistical methods and rule based methods. A consensus system based on object-oriented programming is presented, which integrates the two approaches with the aim of improving the prediction quality. This system uses an object-oriented knowledge representation based on the concepts of conformation, residue and protein, where the conformation class is the basis, the residue class derives from it and the protein class derives from the residue class. The system has been tested with satisfactory results on several proteins of the Brookhaven Protein Data Bank. Its results have been compared with the results of the most widely used prediction methods, and they show a higher prediction capability and greater stability. Moreover, the system itself provides an index of the reliability of its current prediction. This system can also be regarded as a basis structure for programs of this kind.

The flow of plasma in the solar terrestrial environment

NASA Technical Reports Server (NTRS)

Schunk, Robert W.

1991-01-01

The overall goal of our NASA Theory Program is to study the coupling, time delays, and feedback mechanisms between the various regions of the solar-terrestrial system in a self-consistent, quantitative, manner. To accomplish this goal, it will eventually be necessary to have time-dependent macroscopic models of the different regions of the solar-terrestrial system and we are continually working toward this goal. However, our immediate emphasis is on the near-earth plasma environment, including the ionosphere, the plasmasphere, and the polar wind. In this area, we have developed unique global models that allow us to study the coupling between the different regions. These results are highlighted. Another important aspect of our NASA Theory Program concerns the effect that localized structure has on the macroscopic flow in the ionosphere, plasmasphere, thermosphere and polar wind. The localized structure can be created by structured magnetospheric inputs (i.e., structured plasma convection, particle precipitation or Birkeland current patterns) or time variations in these inputs due to storms and substorms. Also, some of the plasma flows that we predict with our macroscopic models may be unstable. Another one of our goals is to examine the stability of our predicted flows. Because time-dependent three-dimensional numerical models of the solar-terrestrial environment generally require extensive computer resources, they are usually based on relatively simple mathematical formulations (i.e., simple MHD or hydrodynamic formulations). Therefore, another long-range goal of our NASA Theory Program is to study the conditions under which various mathematical formulations can be applied to specific solar-terrestrial regions. This may involve a detailed comparison of kinetic, semikinetic, and hydrodynamic predictions for a given polar wind scenario or it may involve the comparison of a small-scale particle-in-cell (PIC) simulation of a plasma expansion event with a similar macroscopic expansion event. The different mathematical formulations have different strengths and weaknesses and a careful comparison of model predictions for similar geophysical situations will provide insight into when the various models can be used with confidence.

A nomogram to predict brain metastasis as the first relapse in curatively resected non-small cell lung cancer patients.

PubMed

Won, Young-Woong; Joo, Jungnam; Yun, Tak; Lee, Geon-Kook; Han, Ji-Youn; Kim, Heung Tae; Lee, Jin Soo; Kim, Moon Soo; Lee, Jong Mog; Lee, Hyun-Sung; Zo, Jae Ill; Kim, Sohee

2015-05-01

Development of brain metastasis results in a significant reduction in overall survival. However, there is no an effective tool to predict brain metastasis in non-small cell lung cancer (NSCLC) patients. We conducted this study to develop a feasible nomogram that can predict metastasis to the brain as the first relapse site in patients with curatively resected NSCLC. A retrospective review of NSCLC patients who had received curative surgery at National Cancer Center (Goyang, South Korea) between 2001 and 2008 was performed. We chose metastasis to the brain as the first relapse site after curative surgery as the primary endpoint of the study. A nomogram was modeled using logistic regression. Among 1218 patients, brain metastasis as the first relapse developed in 87 patients (7.14%) during the median follow-up of 43.6 months. Occurrence rates of brain metastasis were higher in patients with adenocarcinoma or those with a high pT and pN stage. Younger age appeared to be associated with brain metastasis, but this result was not statistically significant. The final prediction model included histology, smoking status, pT stage, and the interaction between adenocarcinoma and pN stage. The model showed fairly good discriminatory ability with a C-statistic of 69.3% and 69.8% for predicting brain metastasis within 2 years and 5 years, respectively. Internal validation using 2000 bootstrap samples resulted in C-statistics of 67.0% and 67.4% which still indicated good discriminatory performances. The nomogram presented here provides the individual risk estimate of developing metastasis to the brain as the first relapse site in patients with NSCLC who have undergone curative surgery. Surveillance programs or preventive treatment strategies for brain metastasis could be established based on this nomogram. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Development of comprehensive nomograms for evaluating overall and cancer-specific survival of laryngeal squamous cell carcinoma patients treated with neck dissection

PubMed Central

Shi, Xiao; Hu, Wei-ping; Ji, Qing-hai

2017-01-01

Background Neck dissection for laryngeal squamous cell carcinoma (LSCC) patients could provide complementary prognostic information for AJCC N staging, like lymph node ratio (LNR). The aim of this study was to develop effective nomograms to better predict survival for LSCC patients treated with neck dissection. Results 2752 patients were identified and randomly divided into training (n = 2477) and validation (n = 275) cohorts. The 3- and 5-year probabilities of cancer-specific mortality (CSM) were 30.1% and 37.2% while 3- and 5-year death resulting from other causes (DROC) rate were 6.2% and 11.3%, respectively. 13 significant prognostic factors including LNR for overall (OS) and 12 (except race) for CSS were enrolled in the nomograms. Concordance index as a commonly used indicator of predictive performance, showed the nomograms had superiority over the no-LNR models and TNM classification (Training-cohort: OS: 0.713 vs 0.703 vs 0.667, CSS: 0.725 vs 0.713 vs 0.688; Validation-cohort: OS: 0.704 vs 0.690 vs 0.658, cancer-specific survival (CSS): 0.709 vs 0.693 vs 0.672). All calibration plots revealed good agreement between nomogram prediction and actual survival. Materials and Methods We identified LSCC patients undergoing neck dissection diagnosed between 1988 and 2008 from Surveillance, Epidemiology, and End Results (SEER) database. Optimal cutoff points were determined by X-tile program. Cumulative incidence function was used to analyze cancer-specific mortality (CSM) and death resulting from other causes (DROC). Significant predictive factors were used to establish nomograms estimating overall (OS) and cancer-specific survival (CSS). The nomograms were bootstrapped validated both internally and externally. Conclusions Comprehensive nomograms were constructed to predict OS and CSS for LSCC patients treated with neck dissection more accurately. PMID:28430613

Genetic improvement of mastitis resistance: validation of somatic cell score and clinical mastitis as selection criteria.

PubMed

Odegård, J; Klemetsdal, G; Heringstad, B

2003-12-01

Mean daughter deviations for clinical mastitis among second-crop daughters were regressed on predicted transmitting abilities for clinical mastitis and lactation mean somatic cell score in first-crop daughters to validate the predictive ability of these traits as selection criteria for reduced incidence of clinical mastitis. A total of 321 sires had 684,897 second-crop daughters, while predicted transmitting abilities were calculated for 2159 sires, based on 495,681 records of first-crop daughters. Predictive ability, as a measure of efficiency of selection, was 23 to 43% higher for clinical mastitis than for lactation mean somatic cell score. Compared to single-trait selection, predictive ability improved 8 to 13% from utilizing information on both traits. The relative weight that should be assigned to standardized predicted transmitting abilities from univariate genetic analyses were 60 to 67% for clinical mastitis and 33 to 40% for lactation mean somatic cell score. No significant nonlinear genetic relationship between the two traits was found.

Predicting Workplace Transfer of Learning: A Study of Adult Learners Enrolled in a Continuing Professional Education Training Program

ERIC Educational Resources Information Center

Nafukho, Fredrick Muyia; Alfred, Mary; Chakraborty, Misha; Johnson, Michelle; Cherrstrom, Catherine A.

2017-01-01

Purpose: The primary purpose of this study was to predict transfer of learning to workplace among adult learners enrolled in a continuing professional education (CPE) training program, specifically training courses offered through face-to-face, blended and online instruction formats. The study examined the predictive capacity of trainee…

Using Admission Assessments to Predict Final Grades in a College Music Program

ERIC Educational Resources Information Center

Lehmann, Andreas C.

2014-01-01

Entrance examinations and auditions are common admission procedures for college music programs, yet few researchers have attempted to look at the long-term predictive validity of such selection processes. In this study, archival data from 93 student records of a German music academy were used to predict development of musicianship skills over the…

The Predictive Accuracy of Verbal, Quantitative, and Nonverbal Reasoning Tests: Consequences for Talent Identification and Program Diversity

ERIC Educational Resources Information Center

Lakin, Joni M.; Lohman, David F.

2011-01-01

Effective talent-identification procedures minimize the proportion of students whose subsequent performance indicates that they were mistakenly included in or excluded from the program. Classification errors occur when students who were predicted to excel subsequently do not excel or when students who were not predicted to excel do. Using a…

The Climate Variability & Predictability (CVP) Program at NOAA - Observing and Understanding Processes Affecting the Propagation of Intraseasonal Oscillations in the Maritime Continent Region

NASA Astrophysics Data System (ADS)

Lucas, S. E.

2017-12-01

The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International and U.S. Climate Variability and Predictability (CLIVAR/US CLIVAR) Program, and the U.S. Global Change Research Program (USGCRP). The CVP program sits within NOAA's Climate Program Office (http://cpo.noaa.gov/CVP). In 2017, the CVP Program had a call for proposals focused on observing and understanding processes affecting the propagation of intraseasonal oscillations in the Maritime Continent region. This poster will present the recently funded CVP projects, the expected scientific outcomes, the geographic areas of their work in the Maritime Continent region, and the collaborations with the Office of Naval Research, Indonesian Agency for Meteorology, Climatology and Geophysics (BMKG), Japan Agency for Marine-Earth Science and Technology (JAMSTEC) and other partners.

A review and update of the NASA aircraft noise prediction program propeller analysis system

NASA Technical Reports Server (NTRS)

Golub, Robert A.; Nguyen, L. Cathy

1989-01-01

The National Aeronautics and Space Administration (NASA) Aircraft Noise Prediction Program (ANOPP) Propeller Analysis System (PAS) is a set of computational modules for predicting the aerodynamics, performance, and noise of propellers. The ANOPP PAS has the capability to predict noise levels for propeller aircraft certification and produce parametric scaling laws for the adjustment of measured data to reference conditions. A technical overview of the prediction techniques incorporated into the system is presented. The prediction system has been applied to predict the noise signature of a variety of propeller configurations including the effects of propeller angle of attack. A summary of these validation studies is discussed with emphasis being placed on the wind tunnel and flight test programs sponsored by the Federal Aviation Administration (FAA) for the Piper Cherokee Lance aircraft. A number of modifications and improvements have been made to the system and both DEC VAX and IBM-PC versions of the system have been added to the original CDC NOS version.

Stochastic-Strength-Based Damage Simulation Tool for Ceramic Matrix and Polymer Matrix Composite Structures

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.; Bednarcyk, Brett A.; Pineda, Evan J.; Walton, Owen J.; Arnold, Steven M.

2016-01-01

Stochastic-based, discrete-event progressive damage simulations of ceramic-matrix composite and polymer matrix composite material structures have been enabled through the development of a unique multiscale modeling tool. This effort involves coupling three independently developed software programs: (1) the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC), (2) the Ceramics Analysis and Reliability Evaluation of Structures Life Prediction Program (CARES/ Life), and (3) the Abaqus finite element analysis (FEA) program. MAC/GMC contributes multiscale modeling capabilities and micromechanics relations to determine stresses and deformations at the microscale of the composite material repeating unit cell (RUC). CARES/Life contributes statistical multiaxial failure criteria that can be applied to the individual brittle-material constituents of the RUC. Abaqus is used at the global scale to model the overall composite structure. An Abaqus user-defined material (UMAT) interface, referred to here as "FEAMAC/CARES," was developed that enables MAC/GMC and CARES/Life to operate seamlessly with the Abaqus FEA code. For each FEAMAC/CARES simulation trial, the stochastic nature of brittle material strength results in random, discrete damage events, which incrementally progress and lead to ultimate structural failure. This report describes the FEAMAC/CARES methodology and discusses examples that illustrate the performance of the tool. A comprehensive example problem, simulating the progressive damage of laminated ceramic matrix composites under various off-axis loading conditions and including a double notched tensile specimen geometry, is described in a separate report.

Cell membrane temperature rate sensitivity predicted from the Nernst equation.

PubMed

Barnes, F S

1984-01-01

A hyperpolarized current is predicted from the Nernst equation for conditions of positive temperature derivatives with respect to time. This ion current, coupled with changes in membrane channel conductivities, is expected to contribute to a transient potential shift across the cell membrane for silent cells and to a change in firing rate for pacemaker cells.

Integrative multicellular biological modeling: a case study of 3D epidermal development using GPU algorithms

PubMed Central

2010-01-01

Background Simulation of sophisticated biological models requires considerable computational power. These models typically integrate together numerous biological phenomena such as spatially-explicit heterogeneous cells, cell-cell interactions, cell-environment interactions and intracellular gene networks. The recent advent of programming for graphical processing units (GPU) opens up the possibility of developing more integrative, detailed and predictive biological models while at the same time decreasing the computational cost to simulate those models. Results We construct a 3D model of epidermal development and provide a set of GPU algorithms that executes significantly faster than sequential central processing unit (CPU) code. We provide a parallel implementation of the subcellular element method for individual cells residing in a lattice-free spatial environment. Each cell in our epidermal model includes an internal gene network, which integrates cellular interaction of Notch signaling together with environmental interaction of basement membrane adhesion, to specify cellular state and behaviors such as growth and division. We take a pedagogical approach to describing how modeling methods are efficiently implemented on the GPU including memory layout of data structures and functional decomposition. We discuss various programmatic issues and provide a set of design guidelines for GPU programming that are instructive to avoid common pitfalls as well as to extract performance from the GPU architecture. Conclusions We demonstrate that GPU algorithms represent a significant technological advance for the simulation of complex biological models. We further demonstrate with our epidermal model that the integration of multiple complex modeling methods for heterogeneous multicellular biological processes is both feasible and computationally tractable using this new technology. We hope that the provided algorithms and source code will be a starting point for modelers to develop their own GPU implementations, and encourage others to implement their modeling methods on the GPU and to make that code available to the wider community. PMID:20696053

77 FR 27277 - FTA Supplemental Fiscal Year 2012 Apportionments, Allocations, and Program Information

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-09

... allocates Section 5309 Bus and Bus Facilities funds to bus testing and the Fuel Cell program. Tables... Fuel Cell program. FTA will issue a supplemental notice at a later date if additional contract... allocated CA, GA, MA E2012-BUSP-018 Fuel Cell Bus Program..... $13,500,000 PA E2012-BUSP-019 Bus Testing 3...

Dysregulation of haematopoietic stem cell regulatory programs in acute myeloid leukaemia.

PubMed

Basilico, Silvia; Göttgens, Berthold

2017-07-01

Haematopoietic stem cells (HSC) are situated at the apex of the haematopoietic differentiation hierarchy, ensuring the life-long supply of mature haematopoietic cells and forming a reservoir to replenish the haematopoietic system in case of emergency such as acute blood loss. To maintain a balanced production of all mature lineages and at the same time secure a stem cell reservoir, intricate regulatory programs have evolved to control multi-lineage differentiation and self-renewal in haematopoietic stem and progenitor cells (HSPCs). Leukaemogenic mutations commonly disrupt these regulatory programs causing a block in differentiation with simultaneous enhancement of proliferation. Here, we briefly summarize key aspects of HSPC regulatory programs, and then focus on their disruption by leukaemogenic fusion genes containing the mixed lineage leukaemia (MLL) gene. Using MLL as an example, we explore important questions of wider significance that are still under debate, including the importance of cell of origin, to what extent leukaemia oncogenes impose specific regulatory programs and the relevance of leukaemia stem cells for disease development and prognosis. Finally, we suggest that disruption of stem cell regulatory programs is likely to play an important role in many other pathologies including ageing-associated regenerative failure.

The Cosmetics Europe strategy for animal-free genotoxicity testing: project status up-date.

PubMed

Pfuhler, S; Fautz, R; Ouedraogo, G; Latil, A; Kenny, J; Moore, C; Diembeck, W; Hewitt, N J; Reisinger, K; Barroso, J

2014-02-01

The Cosmetics Europe (formerly COLIPA) Genotoxicity Task Force has driven and funded three projects to help address the high rate of misleading positives in in vitro genotoxicity tests: The completed "False Positives" project optimized current mammalian cell assays and showed that the predictive capacity of the in vitro micronucleus assay was improved dramatically by selecting more relevant cells and more sensitive toxicity measures. The on-going "3D skin model" project has been developed and is now validating the use of human reconstructed skin (RS) models in combination with the micronucleus (MN) and Comet assays. These models better reflect the in use conditions of dermally applied products, such as cosmetics. Both assays have demonstrated good inter- and intra-laboratory reproducibility and are entering validation stages. The completed "Metabolism" project investigated enzyme capacities of human skin and RS models. The RS models were shown to have comparable metabolic capacity to native human skin, confirming their usefulness for testing of compounds with dermal exposure. The program has already helped to improve the initial test battery predictivity and the RS projects have provided sound support for their use as a follow-up test in the assessment of the genotoxic hazard of cosmetic ingredients in the absence of in vivo data. Copyright © 2013 Elsevier Ltd. All rights reserved.

Binding sites for interaction of peroxiredoxin 6 with surfactant protein A.

PubMed

Krishnaiah, Saikumari Y; Dodia, Chandra; Sorokina, Elena M; Li, Haitao; Feinstein, Sheldon I; Fisher, Aron B

2016-04-01

Peroxiredoxin 6 (Prdx6) is a bifunctional enzyme with peroxidase and phospholipase A2 (PLA2) activities. This protein participates in the degradation and remodeling of internalized dipalmitoylphosphatidylcholine (DPPC), the major phospholipid component of lung surfactant. We have shown previously that the PLA2 activity of Prdx6 is inhibited by the lung surfactant-associated protein called surfactant protein A (SP-A) through direct protein-protein interaction. Docking of SPA and Prdx6 was modeled using the ZDOCK (zlab.bu.edu) program in order to predict molecular sites for binding of the two proteins. The predicted peptide sequences were evaluated for binding to the opposite protein using isothermal titration calorimetry and circular dichroism measurement followed by determination of the effect of the SP-A peptide on the PLA2 activity of Prdx6. The sequences 195EEEAKKLFPK204.in the Prdx6 helix and 83DEELQTELYEIKHQIL99 in SP-A were identified as the sites for hydrophobic interaction and H(+)-bonding between the 2 proteins. Treatment of mouse endothelial cells with the SP-A peptide inhibited their recovery from lipid peroxidation associated with oxidative stress indicating inhibition of Prdx6 activity by the peptide in the intact cell. Copyright © 2015 Elsevier B.V. All rights reserved.

Clinical initiatives linking Japanese and Swedish healthcare resources on cancer studies utilizing Biobank Repositories.

PubMed

Nishimura, Toshihide; Kawamura, Takeshi; Sugihara, Yutaka; Bando, Yasuhiko; Sakamoto, Shigeru; Nomura, Masaharu; Ikeda, Norihiko; Ohira, Tatsuo; Fujimoto, Junichiro; Tojo, Hiromasa; Hamakubo, Takao; Kodama, Tatsuhiko; Andersson, Roland; Fehniger, Thomas E; Kato, Harubumi; Marko-Varga, György

2014-12-01

The Tokyo Medical University Hospital in Japan and the Lund University hospital in Sweden have recently initiated a research program with the objective to impact on patient treatment by clinical disease stage characterization (phenotyping), utilizing proteomics sequencing platforms. By sharing clinical experiences, patient treatment principles, and biobank strategies, our respective clinical teams in Japan and Sweden will aid in the development of predictive and drug related protein biomarkers. Data from joint lung cancer studies are presented where protein expression from Neuro- Endocrine lung cancer (LCNEC) phenotype patients can be separated from Small cell- (SCLC) and Large Cell lung cancer (LCC) patients by deep sequencing and spectral counting analysis. LCNEC, a subtype of large cell carcinoma (LCC), is characterized by neuroendocrine differentiation that small cell lung carcinoma (SCLC) shares. Pre-therapeutic histological distinction between LCNEC and SCLC has so far been problematic, leading to adverse clinical outcome. An establishment of protein targets characteristic of LCNEC is quite helpful for decision of optimal therapeutic strategy by diagnosing individual patients. Proteoform annotation and clinical biobanking is part of the HUPO initiative (http://www.hupo.org) within chromosome 10 and chromosome 19 consortia.

Downsides and benefits of unicellularity in budding yeast

NASA Astrophysics Data System (ADS)

Balazsi, Gabor; Chen, Lin; Kuzdzal-Fick, Jennie

Yeast cells that do not separate after cell division form clumps. Clumping was shown to aid utilization of certain sugars, but its effects in stressful conditions are unknown. Generally speaking, what are the costs and benefits of unicellularity versus clumping multicellularity in normal and stressful conditions? To address this question, we evolved clumping yeast towards unicellularity by continuously propagating only those cells that remain suspended in liquid culture after settling. Whole-genome sequencing indicated that mutations in the AMN1 (antagonist of mitotic exit network) gene underlie the changes from clumping to unicellular phenotypes in these evolved yeast cells. Simple models predict that clumping should hinder growth in normal conditions while being protective in stress. Accordingly, we find experimentally that yeast clumps are more resistant to freeze/thaw, hydrogen peroxide, and ethanol stressors than their unicellular counterparts. On the other hand, unicellularity seems to be advantageous in normal conditions. Overall, these results reveal the downsides and benefits of unicellularity in different environmental conditions and uncover its genetic bases in yeast. This research was supported by the NIH Director's New Innovator Award Program (1DP2 OD006481-01), by NSF/IOS 1021675 and the Laufer Center for Physical & Quantitative Biology.

A theoretical framework for jamming in confluent biological tissues

NASA Astrophysics Data System (ADS)

Manning, M. Lisa

2015-03-01

For important biological functions such as wound healing, embryonic development, and cancer tumorogenesis, cells must initially rearrange and move over relatively large distances, like a liquid. Subsequently, these same tissues must undergo buckling and support shear stresses, like a solid. Our work suggests that biological tissues can accommodate these disparate requirements because the tissues are close to glass or jamming transition. While recent self propelled particle models generically predict a glass/jamming transition that is driven by packing density φ and happens at some critical φc less than unity, many biological tissues that are confluent with no gaps between cells appear to undergo a jamming transition at a constant density (φ = 1). I will discuss a new theoretical framework for predicting energy barriers and rates of cell migration in 2D tissue monolayers, and show that this model predicts a novel type of rigidity transition, which takes place at constant φ = 1 and depends only on single cell properties such as cell-cell adhesion, cortical tension and cell elasticity. This model additionally predicts that an experimentally observable parameter, the ratio between a cell's perimeter and the square root of its cross-sectional area, attains a specific, critical value at the jamming transition. We show that this prediction is precisely realized in primary epithelial cultures from human patients, with implications for asthma pathology.

Aircraft noise source and computer programs - User's guide

NASA Technical Reports Server (NTRS)

Crowley, K. C.; Jaeger, M. A.; Meldrum, D. F.

1973-01-01

The application of computer programs for predicting the noise-time histories and noise contours for five types of aircraft is reported. The aircraft considered are: (1) turbojet, (2) turbofan, (3) turboprop, (4) V/STOL, and (5) helicopter. Three principle considerations incorporated in the design of the noise prediction program are core effectiveness, limited input, and variable output reporting.

Predicting Success: How Predictive Analytics Are Transforming Student Support and Success Programs

ERIC Educational Resources Information Center

Boerner, Heather

2015-01-01

Every year, Lone Star College in Texas hosts a "Men of Honor" program to provide assistance and programming to male students, but particularly those who are Hispanic and black, in hopes their academic performance will improve. Lone Star might have kept directing its limited resources toward these students--and totally missed the subset…

Verification of MICNOISE computer program for the prediction of highway noise : part II : additional verification of MICNOISE version 5.

DOT National Transportation Integrated Search

1975-01-01

This is a continuation of an earlier report in which the MICNOISE computer program for the prediction of highway noise was evaluated. The outputs of the MICNOISE program are the L50 and LI0 sound pressure levels, i.e., those levels experienced 50% an...

Predicting Dropout Student: An Application of Data Mining Methods in an Online Education Program

ERIC Educational Resources Information Center

Yukselturk, Erman; Ozekes, Serhat; Turel, Yalin Kilic

2014-01-01

This study examined the prediction of dropouts through data mining approaches in an online program. The subject of the study was selected from a total of 189 students who registered to the online Information Technologies Certificate Program in 2007-2009. The data was collected through online questionnaires (Demographic Survey, Online Technologies…

2011 Annual Progress Report: DOE Hydrogen and Fuel Cells Program (Book)

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

Not Available

In the past year, the DOE Hydrogen and Fuel Cells Program (the Program) made substantial progress toward its goals and objectives. The Program has conducted comprehensive and focused efforts to enable the widespread commercialization of hydrogen and fuel cell technologies in diverse sectors of the economy. With emphasis on applications that will effectively strengthen our nation's energy security and improve our stewardship of the environment, the Program engages in research, development, and demonstration of critical improvements in the technologies. Highlights of the Program's accomplishments can be found in the sub-program chapters of this report.

Life prediction of turbine components: On-going studies at the NASA Lewis Research Center

NASA Technical Reports Server (NTRS)

Spera, D. A.; Grisaffe, S. J.

1973-01-01

An overview is presented of the many studies at NASA-Lewis that form the turbine component life prediction program. This program has three phases: (1) development of life prediction methods for major failure modes through materials studies, (2) evaluation and improvement of these methods through a variety of burner rig studies on simulated components in research engines and advanced rigs. These three phases form a cooperative, interdisciplinary program. A bibliography of Lewis publications on fatigue, oxidation and coatings, and turbine engine alloys is included.

ANOPP programmer's reference manual for the executive System. [aircraft noise prediction program

NASA Technical Reports Server (NTRS)

Gillian, R. E.; Brown, C. G.; Bartlett, R. W.; Baucom, P. H.

1977-01-01

Documentation for the Aircraft Noise Prediction Program as of release level 01/00/00 is presented in a manual designed for programmers having a need for understanding the internal design and logical concepts of the executive system software. Emphasis is placed on providing sufficient information to modify the system for enhancements or error correction. The ANOPP executive system includes software related to operating system interface, executive control, and data base management for the Aircraft Noise Prediction Program. It is written in Fortran IV for use on CDC Cyber series of computers.

Immune checkpoint inhibitors for non-small-cell lung cancer: does that represent a 'new frontier'?

PubMed

Pilotto, Sara; Kinspergher, Stefania; Peretti, Umberto; Calio, Anna; Carbognin, Luisa; Ferrara, Roberto; Brunelli, Matteo; Chilosi, Marco; Tortora, Giampaolo; Bria, Emilio

2015-01-01

Advances in the interpretation and understanding of cancer behaviour, particularly of its ability to evade the host immunosurveillance, deregulating the balance between inhibitory and stimulatory factors, led to the development of an innovative category of immunotherapeutic agents, currently under investigation. Although the disappointing data deriving from the employment of vaccines in non-small cell lung cancer (NSCLC), more promising results have been obtained in the early phase trials with immune checkpoint inhibitors, such as cytotoxic T-lymphocyte-associated antigen-4 (CTLA-4), programmed cell death protein-1 (PD-1) and programmed death-ligand 1 (PD-L1) inhibitors. This review delineates the main features of the available immunotherapeutic agents, focusing the discussion on immune checkpoint inhibitors, those that have already demonstrated a relevant clinical activity (such as Ipilimumab and Nivolumab) and those molecules still in early development phase. Moreover, we underline the possible emerging issues deriving from the progressive diffusion of Immuno-Oncology into the standard clinical practice. The careful and accurate identification and management of immune-related toxicities, the validation of more reliable immune response criteria and the increasing research of potential predictive biomarkers are key points of discussion. The perspective is that immunotherapy might represent an effective 'magic bullet', able to change the treatment paradigm of NSCLC, particularly of those subgroups featured by a heavily mutant cancer (squamous histology and smokers), where the immunologic agents contribute in cancer development and progression seems to be strong and, concurrently, the efficacy of standard therapies particularly limited.

Correlation of electron and proton irradiation-induced damage in InP solar cells

NASA Technical Reports Server (NTRS)

Walters, Robert J.; Summers, Geoffrey P.; Messenger, Scott R.; Burke, Edward A.

1995-01-01

When determining the best solar cell technology for a particular space flight mission, accurate prediction of solar cell performance in a space radiation environment is essential. The current methodology used to make such predictions requires extensive experimental data measured under both electron and proton irradiation. Due to the rising cost of accelerators and irradiation facilities, such extensive data sets are expensive to obtain. Moreover, with the rapid development of novel cell designs, the necessary data are often not available. Therefore, a method for predicting cell degradation based on limited data is needed. Such a method has been developed at the Naval Research Laboratory based on damage correlation using 'displacement damage dose' which is the product of the non-ionizing energy loss (NIEL) and the particle fluence. Displacement damage dose is a direct analog of the ionization dose used to correlate the effects of ionizing radiations. In this method, the performance of a solar cell in a complex radiation environment can be predicted from data on a single proton energy and two electron energies, or one proton energy, one electron energy, and Co(exp 60) gammas. This method has been used to accurately predict the extensive data set measured by Anspaugh on GaAs/Ge solar cells under a wide range of electron and proton energies. In this paper, the method is applied to InP solar cells using data measured under 1 MeV electron and 3 MeV proton irradiations, and the calculations are shown to agree well with the measured data. In addition to providing accurate damage predictions, this method also provides a basis for quantitative comparisons of the performance of different cell technologies. The performance of the present InP cells is compared to that published for GaAs/Ge cells. The results show InP to be inherently more resistant to displacement energy deposition than GaAs/Ge.

The role of predictive uncertainty in the operational management of reservoirs

NASA Astrophysics Data System (ADS)

Todini, E.

2014-09-01

The present work deals with the operational management of multi-purpose reservoirs, whose optimisation-based rules are derived, in the planning phase, via deterministic (linear and nonlinear programming, dynamic programming, etc.) or via stochastic (generally stochastic dynamic programming) approaches. In operation, the resulting deterministic or stochastic optimised operating rules are then triggered based on inflow predictions. In order to fully benefit from predictions, one must avoid using them as direct inputs to the reservoirs, but rather assess the "predictive knowledge" in terms of a predictive probability density to be operationally used in the decision making process for the estimation of expected benefits and/or expected losses. Using a theoretical and extremely simplified case, it will be shown why directly using model forecasts instead of the full predictive density leads to less robust reservoir management decisions. Moreover, the effectiveness and the tangible benefits for using the entire predictive probability density instead of the model predicted values will be demonstrated on the basis of the Lake Como management system, operational since 1997, as well as on the basis of a case study on the lake of Aswan.