Laser Signature Prediction Using The VALUE Computer Program

NASA Astrophysics Data System (ADS)

Akerman, Alexander; Hoffman, George A.; Patton, Ronald

1989-09-01

A variety of enhancements are being made to the 1976-vintage LASERX computer code. These include: - Surface characterization with BDRF tabular data - Specular reflection from transparent surfaces - Generation of glint direction maps - Generation of relative range imagery - Interface to the LOWTRAN atmospheric transmission code - Interface to the LEOPS laser sensor code - User friendly menu prompting for easy setup Versions of VALUE have been written for both VAX/VMS and PC/DOS computer environments. Outputs have also been revised to be user friendly and include tables, plots, and images for (1) intensity, (2) cross section,(3) reflectance, (4) relative range, (5) region type, and (6) silhouette.

Infrared Signature Modeling and Analysis of Aircraft Plume

NASA Astrophysics Data System (ADS)

Rao, Arvind G.

2011-09-01

In recent years, the survivability of an aircraft has been put to task more than ever before. One of the main reasons is the increase in the usage of Infrared (IR) guided Anti-Aircraft Missiles, especially due to the availability of Man Portable Air Defence System (MANPADS) with some terrorist groups. Thus, aircraft IR signatures are gaining more importance as compared to their radar, visual, acoustic, or any other signatures. The exhaust plume ejected from the aircraft is one of the important sources of IR signature in military aircraft that use low bypass turbofan engines for propulsion. The focus of the present work is modelling of spectral IR radiation emission from the exhaust jet of a typical military aircraft and to evaluate the aircraft susceptibility in terms of the aircraft lock-on range due to its plume emission, for a simple case against a typical Surface to Air Missile (SAM). The IR signature due to the aircraft plume is examined in a holistic manner. A comprehensive methodology of computing IR signatures and its affect on aircraft lock-on range is elaborated. Commercial CFD software has been used to predict the plume thermo-physical properties and subsequently an in-house developed code was used for evaluating the IR radiation emitted by the plume. The LOWTRAN code has been used for modeling the atmospheric IR characteristics. The results obtained from these models are in reasonable agreement with some available experimental data. The analysis carried out in this paper succinctly brings out the intricacy of the radiation emitted by various gaseous species in the plume and the role of atmospheric IR transmissivity in dictating the plume IR signature as perceived by an IR guided SAM.

Hyperheat: a thermal signature model for super- and hypersonic missiles

NASA Astrophysics Data System (ADS)

van Binsbergen, S. A.; van Zelderen, B.; Veraar, R. G.; Bouquet, F.; Halswijk, W. H. C.; Schleijpen, H. M. A.

2017-10-01

In performance prediction of IR sensor systems for missile detection, apart from the sensor specifications, target signatures are essential variables. Very often, for velocities up to Mach 2-2.5, a simple model based on the aerodynamic heating of a perfect gas was used to calculate the temperatures of missile targets. This typically results in an overestimate of the target temperature with correspondingly large infrared signatures and detection ranges. Especially for even higher velocities, this approach is no longer accurate. Alternatives like CFD calculations typically require more complex sets of inputs and significantly more computing power. The MATLAB code Hyperheat was developed to calculate the time-resolved skin temperature of axisymmetric high speed missiles during flight, taking into account the behaviour of non-perfect gas and proper heat transfer to the missile surface. Allowing for variations in parameters like missile shape, altitude, atmospheric profile, angle of attack, flight duration and super- and hypersonic velocities up to Mach 30 enables more accurate calculations of the actual target temperature. The model calculates a map of the skin temperature of the missile, which is updated over the flight time of the missile. The sets of skin temperature maps are calculated within minutes, even for >100 km trajectories, and can be easily converted in thermal infrared signatures for further processing. This paper discusses the approach taken in Hyperheat. Then, the thermal signature of a set of typical missile threats is calculated using both the simple aerodynamic heating model and the Hyperheat code. The respective infrared signatures are compared, as well as the difference in the corresponding calculated detection ranges.

Numerical Predictions of Sonic Boom Signatures for a Straight Line Segmented Leading Edge Model

NASA Technical Reports Server (NTRS)

Elmiligui, Alaa A.; Wilcox, Floyd J.; Cliff, Susan; Thomas, Scott

2012-01-01

A sonic boom wind tunnel test was conducted on a straight-line segmented leading edge (SLSLE) model in the NASA Langley 4- by 4- Foot Unitary Plan Wind Tunnel (UPWT). The purpose of the test was to determine whether accurate sonic boom measurements could be obtained while continuously moving the SLSLE model past a conical pressure probe. Sonic boom signatures were also obtained using the conventional move-pause data acquisition method for comparison. The continuous data acquisition approach allows for accurate signatures approximately 15 times faster than a move-pause technique. These successful results provide an incentive for future testing with greatly increased efficiency using the continuous model translation technique with the single probe to measure sonic boom signatures. Two widely used NASA codes, USM3D (Navier-Stokes) and CART3D-AERO (Euler, adjoint-based adaptive mesh), were used to compute off-body sonic boom pressure signatures of the SLSLE model at several different altitudes below the model at Mach 2.0. The computed pressure signatures compared well with wind tunnel data. The effect of the different altitude for signature extraction was evaluated by extrapolating the near field signatures to the ground and comparing pressure signatures and sonic boom loudness levels.

Generation of signature databases with fast codes

NASA Astrophysics Data System (ADS)

Bradford, Robert A.; Woodling, Arthur E.; Brazzell, James S.

1990-09-01

Using the FASTSIG signature code to generate optical signature databases for the Ground-based Surveillance and Traking System (GSTS) Program has improved the efficiency of the database generation process. The goal of the current GSTS database is to provide standardized, threat representative target signatures that can easily be used for acquisition and trk studies, discrimination algorithm development, and system simulations. Large databases, with as many as eight interpolalion parameters, are required to maintain the fidelity demands of discrimination and to generalize their application to other strateg systems. As the need increases for quick availability of long wave infrared (LWIR) target signatures for an evolving design4o-threat, FASTSIG has become a database generation alternative to using the industry standard OptiCal Signatures Code (OSC). FASTSIG, developed in 1985 to meet the unique strategic systems demands imposed by the discrimination function, has the significant advantage of being a faster running signature code than the OSC, typically requiring two percent of the cpu time. It uses analytical approximations to model axisymmetric targets, with the fidelity required for discrimination analysis. Access of the signature database is accomplished through use of the waveband integration and interpolation software, INTEG and SIGNAT. This paper gives details of this procedure as well as sample interpolated signatures and also covers sample verification by comparison to the OSC, in order to establish the fidelity of the FASTSIG generated database.

XPATCH: a high-frequency electromagnetic scattering prediction code using shooting and bouncing rays

NASA Astrophysics Data System (ADS)

Hazlett, Michael; Andersh, Dennis J.; Lee, Shung W.; Ling, Hao; Yu, C. L.

1995-06-01

This paper describes an electromagnetic computer prediction code for generating radar cross section (RCS), time domain signatures, and synthetic aperture radar (SAR) images of realistic 3-D vehicles. The vehicle, typically an airplane or a ground vehicle, is represented by a computer-aided design (CAD) file with triangular facets, curved surfaces, or solid geometries. The computer code, XPATCH, based on the shooting and bouncing ray technique, is used to calculate the polarimetric radar return from the vehicles represented by these different CAD files. XPATCH computes the first-bounce physical optics plus the physical theory of diffraction contributions and the multi-bounce ray contributions for complex vehicles with materials. It has been found that the multi-bounce contributions are crucial for many aspect angles of all classes of vehicles. Without the multi-bounce calculations, the radar return is typically 10 to 15 dB too low. Examples of predicted range profiles, SAR imagery, and radar cross sections (RCS) for several different geometries are compared with measured data to demonstrate the quality of the predictions. The comparisons are from the UHF through the Ka frequency ranges. Recent enhancements to XPATCH for MMW applications and target Doppler predictions are also presented.

A Code Division Multiple Access Communication System for the Low Frequency Band.

DTIC Science & Technology

1983-04-01

frequency channels spread-spectrum communication / complex sequences, orthogonal codes impulsive noise 20. ABSTRACT (Continue an reverse side It...their transmissions with signature sequences. Our LF/CDMA scheme is different in that each user’s signature sequence set consists of M orthogonal ...signature sequences. Our LF/CDMA scheme is different in that each user’s signature sequence set consists of M orthogonal sequences and thus log 2 M

Radiation and polarization signatures of the 3D multizone time-dependent hadronic blazar model

DOE PAGES

Zhang, Haocheng; Diltz, Chris; Bottcher, Markus

2016-09-23

We present a newly developed time-dependent three-dimensional multizone hadronic blazar emission model. By coupling a Fokker–Planck-based lepto-hadronic particle evolution code, 3DHad, with a polarization-dependent radiation transfer code, 3DPol, we are able to study the time-dependent radiation and polarization signatures of a hadronic blazar model for the first time. Our current code is limited to parameter regimes in which the hadronic γ-ray output is dominated by proton synchrotron emission, neglecting pion production. Our results demonstrate that the time-dependent flux and polarization signatures are generally dominated by the relation between the synchrotron cooling and the light-crossing timescale, which is largely independent ofmore » the exact model parameters. We find that unlike the low-energy polarization signatures, which can vary rapidly in time, the high-energy polarization signatures appear stable. Lastly, future high-energy polarimeters may be able to distinguish such signatures from the lower and more rapidly variable polarization signatures expected in leptonic models.« less

Validation of the Complexity INdex in SARComas prognostic signature on formalin-fixed, paraffin-embedded, soft tissue sarcomas.

PubMed

Le Guellec, S; Lesluyes, T; Sarot, E; Valle, C; Filleron, T; Rochaix, P; Valentin, T; Pérot, G; Coindre, J-M; Chibon, F

2018-05-31

Prediction of metastatic outcome in sarcomas is challenging for clinical management since they are aggressive and carry a high metastatic risk. A 67-gene expression signature, the Complexity INdex in SARComas (CINSARC), has been identified as a better prognostic factor than the reference pathological grade. Since it cannot be applied easily in standard laboratory practice, we assessed its prognostic value using nanoString on formalin-fixed, paraffin-embedded (FFPE) blocks to evaluate its potential in clinical routine practice and guided therapeutic management. A code set consisting of 67 probes derived from the 67 genes of the CINSARC signature was built and named NanoCind®. To compare the performance of RNA-seq and nanoString (NanoCind®), we used expressions of various sarcomas (n=124, frozen samples) using both techniques and compared predictive values based on CINSARC risk groups and clinical annotations. We also used nanoString on FFPE blocks (n=67) and matching frozen and FFPE samples (n=45) to compare their level of agreement. Metastasis-free survival and agreement values in classification groups were evaluated. CINSARC strongly predicted metastatic outcome using nanoString on frozen samples (HR = 2.9, 95% CI 1.23-6.82) with similar risk-group classifications (86%). While more than 50% of FFPE blocks were not analyzable by RNA-seq owing to poor RNA quality, all samples were analyzable with nanoString. When similar (risk-group) classifications were measured with frozen tumors (RNA-seq) compared to FFPE blocks (84% agreement), the CINSARC signature was still a predictive factor of metastatic outcome with nanoString on FFPE samples (HR = 4.43, 95% CI 1.25-15.72). CINSARC is a material-independent prognostic signature for metastatic outcome in sarcomas and outperforms histological grade. Unlike RNA-seq, nanoString is not influenced by the poor quality of RNA extracted from FFPE blocks. The CINSARC signature can potentially be used in combination with nanoString (NanoCind®) in routine clinical practice on FFPE blocks to predict metastatic outcome.

A Grid Sourcing and Adaptation Study Using Unstructured Grids for Supersonic Boom Prediction

NASA Technical Reports Server (NTRS)

Carter, Melissa B.; Deere, Karen A.

2008-01-01

NASA created the Supersonics Project as part of the NASA Fundamental Aeronautics Program to advance technology that will make a supersonic flight over land viable. Computational flow solvers have lacked the ability to accurately predict sonic boom from the near to far field. The focus of this investigation was to establish gridding and adaptation techniques to predict near-to-mid-field (<10 body lengths below the aircraft) boom signatures at supersonic speeds using the USM3D unstructured grid flow solver. The study began by examining sources along the body the aircraft, far field sourcing and far field boundaries. The study then examined several techniques for grid adaptation. During the course of the study, volume sourcing was introduced as a new way to source grids using the grid generation code VGRID. Two different methods of using the volume sources were examined. The first method, based on manual insertion of the numerous volume sources, made great improvements in the prediction capability of USM3D for boom signatures. The second method (SSGRID), which uses an a priori adaptation approach to stretch and shear the original unstructured grid to align the grid and pressure waves, showed similar results with a more automated approach. Due to SSGRID s results and ease of use, the rest of the study focused on developing a best practice using SSGRID. The best practice created by this study for boom predictions using the CFD code USM3D involved: 1) creating a small cylindrical outer boundary either 1 or 2 body lengths in diameter (depending on how far below the aircraft the boom prediction is required), 2) using a single volume source under the aircraft, and 3) using SSGRID to stretch and shear the grid to the desired length.

CFD Predictions of Sonic-Boom Characteristics for Unmodified and Modified SR-71 Configurations

NASA Technical Reports Server (NTRS)

Fouladi, Kamran

1999-01-01

Shaped sonic-boom signatures refer to signatures that look something other than the typical N-waves. Shaped sonic-boom signatures such as "flat-top," "ramp-type," or "hybrid-type" waveforms have been shown to reduce the subjective loudness without requiring reductions in overpressure peaks. The shaping of sonic-boom signatures requires increasing the shock rise time and changes in frequency spectra. So far, a flat-top waveform was shown to be achievable in wind tunnels; however, the influence of long propagation distance and real atmosphere on shaped signatures should be addressed using flight tests. Two different approaches have been proposed for sonic-boom minimization flight tests. The first approach, proposed by Eagle Aerospace, is for a flight test using a modified BQM-34 "FIREBEE" remotely piloted vehicle. The 30-foot long FIREBEE has a steady state flight condition at the Mach number and altitude of interest, and it can be recovered by helicopter from the water. As an alternative approach, a modified SR-71 vehicle has been proposed by the McDonnell Douglas Corporation. Benefits of the SR-71 include its variable geometry supersonic inlets, small cockpit bulge, higher Mach number capabilities, slender design, and longer length (105 foot). The present investigation addresses the sonic-boom analysis for the second vehicle.The objective of the current investigation is to assess the feasibility of a modified SR-71 configuration, with McDonnell Douglas-designed fuselage modifications, intended to produce shaped sonic-boom signatures on the ground. The present study describes the use of a higher-order computational fluid dynamics (CFD) method to predict the sonic-boom characteristics for both unmodified and modified SR-71 configurations. An Euler unstructured grid methodology is used to predict the near-field, three-dimensional pressure patterns generated by both SR-71 models. The computed near-field pressure signatures are extrapolated to specified distances below the aircraft down to impingement on the ground using the code MDBOOM. Comparisons of the near-field pressure signatures with available flight-test data are presented in the current paper.

Promoter analysis reveals globally differential regulation of human long non-coding RNA and protein-coding genes

DOE PAGES

Alam, Tanvir; Medvedeva, Yulia A.; Jia, Hui; ...

2014-10-02

Transcriptional regulation of protein-coding genes is increasingly well-understood on a global scale, yet no comparable information exists for long non-coding RNA (lncRNA) genes, which were recently recognized to be as numerous as protein-coding genes in mammalian genomes. We performed a genome-wide comparative analysis of the promoters of human lncRNA and protein-coding genes, finding global differences in specific genetic and epigenetic features relevant to transcriptional regulation. These two groups of genes are hence subject to separate transcriptional regulatory programs, including distinct transcription factor (TF) proteins that significantly favor lncRNA, rather than coding-gene, promoters. We report a specific signature of promoter-proximal transcriptionalmore » regulation of lncRNA genes, including several distinct transcription factor binding sites (TFBS). Experimental DNase I hypersensitive site profiles are consistent with active configurations of these lncRNA TFBS sets in diverse human cell types. TFBS ChIP-seq datasets confirm the binding events that we predicted using computational approaches for a subset of factors. For several TFs known to be directly regulated by lncRNAs, we find that their putative TFBSs are enriched at lncRNA promoters, suggesting that the TFs and the lncRNAs may participate in a bidirectional feedback loop regulatory network. Accordingly, cells may be able to modulate lncRNA expression levels independently of mRNA levels via distinct regulatory pathways. Our results also raise the possibility that, given the historical reliance on protein-coding gene catalogs to define the chromatin states of active promoters, a revision of these chromatin signature profiles to incorporate expressed lncRNA genes is warranted in the future.« less

Promoter analysis reveals globally differential regulation of human long non-coding RNA and protein-coding genes

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

Alam, Tanvir; Medvedeva, Yulia A.; Jia, Hui

Transcriptional regulation of protein-coding genes is increasingly well-understood on a global scale, yet no comparable information exists for long non-coding RNA (lncRNA) genes, which were recently recognized to be as numerous as protein-coding genes in mammalian genomes. We performed a genome-wide comparative analysis of the promoters of human lncRNA and protein-coding genes, finding global differences in specific genetic and epigenetic features relevant to transcriptional regulation. These two groups of genes are hence subject to separate transcriptional regulatory programs, including distinct transcription factor (TF) proteins that significantly favor lncRNA, rather than coding-gene, promoters. We report a specific signature of promoter-proximal transcriptionalmore » regulation of lncRNA genes, including several distinct transcription factor binding sites (TFBS). Experimental DNase I hypersensitive site profiles are consistent with active configurations of these lncRNA TFBS sets in diverse human cell types. TFBS ChIP-seq datasets confirm the binding events that we predicted using computational approaches for a subset of factors. For several TFs known to be directly regulated by lncRNAs, we find that their putative TFBSs are enriched at lncRNA promoters, suggesting that the TFs and the lncRNAs may participate in a bidirectional feedback loop regulatory network. Accordingly, cells may be able to modulate lncRNA expression levels independently of mRNA levels via distinct regulatory pathways. Our results also raise the possibility that, given the historical reliance on protein-coding gene catalogs to define the chromatin states of active promoters, a revision of these chromatin signature profiles to incorporate expressed lncRNA genes is warranted in the future.« less

Model fitting data from syllogistic reasoning experiments.

PubMed

Hattori, Masasi

2016-12-01

The data presented in this article are related to the research article entitled "Probabilistic representation in syllogistic reasoning: A theory to integrate mental models and heuristics" (M. Hattori, 2016) [1]. This article presents predicted data by three signature probabilistic models of syllogistic reasoning and model fitting results for each of a total of 12 experiments ( N =404) in the literature. Models are implemented in R, and their source code is also provided.

Ventral striatal dopamine reflects behavioral and neural signatures of model-based control during sequential decision making.

PubMed

Deserno, Lorenz; Huys, Quentin J M; Boehme, Rebecca; Buchert, Ralph; Heinze, Hans-Jochen; Grace, Anthony A; Dolan, Raymond J; Heinz, Andreas; Schlagenhauf, Florian

2015-02-03

Dual system theories suggest that behavioral control is parsed between a deliberative "model-based" and a more reflexive "model-free" system. A balance of control exerted by these systems is thought to be related to dopamine neurotransmission. However, in the absence of direct measures of human dopamine, it remains unknown whether this reflects a quantitative relation with dopamine either in the striatum or other brain areas. Using a sequential decision task performed during functional magnetic resonance imaging, combined with striatal measures of dopamine using [(18)F]DOPA positron emission tomography, we show that higher presynaptic ventral striatal dopamine levels were associated with a behavioral bias toward more model-based control. Higher presynaptic dopamine in ventral striatum was associated with greater coding of model-based signatures in lateral prefrontal cortex and diminished coding of model-free prediction errors in ventral striatum. Thus, interindividual variability in ventral striatal presynaptic dopamine reflects a balance in the behavioral expression and the neural signatures of model-free and model-based control. Our data provide a novel perspective on how alterations in presynaptic dopamine levels might be accompanied by a disruption of behavioral control as observed in aging or neuropsychiatric diseases such as schizophrenia and addiction.

Modelling Metamorphism by Abstract Interpretation

NASA Astrophysics Data System (ADS)

Dalla Preda, Mila; Giacobazzi, Roberto; Debray, Saumya; Coogan, Kevin; Townsend, Gregg M.

Metamorphic malware apply semantics-preserving transformations to their own code in order to foil detection systems based on signature matching. In this paper we consider the problem of automatically extract metamorphic signatures from these malware. We introduce a semantics for self-modifying code, later called phase semantics, and prove its correctness by showing that it is an abstract interpretation of the standard trace semantics. Phase semantics precisely models the metamorphic code behavior by providing a set of traces of programs which correspond to the possible evolutions of the metamorphic code during execution. We show that metamorphic signatures can be automatically extracted by abstract interpretation of the phase semantics, and that regular metamorphism can be modelled as finite state automata abstraction of the phase semantics.

Sonic Boom Computations for a Mach 1.6 Cruise Low Boom Configuration and Comparisons with Wind Tunnel Data

NASA Technical Reports Server (NTRS)

Elmiligui, Alaa A.; Cliff, Susan E.; Wilcox, Floyd; Nemec, Marian; Bangert, Linda; Aftosmis, Michael J.; Parlette, Edward

2011-01-01

Accurate analysis of sonic boom pressure signatures using computational fluid dynamics techniques remains quite challenging. Although CFD shows accurate predictions of flow around complex configurations, generating grids that can resolve the sonic boom signature far away from the body is a challenge. The test case chosen for this study corresponds to an experimental wind-tunnel test that was conducted to measure the sonic boom pressure signature of a low boom configuration designed by Gulfstream Aerospace Corporation. Two widely used NASA codes, USM3D and AERO, are examined for their ability to accurately capture sonic boom signature. Numerical simulations are conducted for a free-stream Mach number of 1.6, angle of attack of 0.3 and Reynolds number of 3.85x10(exp 6) based on model reference length. Flow around the low boom configuration in free air and inside the Langley Unitary plan wind tunnel are computed. Results from the numerical simulations are compared with wind tunnel data. The effects of viscous and turbulence modeling along with tunnel walls on the computed sonic boom signature are presented and discussed.

VHF/UHF imagery and RCS measurements of ground targets in forested terrain

NASA Astrophysics Data System (ADS)

Gatesman, Andrew J.; Beaudoin, Christopher J.; Giles, Robert H.; Waldman, Jerry; Nixon, William E.

2002-08-01

The monostatic VV and HH-polarized radar signatures of several targets and trees have been measured at foliage penetration frequencies (VHF/UHF) by using 1/35th scale models and an indoor radar range operating at X-band. An array of high-fidelity scale model ground vehicles and test objects as well as scaled ground terrain and trees have been fabricated for the study. Radar measurement accuracy has been confirmed by comparing the signature of a test object with a method of moments radar cross section prediction code. In addition to acquiring signatures of targets located on a smooth, dielectric ground plane, data have also been acquired with targets located in simulated wooded terrain that included scaled tree trunks and tree branches. In order to assure the correct backscattering behavior, all dielectric properties of live tree wood and moist soil were scaled properly to match the complex dielectric constant of the full-scale materials. The impact of the surrounding tree clutter on the VHF/UHF radar signatures of ground vehicles was accessed. Data were processed into high-resolution, polar-formatted ISAR imagery and signature comparisons are made between targets in open-field and forested scenarios.

Sonic Boom Prediction and Minimization of the Douglas Reference OPT5 Configuration

NASA Technical Reports Server (NTRS)

Siclari, Michael J.

1999-01-01

Conventional CFD methods and grids do not yield adequate resolution of the complex shock flow pattern generated by a real aircraft geometry. As a result, a unique grid topology and supersonic flow solver was developed at Northrop Grumman based on the characteristic behavior of supersonic wave patterns emanating from the aircraft. Using this approach, it was possible to compute flow fields with adequate resolution several body lengths below the aircraft. In this region, three-dimensional effects are diminished and conventional two-dimensional modified linear theory (MLT) can be applied to estimate ground pressure signatures or sonic booms. To accommodate real aircraft geometries and alleviate the burdensome grid generation task, an implicit marching multi-block, multi-grid finite-volume Euler code was developed as the basis for the sonic boom prediction methodology. The Thomas two-dimensional extrapolation method is built into the Euler code so that ground signatures can be obtained quickly and efficiently with minimum computational effort suitable to the aircraft design environment. The loudness levels of these signatures can then be determined using a NASA generated noise code. Since the Euler code is a three-dimensional flow field solver, the complete circumferential region below the aircraft is computed. The extrapolation of all this field data from a cylinder of constant radius leads to the definition of the entire boom corridor occurring directly below and off to the side of the aircraft's flight path yielding an estimate for the entire noise "annoyance" corridor in miles as well as its magnitude. An automated multidisciplinary sonic boom design optimization software system was developed during the latter part of HSR Phase 1. Using this system, it was found that sonic boom signatures could be reduced through optimization of a variety of geometric aircraft parameters. This system uses a gradient based nonlinear optimizer as the driver in conjunction with a computationally efficient Euler CFD solver (NIIM3DSB) for computing the three-dimensional near-field characteristics of the aircraft. The intent of the design system is to identify and optimize geometric design variables that have a beneficial impact on the ground sonic boom. The system uses a simple wave drag data format to specify the aircraft geometry. The geometry is internally enhanced and analytic methods are used to generate marching grids suitable for the multi-block Euler solver. The Thomas extrapolation method is integrated into this system, and hence, the aircraft's centerline ground sonic boom signature is also automatically computed for a specified cruise altitude and yields the parameters necessary to evaluate the design function. The entire design system has been automated since the gradient based optimization software requires many flow analyses in order to obtain the required sensitivity derivatives for each design variable in order to converge on an optimal solution. Hence, once the problem is defined which includes defining the objective function and geometric and aerodynamic constraints, the system will automatically regenerate the perturbed geometry, the necessary grids, the Euler solution, and finally the ground sonic boom signature at the request of the optimizer.

The effects of different representations on static structure analysis of computer malware signatures.

PubMed

Narayanan, Ajit; Chen, Yi; Pang, Shaoning; Tao, Ban

2013-01-01

The continuous growth of malware presents a problem for internet computing due to increasingly sophisticated techniques for disguising malicious code through mutation and the time required to identify signatures for use by antiviral software systems (AVS). Malware modelling has focused primarily on semantics due to the intended actions and behaviours of viral and worm code. The aim of this paper is to evaluate a static structure approach to malware modelling using the growing malware signature databases now available. We show that, if malware signatures are represented as artificial protein sequences, it is possible to apply standard sequence alignment techniques in bioinformatics to improve accuracy of distinguishing between worm and virus signatures. Moreover, aligned signature sequences can be mined through traditional data mining techniques to extract metasignatures that help to distinguish between viral and worm signatures. All bioinformatics and data mining analysis were performed on publicly available tools and Weka.

The Effects of Different Representations on Static Structure Analysis of Computer Malware Signatures

PubMed Central

Narayanan, Ajit; Chen, Yi; Pang, Shaoning; Tao, Ban

2013-01-01

The continuous growth of malware presents a problem for internet computing due to increasingly sophisticated techniques for disguising malicious code through mutation and the time required to identify signatures for use by antiviral software systems (AVS). Malware modelling has focused primarily on semantics due to the intended actions and behaviours of viral and worm code. The aim of this paper is to evaluate a static structure approach to malware modelling using the growing malware signature databases now available. We show that, if malware signatures are represented as artificial protein sequences, it is possible to apply standard sequence alignment techniques in bioinformatics to improve accuracy of distinguishing between worm and virus signatures. Moreover, aligned signature sequences can be mined through traditional data mining techniques to extract metasignatures that help to distinguish between viral and worm signatures. All bioinformatics and data mining analysis were performed on publicly available tools and Weka. PMID:23983644

Security authentication using phase-encoded nanoparticle structures and polarized light.

PubMed

Carnicer, Artur; Hassanfiroozi, Amir; Latorre-Carmona, Pedro; Huang, Yi-Pai; Javidi, Bahram

2015-01-15

Phase-encoded nanostructures such as quick response (QR) codes made of metallic nanoparticles are suggested to be used in security and authentication applications. We present a polarimetric optical method able to authenticate random phase-encoded QR codes. The system is illuminated using polarized light, and the QR code is encoded using a phase-only random mask. Using classification algorithms, it is possible to validate the QR code from the examination of the polarimetric signature of the speckle pattern. We used Kolmogorov-Smirnov statistical test and Support Vector Machine algorithms to authenticate the phase-encoded QR codes using polarimetric signatures.

Superboom Caustic Analysis and Measurement Program (SCAMP) Final Report

NASA Technical Reports Server (NTRS)

Page, Juliet; Plotkin, Ken; Hobbs, Chris; Sparrow, Vic; Salamone, Joe; Cowart, Robbie; Elmer, Kevin; Welge, H. Robert; Ladd, John; Maglieri, Domenic;

21 CFR 11.300 - Controls for identification codes/passwords.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 1 2012-04-01 2012-04-01 false Controls for identification codes/passwords. 11.300 Section 11.300 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL ELECTRONIC RECORDS; ELECTRONIC SIGNATURES Electronic Signatures § 11.300 Controls for...

A Probabilistic Model of Meter Perception: Simulating Enculturation.

PubMed

van der Weij, Bastiaan; Pearce, Marcus T; Honing, Henkjan

2017-01-01

Enculturation is known to shape the perception of meter in music but this is not explicitly accounted for by current cognitive models of meter perception. We hypothesize that the induction of meter is a result of predictive coding: interpreting onsets in a rhythm relative to a periodic meter facilitates prediction of future onsets. Such prediction, we hypothesize, is based on previous exposure to rhythms. As such, predictive coding provides a possible explanation for the way meter perception is shaped by the cultural environment. Based on this hypothesis, we present a probabilistic model of meter perception that uses statistical properties of the relation between rhythm and meter to infer meter from quantized rhythms. We show that our model can successfully predict annotated time signatures from quantized rhythmic patterns derived from folk melodies. Furthermore, we show that by inferring meter, our model improves prediction of the onsets of future events compared to a similar probabilistic model that does not infer meter. Finally, as a proof of concept, we demonstrate how our model can be used in a simulation of enculturation. From the results of this simulation, we derive a class of rhythms that are likely to be interpreted differently by enculturated listeners with different histories of exposure to rhythms.

Study of the integration of wind tunnel and computational methods for aerodynamic configurations

NASA Technical Reports Server (NTRS)

Browne, Lindsey E.; Ashby, Dale L.

1989-01-01

A study was conducted to determine the effectiveness of using a low-order panel code to estimate wind tunnel wall corrections. The corrections were found by two computations. The first computation included the test model and the surrounding wind tunnel walls, while in the second computation the wind tunnel walls were removed. The difference between the force and moment coefficients obtained by comparing these two cases allowed the determination of the wall corrections. The technique was verified by matching the test-section, wall-pressure signature from a wind tunnel test with the signature predicted by the panel code. To prove the viability of the technique, two cases were considered. The first was a two-dimensional high-lift wing with a flap that was tested in the 7- by 10-foot wind tunnel at NASA Ames Research Center. The second was a 1/32-scale model of the F/A-18 aircraft which was tested in the low-speed wind tunnel at San Diego State University. The panel code used was PMARC (Panel Method Ames Research Center). Results of this study indicate that the proposed wind tunnel wall correction method is comparable to other methods and that it also inherently includes the corrections due to model blockage and wing lift.

Sonic Boom Propagation Codes Validated by Flight Test

NASA Technical Reports Server (NTRS)

Poling, Hugh W.

1996-01-01

The sonic boom propagation codes reviewed in this study, SHOCKN and ZEPHYRUS, implement current theory on air absorption using different computational concepts. Review of the codes with a realistic atmosphere model confirm the agreement of propagation results reported by others for idealized propagation conditions. ZEPHYRUS offers greater flexibility in propagation conditions and is thus preferred for practical aircraft analysis. The ZEPHYRUS code was used to propagate sonic boom waveforms measured approximately 1000 feet away from an SR-71 aircraft flying at Mach 1.25 to 5000 feet away. These extrapolated signatures were compared to measurements at 5000 feet. Pressure values of the significant shocks (bow, canopy, inlet and tail) in the waveforms are consistent between extrapolation and measurement. Of particular interest is that four (independent) measurements taken under the aircraft centerline converge to the same extrapolated result despite differences in measurement conditions. Agreement between extrapolated and measured signature duration is prevented by measured duration of the 5000 foot signatures either much longer or shorter than would be expected. The duration anomalies may be due to signature probing not sufficiently parallel to the aircraft flight direction.

Irma 5.2 multi-sensor signature prediction model

NASA Astrophysics Data System (ADS)

Savage, James; Coker, Charles; Thai, Bea; Aboutalib, Omar; Chow, Anthony; Yamaoka, Neil; Kim, Charles

2007-04-01

The Irma synthetic signature prediction code is being developed by the Munitions Directorate of the Air Force Research Laboratory (AFRL/MN) to facilitate the research and development of multi-sensor systems. There are over 130 users within the Department of Defense, NASA, Department of Transportation, academia, and industry. Irma began as a high-resolution, physics-based Infrared (IR) target and background signature model for tactical weapon applications and has grown to include: a laser (or active) channel (1990), improved scene generator to support correlated frame-to-frame imagery (1992), and passive IR/millimeter wave (MMW) channel for a co-registered active/passive IR/MMW model (1994). Irma version 5.0 was released in 2000 and encompassed several upgrades to both the physical models and software; host support was expanded to Windows, Linux, Solaris, and SGI Irix platforms. In 2005, version 5.1 was released after an extensive verification and validation of an upgraded and reengineered active channel. Since 2005, the reengineering effort has focused on the Irma passive channel. Field measurements for the validation effort include the unpolarized data collection. Irma 5.2 is scheduled for release in the summer of 2007. This paper will report the validation test results of the Irma passive models and discuss the new features in Irma 5.2.

Chromatin accessibility prediction via a hybrid deep convolutional neural network.

PubMed

Liu, Qiao; Xia, Fei; Yin, Qijin; Jiang, Rui

2018-03-01

A majority of known genetic variants associated with human-inherited diseases lie in non-coding regions that lack adequate interpretation, making it indispensable to systematically discover functional sites at the whole genome level and precisely decipher their implications in a comprehensive manner. Although computational approaches have been complementing high-throughput biological experiments towards the annotation of the human genome, it still remains a big challenge to accurately annotate regulatory elements in the context of a specific cell type via automatic learning of the DNA sequence code from large-scale sequencing data. Indeed, the development of an accurate and interpretable model to learn the DNA sequence signature and further enable the identification of causative genetic variants has become essential in both genomic and genetic studies. We proposed Deopen, a hybrid framework mainly based on a deep convolutional neural network, to automatically learn the regulatory code of DNA sequences and predict chromatin accessibility. In a series of comparison with existing methods, we show the superior performance of our model in not only the classification of accessible regions against background sequences sampled at random, but also the regression of DNase-seq signals. Besides, we further visualize the convolutional kernels and show the match of identified sequence signatures and known motifs. We finally demonstrate the sensitivity of our model in finding causative noncoding variants in the analysis of a breast cancer dataset. We expect to see wide applications of Deopen with either public or in-house chromatin accessibility data in the annotation of the human genome and the identification of non-coding variants associated with diseases. Deopen is freely available at https://github.com/kimmo1019/Deopen. ruijiang@tsinghua.edu.cn. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Preliminary airborne measurements for the SR-71 sonic boom propagation experiment

NASA Technical Reports Server (NTRS)

Haering, Edward A., Jr.; Ehernberger, L. J.; Whitmore, Stephen A.

1995-01-01

SR-71 sonic boom signatures were measured to validate sonic boom propagation prediction codes. An SR-71 aircraft generated sonic booms from Mach 1.25 to Mach 1.6, at altitudes of 31,000 to 48,000 ft, and at various gross weights. An F-16XL aircraft measured the SR-71 near-field shock waves from close to the aircraft to more than 8,000 ft below, gathering 105 signatures. A YO-3A aircraft measured the SR-71 sonic booms from 21,000 to 38,000 feet below, recording 17 passes. The sonic booms at ground level and atmospheric data were recorded for each flight. Data analysis is underway. Preliminary results show that shock wave patterns and coalescence vary with SR-71 gross weight, Mach number, and altitude. For example, noncoalesced shock wave signatures were measured by the YO-3A at 21,000 ft below the SR-71 aircraft while at a low gross weight, Mach 1.25, and 31,000-ft altitude. This paper describes the design and execution of the flight research experiment. Instrumentation and flight maneuvers of the SR-71, F-16XL, and YO-3A aircraft and sample sonic boom signatures are included.

A signature inferred from Drosophila mitotic genes predicts survival of breast cancer patients.

PubMed

Damasco, Christian; Lembo, Antonio; Somma, Maria Patrizia; Gatti, Maurizio; Di Cunto, Ferdinando; Provero, Paolo

2011-02-28

The classification of breast cancer patients into risk groups provides a powerful tool for the identification of patients who will benefit from aggressive systemic therapy. The analysis of microarray data has generated several gene expression signatures that improve diagnosis and allow risk assessment. There is also evidence that cell proliferation-related genes have a high predictive power within these signatures. We thus constructed a gene expression signature (the DM signature) using the human orthologues of 108 Drosophila melanogaster genes required for either the maintenance of chromosome integrity (36 genes) or mitotic division (72 genes). The DM signature has minimal overlap with the extant signatures and is highly predictive of survival in 5 large breast cancer datasets. In addition, we show that the DM signature outperforms many widely used breast cancer signatures in predictive power, and performs comparably to other proliferation-based signatures. For most genes of the DM signature, an increased expression is negatively correlated with patient survival. The genes that provide the highest contribution to the predictive power of the DM signature are those involved in cytokinesis. This finding highlights cytokinesis as an important marker in breast cancer prognosis and as a possible target for antimitotic therapies.

Irma 5.1 multisensor signature prediction model

NASA Astrophysics Data System (ADS)

Savage, James; Coker, Charles; Thai, Bea; Aboutalib, Omar; Yamaoka, Neil; Kim, Charles

2005-05-01

The Irma synthetic signature prediction code is being developed to facilitate the research and development of multisensor systems. Irma was one of the first high resolution Infrared (IR) target and background signature models to be developed for tactical weapon application. Originally developed in 1980 by the Munitions Directorate of the Air Force Research Laboratory (AFRL/MN), the Irma model was used exclusively to generate IR scenes. In 1988, a number of significant upgrades to Irma were initiated including the addition of a laser (or active) channel. This two-channel version was released to the user community in 1990. In 1992, an improved scene generator was incorporated into the Irma model, which supported correlated frame-to-frame imagery. A passive IR/millimeter wave (MMW) code was completed in 1994. This served as the cornerstone for the development of the co-registered active/passive IR/MMW model, Irma 4.0. In 2000, Irma version 5.0 was released which encompassed several upgrades to both the physical models and software. Circular polarization was added to the passive channel and the doppler capability was added to the active MMW channel. In 2002, the multibounce technique was added to the Irma passive channel. In the ladar channel, a user-friendly Ladar Sensor Assistant (LSA) was incorporated which provides capability and flexibility for sensor modeling. Irma 5.0 runs on several platforms including Windows, Linux, Solaris, and SGI Irix. Since 2000, additional capabilities and enhancements have been added to the ladar channel including polarization and speckle effect. Work is still ongoing to add time-jittering model to the ladar channel. A new user interface has been introduced to aid users in the mechanism of scene generation and running the Irma code. The user interface provides a canvas where a user can add and remove objects using mouse clicks to construct a scene. The scene can then be visualized to find the desired sensor position. The synthetic ladar signatures have been validated twice and underwent a third validation test near the end of 04. These capabilities will be integrated into the next release, Irma 5.1, scheduled for completion in the summer of FY05. Irma is currently being used to support a number of civilian and military applications. The Irma user base includes over 130 agencies within the Air Force, Army, Navy, DARPA, NASA, Department of Transportation, academia, and industry. The purpose of this paper is to report the progress of the Irma 5.1 development effort.

Trading Speed and Accuracy by Coding Time: A Coupled-circuit Cortical Model

PubMed Central

Standage, Dominic; You, Hongzhi; Wang, Da-Hui; Dorris, Michael C.

2013-01-01

Our actions take place in space and time, but despite the role of time in decision theory and the growing acknowledgement that the encoding of time is crucial to behaviour, few studies have considered the interactions between neural codes for objects in space and for elapsed time during perceptual decisions. The speed-accuracy trade-off (SAT) provides a window into spatiotemporal interactions. Our hypothesis is that temporal coding determines the rate at which spatial evidence is integrated, controlling the SAT by gain modulation. Here, we propose that local cortical circuits are inherently suited to the relevant spatial and temporal coding. In simulations of an interval estimation task, we use a generic local-circuit model to encode time by ‘climbing’ activity, seen in cortex during tasks with a timing requirement. The model is a network of simulated pyramidal cells and inhibitory interneurons, connected by conductance synapses. A simple learning rule enables the network to quickly produce new interval estimates, which show signature characteristics of estimates by experimental subjects. Analysis of network dynamics formally characterizes this generic, local-circuit timing mechanism. In simulations of a perceptual decision task, we couple two such networks. Network function is determined only by spatial selectivity and NMDA receptor conductance strength; all other parameters are identical. To trade speed and accuracy, the timing network simply learns longer or shorter intervals, driving the rate of downstream decision processing by spatially non-selective input, an established form of gain modulation. Like the timing network's interval estimates, decision times show signature characteristics of those by experimental subjects. Overall, we propose, demonstrate and analyse a generic mechanism for timing, a generic mechanism for modulation of decision processing by temporal codes, and we make predictions for experimental verification. PMID:23592967

Xpatch prediction improvements to support multiple ATR applications

NASA Astrophysics Data System (ADS)

Andersh, Dennis J.; Lee, Shung W.; Moore, John T.; Sullivan, Douglas P.; Hughes, Jeff A.; Ling, Hao

1998-08-01

This paper describes an electromagnetic computer prediction code for generating radar cross section (RCS), time-domain signature sand synthetic aperture radar (SAR) images of realistic 3D vehicles. The vehicle, typically an airplane or a ground vehicle, is represented by a computer-aided design (CAD) file with triangular facets, IGES curved surfaces, or solid geometries.The computer code, Xpatch, based on the shooting-and-bouncing-ray technique, is used to calculate the polarimetric radar return from the vehicles represented by these different CAD files. Xpatch computers the first- bounce physical optics (PO) plus the physical theory of diffraction (PTD) contributions. Xpatch calculates the multi-bounce ray contributions by using geometric optics and PO for complex vehicles with materials. It has been found that the multi-bounce calculations, the radar return in typically 10 to 15 dB too low. Examples of predicted range profiles, SAR, imagery, and RCS for several different geometries are compared with measured data to demonstrate the quality of the predictions. Recent enhancements to Xpatch include improvements for millimeter wave applications and hybridization with finite element method for small geometric features and augmentation of additional IGES entities to support trimmed and untrimmed surfaces.

Development and Validation of a Multidisciplinary Tool for Accurate and Efficient Rotorcraft Noise Prediction (MUTE)

NASA Technical Reports Server (NTRS)

Liu, Yi; Anusonti-Inthra, Phuriwat; Diskin, Boris

2011-01-01

A physics-based, systematically coupled, multidisciplinary prediction tool (MUTE) for rotorcraft noise was developed and validated with a wide range of flight configurations and conditions. MUTE is an aggregation of multidisciplinary computational tools that accurately and efficiently model the physics of the source of rotorcraft noise, and predict the noise at far-field observer locations. It uses systematic coupling approaches among multiple disciplines including Computational Fluid Dynamics (CFD), Computational Structural Dynamics (CSD), and high fidelity acoustics. Within MUTE, advanced high-order CFD tools are used around the rotor blade to predict the transonic flow (shock wave) effects, which generate the high-speed impulsive noise. Predictions of the blade-vortex interaction noise in low speed flight are also improved by using the Particle Vortex Transport Method (PVTM), which preserves the wake flow details required for blade/wake and fuselage/wake interactions. The accuracy of the source noise prediction is further improved by utilizing a coupling approach between CFD and CSD, so that the effects of key structural dynamics, elastic blade deformations, and trim solutions are correctly represented in the analysis. The blade loading information and/or the flow field parameters around the rotor blade predicted by the CFD/CSD coupling approach are used to predict the acoustic signatures at far-field observer locations with a high-fidelity noise propagation code (WOPWOP3). The predicted results from the MUTE tool for rotor blade aerodynamic loading and far-field acoustic signatures are compared and validated with a variation of experimental data sets, such as UH60-A data, DNW test data and HART II test data.

The fourfold way of the genetic code.

PubMed

Jiménez-Montaño, Miguel Angel

2009-11-01

We describe a compact representation of the genetic code that factorizes the table in quartets. It represents a "least grammar" for the genetic language. It is justified by the Klein-4 group structure of RNA bases and codon doublets. The matrix of the outer product between the column-vector of bases and the corresponding row-vector V(T)=(C G U A), considered as signal vectors, has a block structure consisting of the four cosets of the KxK group of base transformations acting on doublet AA. This matrix, translated into weak/strong (W/S) and purine/pyrimidine (R/Y) nucleotide classes, leads to a code table with mixed and unmixed families in separate regions. A basic difference between them is the non-commuting (R/Y) doublets: AC/CA, GU/UG. We describe the degeneracy in the canonical code and the systematic changes in deviant codes in terms of the divisors of 24, employing modulo multiplication groups. We illustrate binary sub-codes characterizing mutations in the quartets. We introduce a decision-tree to predict the mode of tRNA recognition corresponding to each codon, and compare our result with related findings by Jestin and Soulé [Jestin, J.-L., Soulé, C., 2007. Symmetries by base substitutions in the genetic code predict 2' or 3' aminoacylation of tRNAs. J. Theor. Biol. 247, 391-394], and the rearrangements of the table by Delarue [Delarue, M., 2007. An asymmetric underlying rule in the assignment of codons: possible clue to a quick early evolution of the genetic code via successive binary choices. RNA 13, 161-169] and Rodin and Rodin [Rodin, S.N., Rodin, A.S., 2008. On the origin of the genetic code: signatures of its primordial complementarity in tRNAs and aminoacyl-tRNA synthetases. Heredity 100, 341-355], respectively.

78 FR 57807 - Aged Beneficiary Designation Forms

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-20

... received by the TSP record- keeper not more than one year after date of the participant's signature. DATES... after the date of the participant's signature on the form. Regulatory Flexibility Act I certify that... the participant's signature. * * * * * [FR Doc. 2013-22894 Filed 9-19-13; 8:45 am] BILLING CODE 6760...

Assessment of Near-Field Sonic Boom Simulation Tools

NASA Technical Reports Server (NTRS)

Casper, J. H.; Cliff, S. E.; Thomas, S. D.; Park, M. A.; McMullen, M. S.; Melton, J. E.; Durston, D. A.

2008-01-01

A recent study for the Supersonics Project, within the National Aeronautics and Space Administration, has been conducted to assess current in-house capabilities for the prediction of near-field sonic boom. Such capabilities are required to simulate the highly nonlinear flow near an aircraft, wherein a sonic-boom signature is generated. There are many available computational fluid dynamics codes that could be used to provide the near-field flow for a sonic boom calculation. However, such codes have typically been developed for applications involving aerodynamic configuration, for which an efficiently generated computational mesh is usually not optimum for a sonic boom prediction. Preliminary guidelines are suggested to characterize a state-of-the-art sonic boom prediction methodology. The available simulation tools that are best suited to incorporate into that methodology are identified; preliminary test cases are presented in support of the selection. During this phase of process definition and tool selection, parallel research was conducted in an attempt to establish criteria that link the properties of a computational mesh to the accuracy of a sonic boom prediction. Such properties include sufficient grid density near shocks and within the zone of influence, which are achieved by adaptation and mesh refinement strategies. Prediction accuracy is validated by comparison with wind tunnel data.

USM3D Simulations for Second Sonic Boom Workshop

NASA Technical Reports Server (NTRS)

Elmiligui, Alaa; Carter, Melissa B.; Nayani, Sudheer N.; Cliff, Susan; Pearl, Jason M.

2017-01-01

The NASA Tetrahedral Unstructured Software System with the USM3D flow solver was used to compute test cases for the Second AIAA Sonic Boom Prediction Workshop. The intent of this report is to document the USM3D results for SBPW2 test cases. The test cases included an axisymmetric equivalent area body, a JAXA wing body, a NASA low boom supersonic configuration modeled with flow through nacelles and engine boundary conditions. All simulations were conducted for a free stream Mach number of 1.6, zero degrees angle of attack, and a Reynolds number of 5.7 million per meter. Simulations were conducted on tetrahedral grids provided by the workshop committee, as well as a family of grids generated by an in-house approach for sonic boom analyses known as BoomGrid using current best practices. The near-field pressure signatures were extracted and propagated to the ground with the atmospheric propagation code, sBOOM. The USM3D near-field pressure signatures, corresponding sBOOM ground signatures, and loudness levels on the ground are compared with mean values from other workshop participants.

Security authentication with a three-dimensional optical phase code using random forest classifier: an overview

NASA Astrophysics Data System (ADS)

Markman, Adam; Carnicer, Artur; Javidi, Bahram

2017-05-01

We overview our recent work [1] on utilizing three-dimensional (3D) optical phase codes for object authentication using the random forest classifier. A simple 3D optical phase code (OPC) is generated by combining multiple diffusers and glass slides. This tag is then placed on a quick-response (QR) code, which is a barcode capable of storing information and can be scanned under non-uniform illumination conditions, rotation, and slight degradation. A coherent light source illuminates the OPC and the transmitted light is captured by a CCD to record the unique signature. Feature extraction on the signature is performed and inputted into a pre-trained random-forest classifier for authentication.

Can specific transcriptional regulators assemble a universal cancer signature?

NASA Astrophysics Data System (ADS)

Roy, Janine; Isik, Zerrin; Pilarsky, Christian; Schroeder, Michael

2013-10-01

Recently, there is a lot of interest in using biomarker signatures derived from gene expression data to predict cancer progression. We assembled signatures of 25 published datasets covering 13 types of cancers. How do these signatures compare with each other? On one hand signatures answering the same biological question should overlap, whereas signatures predicting different cancer types should differ. On the other hand, there could also be a Universal Cancer Signature that is predictive independently of the cancer type. Initially, we generate signatures for all datasets using classical approaches such as t-test and fold change and then, we explore signatures resulting from a network-based method, that applies the random surfer model of Google's PageRank algorithm. We show that the signatures as published by the authors and the signatures generated with classical methods do not overlap - not even for the same cancer type - whereas the network-based signatures strongly overlap. Selecting 10 out of 37 universal cancer genes gives the optimal prediction for all cancers thus taking a first step towards a Universal Cancer Signature. We furthermore analyze and discuss the involved genes in terms of the Hallmarks of cancer and in particular single out SP1, JUN/FOS and NFKB1 and examine their specific role in cancer progression.

Comparison of jet plume shape predictions and plume influence on sonic boom signature

NASA Technical Reports Server (NTRS)

Barger, Raymond L.; Melson, N. Duane

1992-01-01

An Euler shock-fitting marching code yields good agreement with semiempirically determined plume shapes, although the agreement decreases somewhat with increasing nozzle angle and the attendant increase in the nonisentropic nature of the flow. Some calculations for the low boom configuration with a simple engine indicated that, for flight at altitudes above 60,000 feet, the plume effect is dominant. This negates the advantages of a low boom design. At lower altitudes, plume effects are significant, but of the order that can be incorporated into the low boom design process.

A Novel Quantum Blind Signature Scheme with Four-Particle Cluster States

NASA Astrophysics Data System (ADS)

Fan, Ling

2016-03-01

In an arbitrated quantum signature scheme, the signer signs the message and the receiver verifies the signature's validity with the assistance of the arbitrator. We present an arbitrated quantum blind signature scheme by measuring four-particle cluster states and coding. By using the special relationship of four-particle cluster states, we cannot only support the security of quantum signature, but also guarantee the anonymity of the message owner. It has a wide application to E-payment system, E-government, E-business, and etc.

Wind Tunnel Model Design for Sonic Boom Studies of Nozzle Jet with Shock Interactions

NASA Technical Reports Server (NTRS)

Cliff, Susan E.; Denison, Marie; Sozer, Emre; Moini-Yekta, Shayan

2016-01-01

NASA and Industry are performing vehicle studies of configurations with low sonic boom pressure signatures. The computational analyses of modern configuration designs have matured to the point where there is confidence in the prediction of the pressure signature from the front of the vehicle, but uncertainty in the aft signatures with often greater boundary layer effects and nozzle jet pressures. Wind tunnel testing at significantly lower Reynolds numbers than in flight and without inlet and nozzle jet pressures make it difficult to accurately assess the computational solutions of flight vehicles. A wind tunnel test in the NASA Ames 9- by 7-Foot Supersonic Wind Tunnel from Mach 1.6 to 2.0 will be used to assess the effects of shocks from components passing through nozzle jet plumes on the sonic boom pressure signature and provide datasets for comparison with CFD codes. A large number of high-fidelity numerical simulations of wind tunnel test models with a variety of shock generators that simulate horizontal tails and aft decks have been studied to provide suitable models for sonic boom pressure measurements using a minimally intrusive pressure rail in the wind tunnel. The computational results are presented and the evolution of candidate wind tunnel models is summarized and discussed in this paper.

An assessment of the adaptive unstructured tetrahedral grid, Euler Flow Solver Code FELISA

NASA Technical Reports Server (NTRS)

Djomehri, M. Jahed; Erickson, Larry L.

1994-01-01

A three-dimensional solution-adaptive Euler flow solver for unstructured tetrahedral meshes is assessed, and the accuracy and efficiency of the method for predicting sonic boom pressure signatures about simple generic models are demonstrated. Comparison of computational and wind tunnel data and enhancement of numerical solutions by means of grid adaptivity are discussed. The mesh generation is based on the advancing front technique. The FELISA code consists of two solvers, the Taylor-Galerkin and the Runge-Kutta-Galerkin schemes, both of which are spacially discretized by the usual Galerkin weighted residual finite-element methods but with different explicit time-marching schemes to steady state. The solution-adaptive grid procedure is based on either remeshing or mesh refinement techniques. An alternative geometry adaptive procedure is also incorporated.

Design of Provider-Provisioned Website Protection Scheme against Malware Distribution

NASA Astrophysics Data System (ADS)

Yagi, Takeshi; Tanimoto, Naoto; Hariu, Takeo; Itoh, Mitsutaka

Vulnerabilities in web applications expose computer networks to security threats, and many websites are used by attackers as hopping sites to attack other websites and user terminals. These incidents prevent service providers from constructing secure networking environments. To protect websites from attacks exploiting vulnerabilities in web applications, service providers use web application firewalls (WAFs). WAFs filter accesses from attackers by using signatures, which are generated based on the exploit codes of previous attacks. However, WAFs cannot filter unknown attacks because the signatures cannot reflect new types of attacks. In service provider environments, the number of exploit codes has recently increased rapidly because of the spread of vulnerable web applications that have been developed through cloud computing. Thus, generating signatures for all exploit codes is difficult. To solve these problems, our proposed scheme detects and filters malware downloads that are sent from websites which have already received exploit codes. In addition, to collect information for detecting malware downloads, web honeypots, which automatically extract the communication records of exploit codes, are used. According to the results of experiments using a prototype, our scheme can filter attacks automatically so that service providers can provide secure and cost-effective network environments.

Quantifying uncertainties in streamflow predictions through signature based inference of hydrological model parameters

NASA Astrophysics Data System (ADS)

Fenicia, Fabrizio; Reichert, Peter; Kavetski, Dmitri; Albert, Calro

2016-04-01

The calibration of hydrological models based on signatures (e.g. Flow Duration Curves - FDCs) is often advocated as an alternative to model calibration based on the full time series of system responses (e.g. hydrographs). Signature based calibration is motivated by various arguments. From a conceptual perspective, calibration on signatures is a way to filter out errors that are difficult to represent when calibrating on the full time series. Such errors may for example occur when observed and simulated hydrographs are shifted, either on the "time" axis (i.e. left or right), or on the "streamflow" axis (i.e. above or below). These shifts may be due to errors in the precipitation input (time or amount), and if not properly accounted in the likelihood function, may cause biased parameter estimates (e.g. estimated model parameters that do not reproduce the recession characteristics of a hydrograph). From a practical perspective, signature based calibration is seen as a possible solution for making predictions in ungauged basins. Where streamflow data are not available, it may in fact be possible to reliably estimate streamflow signatures. Previous research has for example shown how FDCs can be reliably estimated at ungauged locations based on climatic and physiographic influence factors. Typically, the goal of signature based calibration is not the prediction of the signatures themselves, but the prediction of the system responses. Ideally, the prediction of system responses should be accompanied by a reliable quantification of the associated uncertainties. Previous approaches for signature based calibration, however, do not allow reliable estimates of streamflow predictive distributions. Here, we illustrate how the Bayesian approach can be employed to obtain reliable streamflow predictive distributions based on signatures. A case study is presented, where a hydrological model is calibrated on FDCs and additional signatures. We propose an approach where the likelihood function for the signatures is derived from the likelihood for streamflow (rather than using an "ad-hoc" likelihood for the signatures as done in previous approaches). This likelihood is not easily tractable analytically and we therefore cannot apply "simple" MCMC methods. This numerical problem is solved using Approximate Bayesian Computation (ABC). Our result indicate that the proposed approach is suitable for producing reliable streamflow predictive distributions based on calibration to signature data. Moreover, our results provide indications on which signatures are more appropriate to represent the information content of the hydrograph.

Computational Account of Spontaneous Activity as a Signature of Predictive Coding

PubMed Central

Koren, Veronika

2017-01-01

Spontaneous activity is commonly observed in a variety of cortical states. Experimental evidence suggested that neural assemblies undergo slow oscillations with Up ad Down states even when the network is isolated from the rest of the brain. Here we show that these spontaneous events can be generated by the recurrent connections within the network and understood as signatures of neural circuits that are correcting their internal representation. A noiseless spiking neural network can represent its input signals most accurately when excitatory and inhibitory currents are as strong and as tightly balanced as possible. However, in the presence of realistic neural noise and synaptic delays, this may result in prohibitively large spike counts. An optimal working regime can be found by considering terms that control firing rates in the objective function from which the network is derived and then minimizing simultaneously the coding error and the cost of neural activity. In biological terms, this is equivalent to tuning neural thresholds and after-spike hyperpolarization. In suboptimal working regimes, we observe spontaneous activity even in the absence of feed-forward inputs. In an all-to-all randomly connected network, the entire population is involved in Up states. In spatially organized networks with local connectivity, Up states spread through local connections between neurons of similar selectivity and take the form of a traveling wave. Up states are observed for a wide range of parameters and have similar statistical properties in both active and quiescent state. In the optimal working regime, Up states are vanishing, leaving place to asynchronous activity, suggesting that this working regime is a signature of maximally efficient coding. Although they result in a massive increase in the firing activity, the read-out of spontaneous Up states is in fact orthogonal to the stimulus representation, therefore interfering minimally with the network function. PMID:28114353

Target signature modeling and bistatic scattering measurement studies

NASA Technical Reports Server (NTRS)

Burnside, W. D.; Lee, T. H.; Rojas, R.; Marhefka, R. J.; Bensman, D.

1989-01-01

Four areas of study are summarized: bistatic scattering measurements studies for a compact range; target signature modeling for test and evaluation hardware in the loop situation; aircraft code modification study; and SATCOM antenna studies on aircraft.

Experimental and Computational Sonic Boom Assessment of Boeing N+2 Low Boom Models

NASA Technical Reports Server (NTRS)

Durston, Donald A.; Elmiligui, Alaa; Cliff, Susan E.; Winski, Courtney S.; Carter, Melissa B.; Walker, Eric L.

2015-01-01

Near-field pressure signatures were measured and computational predictions made for several sonic boom models representing Boeing's Quiet Experimental Validation Concept (QEVC) supersonic transport, as well as three axisymmetric calibration models. Boeing developed the QEVC under a NASA Research Announcement (NRA) contract for Experimental Systems Validations for N+2 Supersonic Commercial Transport Aircraft, which was led by the NASA High Speed Project under the Fundamental Aeronautics Program. The concept was designed to address environmental and performance goals given in the NRA, specifically for low sonic boom loudness levels and high cruise efficiency, for an aircraft anticipated to enter service in the 2020 timeframe. Wind tunnel tests were conducted on the aircraft and calibration models during Phases I and II of the NRA contract from 2011 to 2013 in the NASA Ames 9- by 7-Foot and NASA Glenn 8- by 6-Foot Supersonic Wind Tunnels. Sonic boom pressure signatures were acquired primarily at Mach 1.6 and 1.8, and force and moment data were acquired from Mach 0.8 to 1.8. The sonic boom test data were obtained using a 2-in. flat-top pressure rail and a 14-in. round-top tapered "reflection factor 1" (RF1) pressure rail. Both rails capture an entire pressure signature in one data point, and successive signatures at varying positions along or above the rail were used to improve data quality through spatial averaging. The sonic boom data obtained by the rails were validated with high-fidelity numerical simulations of off-body pressures using the CFD codes USM3D, Cart3D, and OVERFLOW. The test results from the RF1 rail showed good agreement between the computational and experimental data when a variety of testing techniques including spatial averaging of a series of pressure signatures were employed, however, reflections off the 2-in. flat-top rail caused distortions in the signatures that did not agree with the CFD predictions. The 9 x 7 and 8 x 6 wind tunnels generally produced comparable data.

A gene expression signature of RAS pathway dependence predicts response to PI3K and RAS pathway inhibitors and expands the population of RAS pathway activated tumors.

PubMed

Loboda, Andrey; Nebozhyn, Michael; Klinghoffer, Rich; Frazier, Jason; Chastain, Michael; Arthur, William; Roberts, Brian; Zhang, Theresa; Chenard, Melissa; Haines, Brian; Andersen, Jannik; Nagashima, Kumiko; Paweletz, Cloud; Lynch, Bethany; Feldman, Igor; Dai, Hongyue; Huang, Pearl; Watters, James

2010-06-30

Hyperactivation of the Ras signaling pathway is a driver of many cancers, and RAS pathway activation can predict response to targeted therapies. Therefore, optimal methods for measuring Ras pathway activation are critical. The main focus of our work was to develop a gene expression signature that is predictive of RAS pathway dependence. We used the coherent expression of RAS pathway-related genes across multiple datasets to derive a RAS pathway gene expression signature and generate RAS pathway activation scores in pre-clinical cancer models and human tumors. We then related this signature to KRAS mutation status and drug response data in pre-clinical and clinical datasets. The RAS signature score is predictive of KRAS mutation status in lung tumors and cell lines with high (> 90%) sensitivity but relatively low (50%) specificity due to samples that have apparent RAS pathway activation in the absence of a KRAS mutation. In lung and breast cancer cell line panels, the RAS pathway signature score correlates with pMEK and pERK expression, and predicts resistance to AKT inhibition and sensitivity to MEK inhibition within both KRAS mutant and KRAS wild-type groups. The RAS pathway signature is upregulated in breast cancer cell lines that have acquired resistance to AKT inhibition, and is downregulated by inhibition of MEK. In lung cancer cell lines knockdown of KRAS using siRNA demonstrates that the RAS pathway signature is a better measure of dependence on RAS compared to KRAS mutation status. In human tumors, the RAS pathway signature is elevated in ER negative breast tumors and lung adenocarcinomas, and predicts resistance to cetuximab in metastatic colorectal cancer. These data demonstrate that the RAS pathway signature is superior to KRAS mutation status for the prediction of dependence on RAS signaling, can predict response to PI3K and RAS pathway inhibitors, and is likely to have the most clinical utility in lung and breast tumors.

Identification of differentially expressed small non-coding RNAs in the legume endosymbiont Sinorhizobium meliloti by comparative genomics

PubMed Central

del Val, Coral; Rivas, Elena; Torres-Quesada, Omar; Toro, Nicolás; Jiménez-Zurdo, José I

2007-01-01

Bacterial small non-coding RNAs (sRNAs) are being recognized as novel widespread regulators of gene expression in response to environmental signals. Here, we present the first search for sRNA-encoding genes in the nitrogen-fixing endosymbiont Sinorhizobium meliloti, performed by a genome-wide computational analysis of its intergenic regions. Comparative sequence data from eight related α-proteobacteria were obtained, and the interspecies pairwise alignments were scored with the programs eQRNA and RNAz as complementary predictive tools to identify conserved and stable secondary structures corresponding to putative non-coding RNAs. Northern experiments confirmed that eight of the predicted loci, selected among the original 32 candidates as most probable sRNA genes, expressed small transcripts. This result supports the combined use of eQRNA and RNAz as a robust strategy to identify novel sRNAs in bacteria. Furthermore, seven of the transcripts accumulated differentially in free-living and symbiotic conditions. Experimental mapping of the 5′-ends of the detected transcripts revealed that their encoding genes are organized in autonomous transcription units with recognizable promoter and, in most cases, termination signatures. These findings suggest novel regulatory functions for sRNAs related to the interactions of α-proteobacteria with their eukaryotic hosts. PMID:17971083

Autonomous target recognition using remotely sensed surface vibration measurements

NASA Astrophysics Data System (ADS)

Geurts, James; Ruck, Dennis W.; Rogers, Steven K.; Oxley, Mark E.; Barr, Dallas N.

1993-09-01

The remotely measured surface vibration signatures of tactical military ground vehicles are investigated for use in target classification and identification friend or foe (IFF) systems. The use of remote surface vibration sensing by a laser radar reduces the effects of partial occlusion, concealment, and camouflage experienced by automatic target recognition systems using traditional imagery in a tactical battlefield environment. Linear Predictive Coding (LPC) efficiently represents the vibration signatures and nearest neighbor classifiers exploit the LPC feature set using a variety of distortion metrics. Nearest neighbor classifiers achieve an 88 percent classification rate in an eight class problem, representing a classification performance increase of thirty percent from previous efforts. A novel confidence figure of merit is implemented to attain a 100 percent classification rate with less than 60 percent rejection. The high classification rates are achieved on a target set which would pose significant problems to traditional image-based recognition systems. The targets are presented to the sensor in a variety of aspects and engine speeds at a range of 1 kilometer. The classification rates achieved demonstrate the benefits of using remote vibration measurement in a ground IFF system. The signature modeling and classification system can also be used to identify rotary and fixed-wing targets.

Astronomy in Denver: Polarization of bow shock nebulae around massive stars

NASA Astrophysics Data System (ADS)

Shrestha, Manisha; Hoffman, Jennifer L.; Ignace, Richard; Neilson, Hilding; Richard Ignace

2018-06-01

Stellar wind bow shocks are structures created when stellar winds with supersonic relative velocities interact with the local interstellar medium (ISM). They can be studied to understand the properties of stars as well as the ISM. Since bow shocks are asymmetric, light becomes polarized by scattering in the regions of enhanced density they create. We use a Monte Carlo radiative transfer code calle SLIP to simulate the polarization signatures produced by both resolved and unresolved bow shocks with analytically derived shapes and density structures. When electron scattering is the polarizing mechanism, we find that optical depth plays an important role in the polarization signatures. While results for low optical depths reproduce theoretical predictions, higher optical depths produce higher polarization and position angle rotations at specific viewing angles. This is due to the geometrical properties of the bow shock along with multiple scattering effects. For dust scattering, we find that the polarization signature is strongly affected by wavelength, dust size, dust composition, and viewing angle. Depending on the viewing angle, the polarization magnitude may increase or decrease as a function of wavelength. We will present results from these simulations and preliminary comparisons with observational data.

Seismic diagnosis from gravity modes strongly affected by rotation

NASA Astrophysics Data System (ADS)

Prat, Vincent; Mathis, Stéphane; Lignières, François; Ballot, Jérôme; Culpin, Pierre-Marie

2017-10-01

Most of the information we have about the internal rotation of stars comes from modes that are weakly affected by rotation, for example by using rotational splittings. In contrast, we present here a method, based on the asymptotic theory of Prat et al. (2016), which allows us to analyse the signature of rotation where its effect is the most important, that is in low-frequency gravity modes that are strongly affected by rotation. For such modes, we predict two spectral patterns that could be confronted to observed spectra and those computed using fully two-dimensional oscillation codes.

From sequence to enzyme mechanism using multi-label machine learning.

PubMed

De Ferrari, Luna; Mitchell, John B O

2014-05-19

In this work we predict enzyme function at the level of chemical mechanism, providing a finer granularity of annotation than traditional Enzyme Commission (EC) classes. Hence we can predict not only whether a putative enzyme in a newly sequenced organism has the potential to perform a certain reaction, but how the reaction is performed, using which cofactors and with susceptibility to which drugs or inhibitors, details with important consequences for drug and enzyme design. Work that predicts enzyme catalytic activity based on 3D protein structure features limits the prediction of mechanism to proteins already having either a solved structure or a close relative suitable for homology modelling. In this study, we evaluate whether sequence identity, InterPro or Catalytic Site Atlas sequence signatures provide enough information for bulk prediction of enzyme mechanism. By splitting MACiE (Mechanism, Annotation and Classification in Enzymes database) mechanism labels to a finer granularity, which includes the role of the protein chain in the overall enzyme complex, the method can predict at 96% accuracy (and 96% micro-averaged precision, 99.9% macro-averaged recall) the MACiE mechanism definitions of 248 proteins available in the MACiE, EzCatDb (Database of Enzyme Catalytic Mechanisms) and SFLD (Structure Function Linkage Database) databases using an off-the-shelf K-Nearest Neighbours multi-label algorithm. We find that InterPro signatures are critical for accurate prediction of enzyme mechanism. We also find that incorporating Catalytic Site Atlas attributes does not seem to provide additional accuracy. The software code (ml2db), data and results are available online at http://sourceforge.net/projects/ml2db/ and as supplementary files.

Changes in Gene Expression Predicting Local Control in Cervical Cancer: Results from Radiation Therapy Oncology Group 0128

PubMed Central

Weidhaas, Joanne B.; Li, Shu-Xia; Winter, Kathryn; Ryu, Janice; Jhingran, Anuja; Miller, Bridgette; Dicker, Adam P.; Gaffney, David

2009-01-01

Purpose To evaluate the potential of gene expression signatures to predict response to treatment in locally advanced cervical cancer treated with definitive chemotherapy and radiation. Experimental Design Tissue biopsies were collected from patients participating in Radiation Therapy Oncology Group (RTOG) 0128, a phase II trial evaluating the benefit of celecoxib in addition to cisplatin chemotherapy and radiation for locally advanced cervical cancer. Gene expression profiling was done and signatures of pretreatment, mid-treatment (before the first implant), and “changed” gene expression patterns between pre- and mid-treatment samples were determined. The ability of the gene signatures to predict local control versus local failure was evaluated. Two-group t test was done to identify the initial gene set separating these end points. Supervised classification methods were used to enrich the gene sets. The results were further validated by leave-one-out and 2-fold cross-validation. Results Twenty-two patients had suitable material from pretreatment samples for analysis, and 13 paired pre- and mid-treatment samples were obtained. The changed gene expression signatures between the pre- and mid-treatment biopsies predicted response to treatment, separating patients with local failures from those who achieved local control with a seven-gene signature. The in-sample prediction rate, leave-one-out prediction rate, and 2-fold prediction rate are 100% for this seven-gene signature. This signature was enriched for cell cycle genes. Conclusions Changed gene expression signatures during therapy in cervical cancer can predict outcome as measured by local control. After further validation, such findings could be applied to direct additional therapy for cervical cancer patients treated with chemotherapy and radiation. PMID:19509178

Factor models for cancer signatures

NASA Astrophysics Data System (ADS)

Kakushadze, Zura; Yu, Willie

2016-11-01

We present a novel method for extracting cancer signatures by applying statistical risk models (http://ssrn.com/abstract=2732453) from quantitative finance to cancer genome data. Using 1389 whole genome sequenced samples from 14 cancers, we identify an ;overall; mode of somatic mutational noise. We give a prescription for factoring out this noise and source code for fixing the number of signatures. We apply nonnegative matrix factorization (NMF) to genome data aggregated by cancer subtype and filtered using our method. The resultant signatures have substantially lower variability than those from unfiltered data. Also, the computational cost of signature extraction is cut by about a factor of 10. We find 3 novel cancer signatures, including a liver cancer dominant signature (96% contribution) and a renal cell carcinoma signature (70% contribution). Our method accelerates finding new cancer signatures and improves their overall stability. Reciprocally, the methods for extracting cancer signatures could have interesting applications in quantitative finance.

Antipsychotic dose modulates behavioral and neural responses to feedback during reinforcement learning in schizophrenia.

PubMed

Insel, Catherine; Reinen, Jenna; Weber, Jochen; Wager, Tor D; Jarskog, L Fredrik; Shohamy, Daphna; Smith, Edward E

2014-03-01

Schizophrenia is characterized by an abnormal dopamine system, and dopamine blockade is the primary mechanism of antipsychotic treatment. Consistent with the known role of dopamine in reward processing, prior research has demonstrated that patients with schizophrenia exhibit impairments in reward-based learning. However, it remains unknown how treatment with antipsychotic medication impacts the behavioral and neural signatures of reinforcement learning in schizophrenia. The goal of this study was to examine whether antipsychotic medication modulates behavioral and neural responses to prediction error coding during reinforcement learning. Patients with schizophrenia completed a reinforcement learning task while undergoing functional magnetic resonance imaging. The task consisted of two separate conditions in which participants accumulated monetary gain or avoided monetary loss. Behavioral results indicated that antipsychotic medication dose was associated with altered behavioral approaches to learning, such that patients taking higher doses of medication showed increased sensitivity to negative reinforcement. Higher doses of antipsychotic medication were also associated with higher learning rates (LRs), suggesting that medication enhanced sensitivity to trial-by-trial feedback. Neuroimaging data demonstrated that antipsychotic dose was related to differences in neural signatures of feedback prediction error during the loss condition. Specifically, patients taking higher doses of medication showed attenuated prediction error responses in the striatum and the medial prefrontal cortex. These findings indicate that antipsychotic medication treatment may influence motivational processes in patients with schizophrenia.

Predictions of runoff signatures in ungauged basins: Austrian case study

NASA Astrophysics Data System (ADS)

Viglione, A.; Parajka, J.; Salinas, J.; Rogger, M.; Sivapalan, M.; Bloeschl, G.

2012-12-01

Runoff variability can be broken up into several components, each of them meaningful of a certain class of applications of societal relevance: annual runoff, seasonal runoff, flow duration curve, low flows, floods and hydrographs. We call them runoff signatures and we view them as a manifestation of catchment functioning at different time scales, as emergent properties of the complex systems that catchments are. Just as a medical doctor has many different options for studying the state and functioning of a patient, we can infer the state and functioning of a catchment observing its runoff signatures. But what can we do in the absence of runoff data? This study aims to understand how well one can predict runoff signatures in ungauged catchments. The comparison across signatures is based on one consistent data set (Austria) and one regionalisation method (Top-Kriging) in order to explore the relative performance of the predictions of each of the signatures. Results indicate that the performance, assessed by cross-validation, is best for annual and seasonal runoff, it degrades as one moves to low flows and floods and goes up again to high values for runoff hydrographs. Also, dedicated regionalisation methods, i.e. focusing on particular signatures and their characteristics, provide better predictions of the signatures than regionalisation of the entire hydrograph. These results suggest that the use of signatures in the calibration or assessment of process models can be valuable, in that this can lead to models predicting runoff correctly for the right reasons.

A probabilistic methodology for radar cross section prediction in conceptual aircraft design

NASA Astrophysics Data System (ADS)

Hines, Nathan Robert

System effectiveness has increasingly become the prime metric for the evaluation of military aircraft. As such, it is the decision maker's/designer's goal to maximize system effectiveness. Industry and government research documents indicate that all future military aircraft will incorporate signature reduction as an attempt to improve system effectiveness and reduce the cost of attrition. Today's operating environments demand low observable aircraft which are able to reliably take out valuable, time critical targets. Thus it is desirable to be able to design vehicles that are balanced for increased effectiveness. Previous studies have shown that shaping of the vehicle is one of the most important contributors to radar cross section, a measure of radar signature, and must be considered from the very beginning of the design process. Radar cross section estimation should be incorporated into conceptual design to develop more capable systems. This research strives to meet these needs by developing a conceptual design tool that predicts radar cross section for parametric geometries. This tool predicts the absolute radar cross section of the vehicle as well as the impact of geometry changes, allowing for the simultaneous tradeoff of the aerodynamic, performance, and cost characteristics of the vehicle with the radar cross section. Furthermore, this tool can be linked to a campaign theater analysis code to demonstrate the changes in system and system of system effectiveness due to changes in aircraft geometry. A general methodology was developed and implemented and sample computer codes applied to prototype the proposed process. Studies utilizing this radar cross section tool were subsequently performed to demonstrate the capabilities of this method and show the impact that various inputs have on the outputs of these models. The F/A-18 aircraft configuration was chosen as a case study vehicle to perform a design space exercise and to investigate the relative impact of shaping parameters on radar cross section. Finally, two unique low observable configurations were analyzed to examine the impact of shaping for stealthiness.

A gene expression signature of RAS pathway dependence predicts response to PI3K and RAS pathway inhibitors and expands the population of RAS pathway activated tumors

PubMed Central

2010-01-01

Background Hyperactivation of the Ras signaling pathway is a driver of many cancers, and RAS pathway activation can predict response to targeted therapies. Therefore, optimal methods for measuring Ras pathway activation are critical. The main focus of our work was to develop a gene expression signature that is predictive of RAS pathway dependence. Methods We used the coherent expression of RAS pathway-related genes across multiple datasets to derive a RAS pathway gene expression signature and generate RAS pathway activation scores in pre-clinical cancer models and human tumors. We then related this signature to KRAS mutation status and drug response data in pre-clinical and clinical datasets. Results The RAS signature score is predictive of KRAS mutation status in lung tumors and cell lines with high (> 90%) sensitivity but relatively low (50%) specificity due to samples that have apparent RAS pathway activation in the absence of a KRAS mutation. In lung and breast cancer cell line panels, the RAS pathway signature score correlates with pMEK and pERK expression, and predicts resistance to AKT inhibition and sensitivity to MEK inhibition within both KRAS mutant and KRAS wild-type groups. The RAS pathway signature is upregulated in breast cancer cell lines that have acquired resistance to AKT inhibition, and is downregulated by inhibition of MEK. In lung cancer cell lines knockdown of KRAS using siRNA demonstrates that the RAS pathway signature is a better measure of dependence on RAS compared to KRAS mutation status. In human tumors, the RAS pathway signature is elevated in ER negative breast tumors and lung adenocarcinomas, and predicts resistance to cetuximab in metastatic colorectal cancer. Conclusions These data demonstrate that the RAS pathway signature is superior to KRAS mutation status for the prediction of dependence on RAS signaling, can predict response to PI3K and RAS pathway inhibitors, and is likely to have the most clinical utility in lung and breast tumors. PMID:20591134

Clinical Value of Prognosis Gene Expression Signatures in Colorectal Cancer: A Systematic Review

PubMed Central

Cordero, David; Riccadonna, Samantha; Solé, Xavier; Crous-Bou, Marta; Guinó, Elisabet; Sanjuan, Xavier; Biondo, Sebastiano; Soriano, Antonio; Jurman, Giuseppe; Capella, Gabriel; Furlanello, Cesare; Moreno, Victor

2012-01-01

Introduction The traditional staging system is inadequate to identify those patients with stage II colorectal cancer (CRC) at high risk of recurrence or with stage III CRC at low risk. A number of gene expression signatures to predict CRC prognosis have been proposed, but none is routinely used in the clinic. The aim of this work was to assess the prediction ability and potential clinical usefulness of these signatures in a series of independent datasets. Methods A literature review identified 31 gene expression signatures that used gene expression data to predict prognosis in CRC tissue. The search was based on the PubMed database and was restricted to papers published from January 2004 to December 2011. Eleven CRC gene expression datasets with outcome information were identified and downloaded from public repositories. Random Forest classifier was used to build predictors from the gene lists. Matthews correlation coefficient was chosen as a measure of classification accuracy and its associated p-value was used to assess association with prognosis. For clinical usefulness evaluation, positive and negative post-tests probabilities were computed in stage II and III samples. Results Five gene signatures showed significant association with prognosis and provided reasonable prediction accuracy in their own training datasets. Nevertheless, all signatures showed low reproducibility in independent data. Stratified analyses by stage or microsatellite instability status showed significant association but limited discrimination ability, especially in stage II tumors. From a clinical perspective, the most predictive signatures showed a minor but significant improvement over the classical staging system. Conclusions The published signatures show low prediction accuracy but moderate clinical usefulness. Although gene expression data may inform prognosis, better strategies for signature validation are needed to encourage their widespread use in the clinic. PMID:23145004

Correlation of predicted and measured sonic boom characteristics from the reentry of STS-1 orbiter

NASA Technical Reports Server (NTRS)

Garcia, F., Jr.; Jones, J. H.; Henderson, H. R.

1985-01-01

Characteristics from sonic boom pressure signatures recorded at 11 locations during reentry of the Space Shuttle Orbiter Columbia are correlated with characteristics of wind tunnel signatures extrapolated from flight altitudes for Mach numbers ranging from 1.23 to 5.87. The flight pressure signature were recorded by microphones positioned at two levels near the descent groundtrack along the California corridor. The wind tunnel signatures used in theoretical predictions were measured using a 0.0041-scale model Orbiter. The mean difference between all measured and predicted overpressures is 12 percent from measured levels. With one exception, the flight signatures are very similar to theoretical n-waves.

Non-coding cancer driver candidates identified with a sample- and position-specific model of the somatic mutation rate

PubMed Central

Juul, Malene; Bertl, Johanna; Guo, Qianyun; Nielsen, Morten Muhlig; Świtnicki, Michał; Hornshøj, Henrik; Madsen, Tobias; Hobolth, Asger; Pedersen, Jakob Skou

2017-01-01

Non-coding mutations may drive cancer development. Statistical detection of non-coding driver regions is challenged by a varying mutation rate and uncertainty of functional impact. Here, we develop a statistically founded non-coding driver-detection method, ncdDetect, which includes sample-specific mutational signatures, long-range mutation rate variation, and position-specific impact measures. Using ncdDetect, we screened non-coding regulatory regions of protein-coding genes across a pan-cancer set of whole-genomes (n = 505), which top-ranked known drivers and identified new candidates. For individual candidates, presence of non-coding mutations associates with altered expression or decreased patient survival across an independent pan-cancer sample set (n = 5454). This includes an antigen-presenting gene (CD1A), where 5’UTR mutations correlate significantly with decreased survival in melanoma. Additionally, mutations in a base-excision-repair gene (SMUG1) correlate with a C-to-T mutational-signature. Overall, we find that a rich model of mutational heterogeneity facilitates non-coding driver identification and integrative analysis points to candidates of potential clinical relevance. DOI: http://dx.doi.org/10.7554/eLife.21778.001 PMID:28362259

Omics AnalySIs System for PRecision Oncology (OASISPRO): A Web-based Omics Analysis Tool for Clinical Phenotype Prediction.

PubMed

Yu, Kun-Hsing; Fitzpatrick, Michael R; Pappas, Luke; Chan, Warren; Kung, Jessica; Snyder, Michael

2017-09-12

Precision oncology is an approach that accounts for individual differences to guide cancer management. Omics signatures have been shown to predict clinical traits for cancer patients. However, the vast amount of omics information poses an informatics challenge in systematically identifying patterns associated with health outcomes, and no general-purpose data-mining tool exists for physicians, medical researchers, and citizen scientists without significant training in programming and bioinformatics. To bridge this gap, we built the Omics AnalySIs System for PRecision Oncology (OASISPRO), a web-based system to mine the quantitative omics information from The Cancer Genome Atlas (TCGA). This system effectively visualizes patients' clinical profiles, executes machine-learning algorithms of choice on the omics data, and evaluates the prediction performance using held-out test sets. With this tool, we successfully identified genes strongly associated with tumor stage, and accurately predicted patients' survival outcomes in many cancer types, including mesothelioma and adrenocortical carcinoma. By identifying the links between omics and clinical phenotypes, this system will facilitate omics studies on precision cancer medicine and contribute to establishing personalized cancer treatment plans. This web-based tool is available at http://tinyurl.com/oasispro ;source codes are available at http://tinyurl.com/oasisproSourceCode . © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Minimum Total-Squared-Correlation Quaternary Signature Sets: New Bounds and Optimal Designs

DTIC Science & Technology

2009-12-01

50, pp. 2433-2440, Oct. 2004. [11] G. S. Rajappan and M. L. Honig, “Signature sequence adaptation for DS - CDMA with multipath," IEEE J. Sel. Areas...OPTIMAL DESIGNS 3671 [14] C. Ding, M. Golin, and T. Kløve, “Meeting the Welch and Karystinos- Pados bounds on DS - CDMA binary signature sets," Des., Codes...Cryp- togr., vol. 30, pp. 73-84, Aug. 2003. [15] V. P. Ipatov, “On the Karystinos-Pados bounds and optimal binary DS - CDMA signature ensembles," IEEE

Draft versus finished sequence data for DNA and protein diagnostic signature development

PubMed Central

Gardner, Shea N.; Lam, Marisa W.; Smith, Jason R.; Torres, Clinton L.; Slezak, Tom R.

2005-01-01

Sequencing pathogen genomes is costly, demanding careful allocation of limited sequencing resources. We built a computational Sequencing Analysis Pipeline (SAP) to guide decisions regarding the amount of genomic sequencing necessary to develop high-quality diagnostic DNA and protein signatures. SAP uses simulations to estimate the number of target genomes and close phylogenetic relatives (near neighbors or NNs) to sequence. We use SAP to assess whether draft data are sufficient or finished sequencing is required using Marburg and variola virus sequences. Simulations indicate that intermediate to high-quality draft with error rates of 10−3–10−5 (∼8× coverage) of target organisms is suitable for DNA signature prediction. Low-quality draft with error rates of ∼1% (3× to 6× coverage) of target isolates is inadequate for DNA signature prediction, although low-quality draft of NNs is sufficient, as long as the target genomes are of high quality. For protein signature prediction, sequencing errors in target genomes substantially reduce the detection of amino acid sequence conservation, even if the draft is of high quality. In summary, high-quality draft of target and low-quality draft of NNs appears to be a cost-effective investment for DNA signature prediction, but may lead to underestimation of predicted protein signatures. PMID:16243783

Building gene expression signatures indicative of transcription factor activation to predict AOP modulation

EPA Science Inventory

Building gene expression signatures indicative of transcription factor activation to predict AOP modulation Adverse outcome pathways (AOPs) are a framework for predicting quantitative relationships between molecular initiatin...

Expression profiles analysis of long non-coding RNAs identified novel lncRNA biomarkers with predictive value in outcome of cutaneous melanoma.

PubMed

Ma, Xu; He, Zhijuan; Li, Ling; Yang, Daping; Liu, Guofeng

2017-09-29

Recent advancements in cancer biology have identified a large number of lncRNAs that are dysregulated expression in the development and tumorigenesis of cancers, highlighting the importance of lncRNAs as a key player for human cancers. However, the prognostic value of lncRNAs still remains unclear and needs to be further investigated. In the present study, we aim to assess the prognostic value of lncRNAs in cutaneous melanoma by integrated lncRNA expression profiles from TCGA database and matched clinical information from a large cohort of patients with cutaneous melanoma. We finally identified a set of six lncRNAs that are significantly associated with survival of patients with cutaneous melanoma. A linear combination of six lncRNAs ( LINC01260, HCP5, PIGBOS1, RP11-247L20.4, CTA-292E10.6 and CTB-113P19.5 ) was constructed as a six-lncRNA signature which classified patients of training cohort into the high-risk group and low-risk group with significantly different survival time. The prognostic value of the six-lncRNA signature was validated in both the validation cohort and entire TCGA cohort. Moreover, the six-lncRNA signature is independent of known clinic-pathological factors by multivariate Cox regression analysis and demonstrated good performance for predicting three- and five-year overall survival by time-dependent receiver operating characteristic (ROC) analysis. Our study provides novel insights into the molecular heterogeneity of cutaneous melanoma and also shows potentially important implications of lncRNAs for prognosis and therapy for cutaneous melanoma.

27 CFR 73.12 - What security controls must I use for identification codes and passwords?

Code of Federal Regulations, 2010 CFR

2010-04-01

... 27 Alcohol, Tobacco Products and Firearms 2 2010-04-01 2010-04-01 false What security controls... controls must I use for identification codes and passwords? If you use electronic signatures based upon use of identification codes in combination with passwords, you must employ controls to ensure their...

Bar Coding the U. S. Government Bill of Lading and the Material Inspection and Receiving Report.

DTIC Science & Technology

1984-12-01

of respondents K because some of the replies did not respond to this question.) TABLE 3-2. DD 250 PROCESSING CAPABILITIES AUTOMiATED - BAR CODE...Proposed minimum data elements (both human readable and bar coded) required and why? (3) Proposed signature requirement changes and why? (4) Proposed

Radiation Modeling for the Reentry of the Hayabusa Sample Return Capsule

NASA Technical Reports Server (NTRS)

Winter, Michael W.; McDaniel, Ryan D.; Chen, Yih-Kang; Liu, Yen; Saunders, David; Jenniskens, Petrus

2011-01-01

Predicted shock-layer emission signatures of the Japanese Hayabusa capsule during its reentry are presented for comparison with flight measurements made during an airborne observation mission using NASA s DC-8 Airborne Laboratory. For each altitude, lines of sight were extracted from flow field solutions computed using an inhouse high-fidelity CFD code, DPLR, at 11 points along the flight trajectory of the capsule. These lines of sight were used as inputs for the line-by-line radiation code NEQAIR, and emission spectra of the air plasma were computed in the wavelength range from 300 nm to 1600 nm, a range which covers all of the different experiments onboard the DC-8. In addition, the computed flow field solutions were post-processed with the material thermal response code FIAT, and the resulting surface temperatures of the heat shield were used to generate thermal emission spectra based on Planck radiation. Both spectra were summed and integrated over the flow field. The resulting emission at each trajectory point was propagated to the DC-8 position and transformed into incident irradiance. Comparisons with experimental data are shown.

Prognostic breast cancer signature identified from 3D culture model accurately predicts clinical outcome across independent datasets

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

Martin, Katherine J.; Patrick, Denis R.; Bissell, Mina J.

2008-10-20

One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasetsmore » having 295, 286, and 118 samples, respectively. Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome. The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds prognostic value for both ER-positive and ER-negative breast cancer. The signature was selected using a novel biological approach and hence holds promise to represent the key biological processes of breast cancer.« less

Prioritizing Therapeutics for Lung Cancer: An Integrative Meta-analysis of Cancer Gene Signatures and Chemogenomic Data

PubMed Central

Fortney, Kristen; Griesman, Joshua; Kotlyar, Max; Pastrello, Chiara; Angeli, Marc; Sound-Tsao, Ming; Jurisica, Igor

2015-01-01

Repurposing FDA-approved drugs with the aid of gene signatures of disease can accelerate the development of new therapeutics. A major challenge to developing reliable drug predictions is heterogeneity. Different gene signatures of the same disease or drug treatment often show poor overlap across studies, as a consequence of both biological and technical variability, and this can affect the quality and reproducibility of computational drug predictions. Existing algorithms for signature-based drug repurposing use only individual signatures as input. But for many diseases, there are dozens of signatures in the public domain. Methods that exploit all available transcriptional knowledge on a disease should produce improved drug predictions. Here, we adapt an established meta-analysis framework to address the problem of drug repurposing using an ensemble of disease signatures. Our computational pipeline takes as input a collection of disease signatures, and outputs a list of drugs predicted to consistently reverse pathological gene changes. We apply our method to conduct the largest and most systematic repurposing study on lung cancer transcriptomes, using 21 signatures. We show that scaling up transcriptional knowledge significantly increases the reproducibility of top drug hits, from 44% to 78%. We extensively characterize drug hits in silico, demonstrating that they slow growth significantly in nine lung cancer cell lines from the NCI-60 collection, and identify CALM1 and PLA2G4A as promising drug targets for lung cancer. Our meta-analysis pipeline is general, and applicable to any disease context; it can be applied to improve the results of signature-based drug repurposing by leveraging the large number of disease signatures in the public domain. PMID:25786242

Numerical prediction of meteoric infrasound signatures

NASA Astrophysics Data System (ADS)

Nemec, Marian; Aftosmis, Michael J.; Brown, Peter G.

2017-06-01

We present a thorough validation of a computational approach to predict infrasonic signatures of centimeter-sized meteoroids. This is the first direct comparison of computational results with well-calibrated observations that include trajectories, optical masses and ground pressure signatures. We assume that the energy deposition along the meteor trail is dominated by atmospheric drag and simulate a steady, inviscid flow of air in thermochemical equilibrium to compute a near-body pressure signature of the meteoroid. This signature is then propagated through a stratified and windy atmosphere to the ground using a methodology from aircraft sonic-boom analysis. The results show that when the source of the signature is the cylindrical Mach-cone, the simulations closely match the observations. The prediction of the shock rise-time, the zero-peak amplitude of the waveform and the duration of the positive pressure phase are consistently within 10% of the measurements. Uncertainty in primarily the shape of the meteoroid results in a poorer prediction of the trailing part of the waveform. Overall, our results independently verify energy deposition estimates deduced from optical observations.

MicroRNA signature of the human developing pancreas.

PubMed

Rosero, Samuel; Bravo-Egana, Valia; Jiang, Zhijie; Khuri, Sawsan; Tsinoremas, Nicholas; Klein, Dagmar; Sabates, Eduardo; Correa-Medina, Mayrin; Ricordi, Camillo; Domínguez-Bendala, Juan; Diez, Juan; Pastori, Ricardo L

2010-09-22

MicroRNAs are non-coding RNAs that regulate gene expression including differentiation and development by either inhibiting translation or inducing target degradation. The aim of this study is to determine the microRNA expression signature during human pancreatic development and to identify potential microRNA gene targets calculating correlations between the signature microRNAs and their corresponding mRNA targets, predicted by bioinformatics, in genome-wide RNA microarray study. The microRNA signature of human fetal pancreatic samples 10-22 weeks of gestational age (wga), was obtained by PCR-based high throughput screening with Taqman Low Density Arrays. This method led to identification of 212 microRNAs. The microRNAs were classified in 3 groups: Group number I contains 4 microRNAs with the increasing profile; II, 35 microRNAs with decreasing profile and III with 173 microRNAs, which remain unchanged. We calculated Pearson correlations between the expression profile of microRNAs and target mRNAs, predicted by TargetScan 5.1 and miRBase algorithms, using genome-wide mRNA expression data. Group I correlated with the decreasing expression of 142 target mRNAs and Group II with the increasing expression of 876 target mRNAs. Most microRNAs correlate with multiple targets, just as mRNAs are targeted by multiple microRNAs. Among the identified targets are the genes and transcription factors known to play an essential role in pancreatic development. We have determined specific groups of microRNAs in human fetal pancreas that change the degree of their expression throughout the development. A negative correlative analysis suggests an intertwined network of microRNAs and mRNAs collaborating with each other. This study provides information leading to potential two-way level of combinatorial control regulating gene expression through microRNAs targeting multiple mRNAs and, conversely, target mRNAs regulated in parallel by other microRNAs as well. This study may further the understanding of gene expression regulation in the human developing pancreas.

MicroRNA signature of the human developing pancreas

PubMed Central

2010-01-01

Background MicroRNAs are non-coding RNAs that regulate gene expression including differentiation and development by either inhibiting translation or inducing target degradation. The aim of this study is to determine the microRNA expression signature during human pancreatic development and to identify potential microRNA gene targets calculating correlations between the signature microRNAs and their corresponding mRNA targets, predicted by bioinformatics, in genome-wide RNA microarray study. Results The microRNA signature of human fetal pancreatic samples 10-22 weeks of gestational age (wga), was obtained by PCR-based high throughput screening with Taqman Low Density Arrays. This method led to identification of 212 microRNAs. The microRNAs were classified in 3 groups: Group number I contains 4 microRNAs with the increasing profile; II, 35 microRNAs with decreasing profile and III with 173 microRNAs, which remain unchanged. We calculated Pearson correlations between the expression profile of microRNAs and target mRNAs, predicted by TargetScan 5.1 and miRBase altgorithms, using genome-wide mRNA expression data. Group I correlated with the decreasing expression of 142 target mRNAs and Group II with the increasing expression of 876 target mRNAs. Most microRNAs correlate with multiple targets, just as mRNAs are targeted by multiple microRNAs. Among the identified targets are the genes and transcription factors known to play an essential role in pancreatic development. Conclusions We have determined specific groups of microRNAs in human fetal pancreas that change the degree of their expression throughout the development. A negative correlative analysis suggests an intertwined network of microRNAs and mRNAs collaborating with each other. This study provides information leading to potential two-way level of combinatorial control regulating gene expression through microRNAs targeting multiple mRNAs and, conversely, target mRNAs regulated in parallel by other microRNAs as well. This study may further the understanding of gene expression regulation in the human developing pancreas. PMID:20860821

Prediction of chemo-response in serous ovarian cancer.

PubMed

Gonzalez Bosquet, Jesus; Newtson, Andreea M; Chung, Rebecca K; Thiel, Kristina W; Ginader, Timothy; Goodheart, Michael J; Leslie, Kimberly K; Smith, Brian J

2016-10-19

Nearly one-third of serous ovarian cancer (OVCA) patients will not respond to initial treatment with surgery and chemotherapy and die within one year of diagnosis. If patients who are unlikely to respond to current standard therapy can be identified up front, enhanced tumor analyses and treatment regimens could potentially be offered. Using the Cancer Genome Atlas (TCGA) serous OVCA database, we previously identified a robust molecular signature of 422-genes associated with chemo-response. Our objective was to test whether this signature is an accurate and sensitive predictor of chemo-response in serous OVCA. We first constructed prediction models to predict chemo-response using our previously described 422-gene signature that was associated with response to treatment in serous OVCA. Performance of all prediction models were measured with area under the curves (AUCs, a measure of the model's accuracy) and their respective confidence intervals (CIs). To optimize the prediction process, we determined which elements of the signature most contributed to chemo-response prediction. All prediction models were replicated and validated using six publicly available independent gene expression datasets. The 422-gene signature prediction models predicted chemo-response with AUCs of ~70 %. Optimization of prediction models identified the 34 most important genes in chemo-response prediction. These 34-gene models had improved performance, with AUCs approaching 80 %. Both 422-gene and 34-gene prediction models were replicated and validated in six independent datasets. These prediction models serve as the foundation for the future development and implementation of a diagnostic tool to predict response to chemotherapy for serous OVCA patients.

Discovery of metabolic signatures for predicting whole organism toxicology.

PubMed

Hines, Adam; Staff, Fred J; Widdows, John; Compton, Russell M; Falciani, Francesco; Viant, Mark R

2010-06-01

Toxicological studies in sentinel organisms frequently use biomarkers to assess biological effect. Development of "omic" technologies has enhanced biomarker discovery at the molecular level, providing signatures unique to toxicant mode-of-action (MOA). However, these signatures often lack relevance to organismal responses, such as growth or reproduction, limiting their value for environmental monitoring. Our primary objective was to discover metabolic signatures in chemically exposed organisms that can predict physiological toxicity. Marine mussels (Mytilus edulis) were exposed for 7 days to 12 and 50 microg/l copper and 50 and 350 microg/l pentachlorophenol (PCP), toxicants with unique MOAs. Physiological responses comprised an established measure of organism energetic fitness, scope for growth (SFG). Metabolic fingerprints were measured in the same individuals using nuclear magnetic resonance-based metabolomics. Metabolic signatures predictive of SFG were sought using optimal variable selection strategies and multivariate regression and then tested upon independently field-sampled mussels from rural and industrialized sites. Copper and PCP induced rational metabolic and physiological changes. Measured and predicted SFG were highly correlated for copper (r(2) = 0.55, P = 2.82 x 10(-7)) and PCP (r(2) = 0.66, P = 3.20 x 10(-6)). Predictive metabolites included methionine and arginine/phosphoarginine for copper and allantoin, valine, and methionine for PCP. When tested on field-sampled animals, metabolic signatures predicted considerably reduced fitness of mussels from the contaminated (SFG = 6.0 J/h/g) versus rural (SFG = 15.2 J/h/g) site. We report the first successful discovery of metabolic signatures in chemically exposed environmental organisms that inform on molecular MOA and that can predict physiological toxicity. This could have far-reaching implications for monitoring impacts on environmental health.

Molecular Structure-Based Large-Scale Prediction of Chemical-Induced Gene Expression Changes.

PubMed

Liu, Ruifeng; AbdulHameed, Mohamed Diwan M; Wallqvist, Anders

2017-09-25

The quantitative structure-activity relationship (QSAR) approach has been used to model a wide range of chemical-induced biological responses. However, it had not been utilized to model chemical-induced genomewide gene expression changes until very recently, owing to the complexity of training and evaluating a very large number of models. To address this issue, we examined the performance of a variable nearest neighbor (v-NN) method that uses information on near neighbors conforming to the principle that similar structures have similar activities. Using a data set of gene expression signatures of 13 150 compounds derived from cell-based measurements in the NIH Library of Integrated Network-based Cellular Signatures program, we were able to make predictions for 62% of the compounds in a 10-fold cross validation test, with a correlation coefficient of 0.61 between the predicted and experimentally derived signatures-a reproducibility rivaling that of high-throughput gene expression measurements. To evaluate the utility of the predicted gene expression signatures, we compared the predicted and experimentally derived signatures in their ability to identify drugs known to cause specific liver, kidney, and heart injuries. Overall, the predicted and experimentally derived signatures had similar receiver operating characteristics, whose areas under the curve ranged from 0.71 to 0.77 and 0.70 to 0.73, respectively, across the three organ injury models. However, detailed analyses of enrichment curves indicate that signatures predicted from multiple near neighbors outperformed those derived from experiments, suggesting that averaging information from near neighbors may help improve the signal from gene expression measurements. Our results demonstrate that the v-NN method can serve as a practical approach for modeling large-scale, genomewide, chemical-induced, gene expression changes.

The X-Ray Polarization of the Accretion Disk Coronae of Active Galactic Nuclei

NASA Astrophysics Data System (ADS)

Beheshtipour, Banafsheh; Krawczynski, Henric; Malzac, Julien

2017-11-01

Hard X-rays observed in Active Galactic Nuclei (AGNs) are thought to originate from the Comptonization of the optical/UV accretion disk photons in a hot corona. Polarization studies of these photons can help to constrain the corona geometry and the plasma properties. We have developed a ray-tracing code that simulates the Comptonization of accretion disk photons in coronae of arbitrary shapes, and use it here to study the polarization of the X-ray emission from wedge and spherical coronae. We study the predicted polarization signatures for the fully relativistic and various approximate treatments of the elemental Compton scattering processes. We furthermore use the code to evaluate the impact of nonthermal electrons and cyclo-synchrotron photons on the polarization properties. Finally, we model the NuSTAR observations of the Seyfert I galaxy Mrk 335 and predict the associated polarization signal. Our studies show that X-ray polarimetry missions such as NASA’s Imaging X-ray Polarimetry Explorer and the X-ray Imaging Polarimetry Explorer proposed to ESA will provide valuable new information about the physical properties of the plasma close to the event horizon of AGN black holes.

Identification and substrate prediction of new Fragaria x ananassa aquaporins and expression in different tissues and during strawberry fruit development.

PubMed

Merlaen, Britt; De Keyser, Ellen; Van Labeke, Marie-Christine

2018-01-01

The newly identified aquaporin coding sequences presented here pave the way for further insights into the plant-water relations in the commercial strawberry ( Fragaria x ananassa ). Aquaporins are water channel proteins that allow water to cross (intra)cellular membranes. In Fragaria x ananassa , few of them have been identified hitherto, hampering the exploration of the water transport regulation at cellular level. Here, we present new aquaporin coding sequences belonging to different subclasses: plasma membrane intrinsic proteins subtype 1 and subtype 2 (PIP1 and PIP2) and tonoplast intrinsic proteins (TIP). The classification is based on phylogenetic analysis and is confirmed by the presence of conserved residues. Substrate-specific signature sequences (SSSSs) and specificity-determining positions (SDPs) predict the substrate specificity of each new aquaporin. Expression profiling in leaves, petioles and developing fruits reveals distinct patterns, even within the same (sub)class. Expression profiles range from leaf-specific expression over constitutive expression to fruit-specific expression. Both upregulation and downregulation during fruit ripening occur. Substrate specificity and expression profiles suggest that functional specialization exists among aquaporins belonging to a different but also to the same (sub)class.

matK-QR classifier: a patterns based approach for plant species identification.

PubMed

More, Ravi Prabhakar; Mane, Rupali Chandrashekhar; Purohit, Hemant J

2016-01-01

DNA barcoding is widely used and most efficient approach that facilitates rapid and accurate identification of plant species based on the short standardized segment of the genome. The nucleotide sequences of maturaseK ( matK ) and ribulose-1, 5-bisphosphate carboxylase ( rbcL ) marker loci are commonly used in plant species identification. Here, we present a new and highly efficient approach for identifying a unique set of discriminating nucleotide patterns to generate a signature (i.e. regular expression) for plant species identification. In order to generate molecular signatures, we used matK and rbcL loci datasets, which encompass 125 plant species in 52 genera reported by the CBOL plant working group. Initially, we performed Multiple Sequence Alignment (MSA) of all species followed by Position Specific Scoring Matrix (PSSM) for both loci to achieve a percentage of discrimination among species. Further, we detected Discriminating Patterns (DP) at genus and species level using PSSM for the matK dataset. Combining DP and consecutive pattern distances, we generated molecular signatures for each species. Finally, we performed a comparative assessment of these signatures with the existing methods including BLASTn, Support Vector Machines (SVM), Jrip-RIPPER, J48 (C4.5 algorithm), and the Naïve Bayes (NB) methods against NCBI-GenBank matK dataset. Due to the higher discrimination success obtained with the matK as compared to the rbcL , we selected matK gene for signature generation. We generated signatures for 60 species based on identified discriminating patterns at genus and species level. Our comparative assessment results suggest that a total of 46 out of 60 species could be correctly identified using generated signatures, followed by BLASTn (34 species), SVM (18 species), C4.5 (7 species), NB (4 species) and RIPPER (3 species) methods As a final outcome of this study, we converted signatures into QR codes and developed a software matK -QR Classifier (http://www.neeri.res.in/matk_classifier/index.htm), which search signatures in the query matK gene sequences and predict corresponding plant species. This novel approach of employing pattern-based signatures opens new avenues for the classification of species. In addition to existing methods, we believe that matK -QR Classifier would be a valuable tool for molecular taxonomists enabling precise identification of plant species.

CRC-113 gene expression signature for predicting prognosis in patients with colorectal cancer

PubMed Central

Nguyen, Dinh Truong; Kim, Jin-Hwan; Jo, Yong Hwa; Shahid, Muhammad; Akter, Salima; Aryal, Saurav Nath; Yoo, Ji Youn; Ahn, Yong-Joo; Cho, Kyoung Min; Lee, Ju-Seog; Choe, Wonchae; Kang, Insug; Ha, Joohun; Kim, Sung Soo

2015-01-01

Colorectal cancer (CRC) is the third leading cause of global cancer mortality. Recent studies have proposed several gene signatures to predict CRC prognosis, but none of those have proven reliable for predicting prognosis in clinical practice yet due to poor reproducibility and molecular heterogeneity. Here, we have established a prognostic signature of 113 probe sets (CRC-113) that include potential biomarkers and reflect the biological and clinical characteristics. Robustness and accuracy were significantly validated in external data sets from 19 centers in five countries. In multivariate analysis, CRC-113 gene signature showed a stronger prognostic value for survival and disease recurrence in CRC patients than current clinicopathological risk factors and molecular alterations. We also demonstrated that the CRC-113 gene signature reflected both genetic and epigenetic molecular heterogeneity in CRC patients. Furthermore, incorporation of the CRC-113 gene signature into a clinical context and molecular markers further refined the selection of the CRC patients who might benefit from postoperative chemotherapy. Conclusively, CRC-113 gene signature provides new possibilities for improving prognostic models and personalized therapeutic strategies. PMID:26397224

CRC-113 gene expression signature for predicting prognosis in patients with colorectal cancer.

PubMed

Nguyen, Minh Nam; Choi, Tae Gyu; Nguyen, Dinh Truong; Kim, Jin-Hwan; Jo, Yong Hwa; Shahid, Muhammad; Akter, Salima; Aryal, Saurav Nath; Yoo, Ji Youn; Ahn, Yong-Joo; Cho, Kyoung Min; Lee, Ju-Seog; Choe, Wonchae; Kang, Insug; Ha, Joohun; Kim, Sung Soo

2015-10-13

Colorectal cancer (CRC) is the third leading cause of global cancer mortality. Recent studies have proposed several gene signatures to predict CRC prognosis, but none of those have proven reliable for predicting prognosis in clinical practice yet due to poor reproducibility and molecular heterogeneity. Here, we have established a prognostic signature of 113 probe sets (CRC-113) that include potential biomarkers and reflect the biological and clinical characteristics. Robustness and accuracy were significantly validated in external data sets from 19 centers in five countries. In multivariate analysis, CRC-113 gene signature showed a stronger prognostic value for survival and disease recurrence in CRC patients than current clinicopathological risk factors and molecular alterations. We also demonstrated that the CRC-113 gene signature reflected both genetic and epigenetic molecular heterogeneity in CRC patients. Furthermore, incorporation of the CRC-113 gene signature into a clinical context and molecular markers further refined the selection of the CRC patients who might benefit from postoperative chemotherapy. Conclusively, CRC-113 gene signature provides new possibilities for improving prognostic models and personalized therapeutic strategies.

On the Eigenstrain Application of Shot-Peened Residual Stresses Within a Crystal Plasticity Framework: Application to Ni-Base Superalloy Specimens (Postprint)

DTIC Science & Technology

2016-01-06

Signature// //Signature// //Signature// REPORT DOCUMENTATION PAGE Form Approved OMB No. 0704-0188 The public reporting burden for this collection...information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1. REPORT DATE (DD...D. Musinski 19b. TELEPHONE NUMBER (Include Area Code) (937) 255-0485 Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std. Z39-18 REPORT

L1000CDS2: LINCS L1000 characteristic direction signatures search engine.

PubMed

Duan, Qiaonan; Reid, St Patrick; Clark, Neil R; Wang, Zichen; Fernandez, Nicolas F; Rouillard, Andrew D; Readhead, Ben; Tritsch, Sarah R; Hodos, Rachel; Hafner, Marc; Niepel, Mario; Sorger, Peter K; Dudley, Joel T; Bavari, Sina; Panchal, Rekha G; Ma'ayan, Avi

2016-01-01

The library of integrated network-based cellular signatures (LINCS) L1000 data set currently comprises of over a million gene expression profiles of chemically perturbed human cell lines. Through unique several intrinsic and extrinsic benchmarking schemes, we demonstrate that processing the L1000 data with the characteristic direction (CD) method significantly improves signal to noise compared with the MODZ method currently used to compute L1000 signatures. The CD processed L1000 signatures are served through a state-of-the-art web-based search engine application called L1000CDS 2 . The L1000CDS 2 search engine provides prioritization of thousands of small-molecule signatures, and their pairwise combinations, predicted to either mimic or reverse an input gene expression signature using two methods. The L1000CDS 2 search engine also predicts drug targets for all the small molecules profiled by the L1000 assay that we processed. Targets are predicted by computing the cosine similarity between the L1000 small-molecule signatures and a large collection of signatures extracted from the gene expression omnibus (GEO) for single-gene perturbations in mammalian cells. We applied L1000CDS 2 to prioritize small molecules that are predicted to reverse expression in 670 disease signatures also extracted from GEO, and prioritized small molecules that can mimic expression of 22 endogenous ligand signatures profiled by the L1000 assay. As a case study, to further demonstrate the utility of L1000CDS 2 , we collected expression signatures from human cells infected with Ebola virus at 30, 60 and 120 min. Querying these signatures with L1000CDS 2 we identified kenpaullone, a GSK3B/CDK2 inhibitor that we show, in subsequent experiments, has a dose-dependent efficacy in inhibiting Ebola infection in vitro without causing cellular toxicity in human cell lines. In summary, the L1000CDS 2 tool can be applied in many biological and biomedical settings, while improving the extraction of knowledge from the LINCS L1000 resource.

DNA Copy Number Signature to Predict Recurrence in Early Stage Ovarian Cancer

DTIC Science & Technology

2016-08-01

AWARD NUMBER: W81XWH-14-1-0194 TITLE: DNA Copy Number Signature to Predict Recurrence in Early-Stage Ovarian Cancer PRINCIPAL INVESTIGATOR...SUBTITLE 5a. CONTRACT NUMBER DNA Copy Number Signature to Predict Recurrence in Early-Stage Ovarian Cancer 5b. GRANT NUMBER W81XWH-14-1-0194 5c. PROGRAM...determine the copy number gain and loss for early stage high grade ovarian cancers through IlluminaHumanOmniExpress-FFPE BeadChip system • Subtask 1 DNA

Enhanced anti-counterfeiting measures for additive manufacturing: coupling lanthanide nanomaterial chemical signatures with blockchain technology

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

Kennedy, Zachary C.; Stephenson, David E.; Christ, Josef F.

The significant rise of additive manufacturing (AM) in recent years is in part due to the open sourced nature of the printing processes and reduced cost and capital barriers relative to traditional manufacturing. However, this democratization of manufacturing spurs an increased demand for producers and end-users to verify the authenticity and quality of individual parts. To this end, we introduce an anti-counterfeiting method composed of first embedding engineered nanomaterials into features of a 3D-printed part followed by non-destructive interrogation of these features to quantify a chemical signature profile. The part specific chemical signature data is then linked to a securitized,more » distributed, and time-stamped blockchain ledger entry. To demonstrate the utility of this approach, lanthanide-aspartic acid nanoscale coordination polymers (Ln3+- Asp NCs) / poly(lactic) acid (PLA) composites were formulated and transformed into a filament feedstock for fused deposition modeling (FDM) 3D printing. In the present case, a quick-response (QR) code containing the doped Ln3+-Asp NCs was printed using a dual-extruder FDM printer into pure PLA parts. The QR code provides a searchable reference to an Ethereum-based blockchain entry. The QR code physical features also serve as defined areas to probe the signatures arising from the embedded Ln3+-Asp NCs. Visible fluorescence emission with UV-excitation was quantified in terms of color using a smartphone camera and incorporated into blockchain entries. Ultimately, linking unique chemical signature data to blockchain databases is anticipated to make the costs of counterfeiting AM materials significantly more prohibitive and transactions between those in the supply chain more trustworthy.« less

ToxCast: Developing Predictive Signatures of Chemically Induced Toxicity (Developing Predictive Bioactivity Signatures from ToxCasts HTS Data)

EPA Science Inventory

ToxCast, the United States Environmental Protection Agency’s chemical prioritization research program, is developing methods for utilizing computational chemistry, bioactivity profiling and toxicogenomic data to predict potential for toxicity and prioritize limited testing resour...

Uncertainty in hydrological signatures for gauged and ungauged catchments

NASA Astrophysics Data System (ADS)

Westerberg, Ida K.; Wagener, Thorsten; Coxon, Gemma; McMillan, Hilary K.; Castellarin, Attilio; Montanari, Alberto; Freer, Jim

2016-03-01

Reliable information about hydrological behavior is needed for water-resource management and scientific investigations. Hydrological signatures quantify catchment behavior as index values, and can be predicted for ungauged catchments using a regionalization procedure. The prediction reliability is affected by data uncertainties for the gauged catchments used in prediction and by uncertainties in the regionalization procedure. We quantified signature uncertainty stemming from discharge data uncertainty for 43 UK catchments and propagated these uncertainties in signature regionalization, while accounting for regionalization uncertainty with a weighted-pooling-group approach. Discharge uncertainty was estimated using Monte Carlo sampling of multiple feasible rating curves. For each sampled rating curve, a discharge time series was calculated and used in deriving the gauged signature uncertainty distribution. We found that the gauged uncertainty varied with signature type, local measurement conditions and catchment behavior, with the highest uncertainties (median relative uncertainty ±30-40% across all catchments) for signatures measuring high- and low-flow magnitude and dynamics. Our regionalization method allowed assessing the role and relative magnitudes of the gauged and regionalized uncertainty sources in shaping the signature uncertainty distributions predicted for catchments treated as ungauged. We found that (1) if the gauged uncertainties were neglected there was a clear risk of overconditioning the regionalization inference, e.g., by attributing catchment differences resulting from gauged uncertainty to differences in catchment behavior, and (2) uncertainty in the regionalization results was lower for signatures measuring flow distribution (e.g., mean flow) than flow dynamics (e.g., autocorrelation), and for average flows (and then high flows) compared to low flows.

A review of propeller discrete frequency noise prediction technology with emphasis on two current methods for time domain calculations

NASA Technical Reports Server (NTRS)

Farassat, F.; Succi, G. P.

1980-01-01

A review of propeller noise prediction technology is presented which highlights the developments in the field from the successful attempt of Gutin to the current sophisticated techniques. Two methods for the predictions of the discrete frequency noise from conventional and advanced propellers in forward flight are described. These methods developed at MIT and NASA Langley Research Center are based on different time domain formulations. Brief description of the computer algorithms based on these formulations are given. The output of these two programs, which is the acoustic pressure signature, is Fourier analyzed to get the acoustic pressure spectrum. The main difference between the programs as they are coded now is that the Langley program can handle propellers with supersonic tip speed while the MIT program is for subsonic tip speed propellers. Comparisons of the calculated and measured acoustic data for a conventional and an advanced propeller show good agreement in general.

A Plastic Temporal Brain Code for Conscious State Generation

PubMed Central

Dresp-Langley, Birgitta; Durup, Jean

2009-01-01

Consciousness is known to be limited in processing capacity and often described in terms of a unique processing stream across a single dimension: time. In this paper, we discuss a purely temporal pattern code, functionally decoupled from spatial signals, for conscious state generation in the brain. Arguments in favour of such a code include Dehaene et al.'s long-distance reverberation postulate, Ramachandran's remapping hypothesis, evidence for a temporal coherence index and coincidence detectors, and Grossberg's Adaptive Resonance Theory. A time-bin resonance model is developed, where temporal signatures of conscious states are generated on the basis of signal reverberation across large distances in highly plastic neural circuits. The temporal signatures are delivered by neural activity patterns which, beyond a certain statistical threshold, activate, maintain, and terminate a conscious brain state like a bar code would activate, maintain, or inactivate the electronic locks of a safe. Such temporal resonance would reflect a higher level of neural processing, independent from sensorial or perceptual brain mechanisms. PMID:19644552

49 CFR 592.6 - Duties of a registered importer.

Code of Federal Regulations, 2010 CFR

2010-10-01

... pursuant to § 592.5(a)(5)(iv), with an original hand-written signature and not with a signature that is... paragraph (d) of this section (the 30-day period will be extended if the Administrator has made written... on which Code J is checked, and the EPA has granted the ICI written permission to operate the vehicle...

Relationship between Effective Application of Machine Learning and Malware Detection: A Quantitative Study

ERIC Educational Resources Information Center

Enfinger, Kerry Wayne

2016-01-01

The number of malicious files present in the public domain continues to rise at a substantial rate. Current anti-malware software utilizes a signature-based method to detect the presence of malicious software. Generating these pattern signatures is time consuming due to malicious code complexity and the need for expert analysis, however, by making…

A Third Approach to Gene Prediction Suggests Thousands of Additional Human Transcribed Regions

PubMed Central

Glusman, Gustavo; Qin, Shizhen; El-Gewely, M. Raafat; Siegel, Andrew F; Roach, Jared C; Hood, Leroy; Smit, Arian F. A

2006-01-01

The identification and characterization of the complete ensemble of genes is a main goal of deciphering the digital information stored in the human genome. Many algorithms for computational gene prediction have been described, ultimately derived from two basic concepts: (1) modeling gene structure and (2) recognizing sequence similarity. Successful hybrid methods combining these two concepts have also been developed. We present a third orthogonal approach to gene prediction, based on detecting the genomic signatures of transcription, accumulated over evolutionary time. We discuss four algorithms based on this third concept: Greens and CHOWDER, which quantify mutational strand biases caused by transcription-coupled DNA repair, and ROAST and PASTA, which are based on strand-specific selection against polyadenylation signals. We combined these algorithms into an integrated method called FEAST, which we used to predict the location and orientation of thousands of putative transcription units not overlapping known genes. Many of the newly predicted transcriptional units do not appear to code for proteins. The new algorithms are particularly apt at detecting genes with long introns and lacking sequence conservation. They therefore complement existing gene prediction methods and will help identify functional transcripts within many apparent “genomic deserts.” PMID:16543943

Transonic blade-vortex interactions - The far field

NASA Astrophysics Data System (ADS)

Lyrintzis, A. S.; George, A. R.

Numerical techniques are developed to predict midfield and far-field helicopter noise due to main-rotor blade-vortex interaction (BVI). The extension of the two-dimensional small-disturbance transonic flow code VTRAN2 (George and Chang, 1983) to the three-dimensional far field (via the Green-function approach of Kirchhoff) is described, and the treatment of oblique BVIs is discussed. Numerical results for a NACA 64A006 airfoil at Mach 0.82 are presented in extensive graphs and characterized in detail. The far-field BVI signature is shown to begin with a strongly forward-directed primary wave (from the original BVI), with an additional downward-directed wave in the case of type C shock motion on the blade.

Building a Predictive Capability for Decision-Making that Supports MultiPEM

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

Carmichael, Joshua Daniel

Multi-phenomenological explosion monitoring (multiPEM) is a developing science that uses multiple geophysical signatures of explosions to better identify and characterize their sources. MultiPEM researchers seek to integrate explosion signatures together to provide stronger detection, parameter estimation, or screening capabilities between different sources or processes. This talk will address forming a predictive capability for screening waveform explosion signatures to support multiPEM.

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.

SETI in vivo: testing the we-are-them hypothesis

NASA Astrophysics Data System (ADS)

Makukov, Maxim A.; Shcherbak, Vladimir I.

2018-04-01

After it was proposed that life on Earth might descend from seeding by an earlier extraterrestrial civilization motivated to secure and spread life, some authors noted that this alternative offers a testable implication: microbial seeds could be intentionally supplied with a durable signature that might be found in extant organisms. In particular, it was suggested that the optimal location for such an artefact is the genetic code, as the least evolving part of cells. However, as the mainstream view goes, this scenario is too speculative and cannot be meaningfully tested because encoding/decoding a signature within the genetic code is something ill-defined, so any retrieval attempt is doomed to guesswork. Here we refresh the seeded-Earth hypothesis in light of recent observations, and discuss the motivation for inserting a signature. We then show that `biological SETI' involves even weaker assumptions than traditional SETI and admits a well-defined methodological framework. After assessing the possibility in terms of molecular and evolutionary biology, we formalize the approach and, adopting the standard guideline of SETI that encoding/decoding should follow from first principles and be convention-free, develop a universal retrieval strategy. Applied to the canonical genetic code, it reveals a non-trivial precision structure of interlocked logical and numerical attributes of systematic character (previously we found these heuristically). To assess this result in view of the initial assumption, we perform statistical, comparison, interdependence and semiotic analyses. Statistical analysis reveals no causal connection of the result to evolutionary models of the genetic code, interdependence analysis precludes overinterpretation, and comparison analysis shows that known variations of the code lack any precision-logic structures, in agreement with these variations being post-LUCA (i.e. post-seeding) evolutionary deviations from the canonical code. Finally, semiotic analysis shows that not only the found attributes are consistent with the initial assumption, but that they make perfect sense from SETI perspective, as they ultimately maintain some of the most universal codes of culture.

Ground signature extrapolation of three-dimensional near-field CFD predictions for several HSCT configurations

NASA Technical Reports Server (NTRS)

Siclari, M. J.

1992-01-01

A CFD analysis of the near-field sonic boom environment of several low boom High Speed Civilian Transport (HSCT) concepts is presented. The CFD method utilizes a multi-block Euler marching code within the context of an innovative mesh topology that allows for the resolution of shock waves several body lengths from the aircraft. Three-dimensional pressure footprints at one body length below three-different low boom aircraft concepts are presented. Models of two concepts designed by NASA to cruise at Mach 2 and Mach 3 were built and tested in the wind tunnel. The third concept was designed by Boeing to cruise at Mach 1.7. Centerline and sideline samples of these footprints are then extrapolated to the ground using a linear waveform parameter method to estimate the ground signatures or sonic boom ground overpressure levels. The Mach 2 concept achieved its centerline design signature but indicated higher sideline booms due to the outboard wing crank of the configuration. Nacelles are also included on two of NASA's low boom concepts. Computations are carried out for both flow-through nacelles and nacelles with engine exhaust simulation. The flow-through nacelles with the assumption of zero spillage and zero inlet lip radius showed very little effect on the sonic boom signatures. On the other hand, it was shown that the engine exhaust plumes can have an effect on the levels of overpressure reaching the ground depending on the engine operating conditions. The results of this study indicate that engine integration into a low boom design should be given some attention.

Development of Neutron Energy Spectral Signatures for Passive Monitoring of Spent Nuclear Fuels in Dry Cask Storage

NASA Astrophysics Data System (ADS)

Harkness, Ira; Zhu, Ting; Liang, Yinong; Rauch, Eric; Enqvist, Andreas; Jordan, Kelly A.

2018-01-01

Demand for spent nuclear fuel dry casks as an interim storage solution has increased globally and the IAEA has expressed a need for robust safeguards and verification technologies for ensuring the continuity of knowledge and the integrity of radioactive materials inside spent fuel casks. Existing research has been focusing on "fingerprinting" casks based on count rate statistics to represent radiation emission signatures. The current research aims to expand to include neutron energy spectral information as part of the fuel characteristics. First, spent fuel composition data are taken from the Next Generation Safeguards Initiative Spent Fuel Libraries, representative for Westinghouse 17ˣ17 PWR assemblies. The ORIGEN-S code then calculates the spontaneous fission and (α,n) emissions for individual fuel rods, followed by detailed MCNP simulations of neutrons transported through the fuel assemblies. A comprehensive database of neutron energy spectral profiles is to be constructed, with different enrichment, burn-up, and cooling time conditions. The end goal is to utilize the computational spent fuel library, predictive algorithm, and a pressurized 4He scintillator to verify the spent fuel assemblies inside a cask. This work identifies neutron spectral signatures that correlate with the cooling time of spent fuel. Both the total and relative contributions from spontaneous fission and (α,n) change noticeably with respect to cooling time, due to the relatively short half-life (18 years) of the major neutron source 244Cm. Identification of this and other neutron spectral signatures allows the characterization of spent nuclear fuels in dry cask storage.

Simulating the universe(s): from cosmic bubble collisions to cosmological observables with numerical relativity

NASA Astrophysics Data System (ADS)

Wainwright, Carroll L.; Johnson, Matthew C.; Peiris, Hiranya V.; Aguirre, Anthony; Lehner, Luis; Liebling, Steven L.

2014-03-01

The theory of eternal inflation in an inflaton potential with multiple vacua predicts that our universe is one of many bubble universes nucleating and growing inside an ever-expanding false vacuum. The collision of our bubble with another could provide an important observational signature to test this scenario. We develop and implement an algorithm for accurately computing the cosmological observables arising from bubble collisions directly from the Lagrangian of a single scalar field. We first simulate the collision spacetime by solving Einstein's equations, starting from nucleation and ending at reheating. Taking advantage of the collision's hyperbolic symmetry, the simulations are performed with a 1+1-dimensional fully relativistic code that uses adaptive mesh refinement. We then calculate the comoving curvature perturbation in an open Friedmann-Robertson-Walker universe, which is used to determine the temperature anisotropies of the cosmic microwave background radiation. For a fiducial Lagrangian, the anisotropies are well described by a power law in the cosine of the angular distance from the center of the collision signature. For a given form of the Lagrangian, the resulting observational predictions are inherently statistical due to stochastic elements of the bubble nucleation process. Further uncertainties arise due to our imperfect knowledge about inflationary and pre-recombination physics. We characterize observational predictions by computing the probability distributions over four phenomenological parameters which capture these intrinsic and model uncertainties. This represents the first fully-relativistic set of predictions from an ensemble of scalar field models giving rise to eternal inflation, yielding significant differences from previous non-relativistic approximations. Thus, our results provide a basis for a rigorous confrontation of these theories with cosmological data.

Output-Adaptive Tetrahedral Cut-Cell Validation for Sonic Boom Prediction

NASA Technical Reports Server (NTRS)

Park, Michael A.; Darmofal, David L.

2008-01-01

A cut-cell approach to Computational Fluid Dynamics (CFD) that utilizes the median dual of a tetrahedral background grid is described. The discrete adjoint is also calculated, which permits adaptation based on improving the calculation of a specified output (off-body pressure signature) in supersonic inviscid flow. These predicted signatures are compared to wind tunnel measurements on and off the configuration centerline 10 body lengths below the model to validate the method for sonic boom prediction. Accurate mid-field sonic boom pressure signatures are calculated with the Euler equations without the use of hybrid grid or signature propagation methods. Highly-refined, shock-aligned anisotropic grids were produced by this method from coarse isotropic grids created without prior knowledge of shock locations. A heuristic reconstruction limiter provided stable flow and adjoint solution schemes while producing similar signatures to Barth-Jespersen and Venkatakrishnan limiters. The use of cut-cells with an output-based adaptive scheme completely automated this accurate prediction capability after a triangular mesh is generated for the cut surface. This automation drastically reduces the manual intervention required by existing methods.

New Bounds on the Total-Squared-Correlation of Quaternary Signature Sets and Optimal Designs

DTIC Science & Technology

2010-03-01

2004. [8] G. S. Rajappan and M. L. Honig, “Signature sequence adaptation for DS - CDMA with multipath,” IEEE Journal on Selected Areas in Commun., vol...vol. 51, pp. 1900-1907, May 2005. [10] G. N. Karystinos and D. A. Pados, “New bounds on the total squared correlation and optimum design of DS - CDMA ...Pados bounds on DS - CDMA binary signature sets,” Des., Codes Cryp- togr., vol. 30, pp. 73-84, Aug. 2003. [12] V. P. Ipatov, “On the Karystinos-Pados bounds

Insertion, Detection, and Extraction of Messages Hidden by Optimal Multi-Signature Spread Spectrum Means

DTIC Science & Technology

2015-07-09

49, pp. 873-885, Apr. 2003. [23] G. N. Karystinos and D. A. Pados, “New bounds on the total squared correlation and optimum design of DS - CDMA binary...bounds on DS - CDMA binary signature sets,” Designs, Codes and Cryptography, vol. 30, pp. 73-84, Aug. 2003. [25] V. P. Ipatov, “On the Karystinos-Pados...bounds and optimal binary DS - CDMA signature ensembles,” IEEE Commun. Letters, vol. 8, pp. 81-83, Feb. 2004. [26] G. N. Karystinos and D. A. Pados

Transcriptional dissection of melanoma identifies a high-risk subtype underlying TP53 family genes and epigenome deregulation

PubMed Central

Badal, Brateil; Solovyov, Alexander; Di Cecilia, Serena; Chan, Joseph Minhow; Chang, Li-Wei; Iqbal, Ramiz; Aydin, Iraz T.; Rajan, Geena S.; Chen, Chen; Abbate, Franco; Arora, Kshitij S.; Tanne, Antoine; Gruber, Stephen B.; Johnson, Timothy M.; Fullen, Douglas R.; Phelps, Robert; Bhardwaj, Nina; Bernstein, Emily; Ting, David T.; Brunner, Georg; Schadt, Eric E.; Greenbaum, Benjamin D.; Celebi, Julide Tok

2017-01-01

BACKGROUND. Melanoma is a heterogeneous malignancy. We set out to identify the molecular underpinnings of high-risk melanomas, those that are likely to progress rapidly, metastasize, and result in poor outcomes. METHODS. We examined transcriptome changes from benign states to early-, intermediate-, and late-stage tumors using a set of 78 treatment-naive melanocytic tumors consisting of primary melanomas of the skin and benign melanocytic lesions. We utilized a next-generation sequencing platform that enabled a comprehensive analysis of protein-coding and -noncoding RNA transcripts. RESULTS. Gene expression changes unequivocally discriminated between benign and malignant states, and a dual epigenetic and immune signature emerged defining this transition. To our knowledge, we discovered previously unrecognized melanoma subtypes. A high-risk primary melanoma subset was distinguished by a 122-epigenetic gene signature (“epigenetic” cluster) and TP53 family gene deregulation (TP53, TP63, and TP73). This subtype associated with poor overall survival and showed enrichment of cell cycle genes. Noncoding repetitive element transcripts (LINEs, SINEs, and ERVs) that can result in immunostimulatory signals recapitulating a state of “viral mimicry” were significantly repressed. The high-risk subtype and its poor predictive characteristics were validated in several independent cohorts. Additionally, primary melanomas distinguished by specific immune signatures (“immune” clusters) were identified. CONCLUSION. The TP53 family of genes and genes regulating the epigenetic machinery demonstrate strong prognostic and biological relevance during progression of early disease. Gene expression profiling of protein-coding and -noncoding RNA transcripts may be a better predictor for disease course in melanoma. This study outlines the transcriptional interplay of the cancer cell’s epigenome with the immune milieu with potential for future therapeutic targeting. FUNDING. National Institutes of Health (CA154683, CA158557, CA177940, CA087497-13), Tisch Cancer Institute, Melanoma Research Foundation, the Dow Family Charitable Foundation, and the Icahn School of Medicine at Mount Sinai. PMID:28469092

L1000CDS2: LINCS L1000 characteristic direction signatures search engine

PubMed Central

Duan, Qiaonan; Reid, St Patrick; Clark, Neil R; Wang, Zichen; Fernandez, Nicolas F; Rouillard, Andrew D; Readhead, Ben; Tritsch, Sarah R; Hodos, Rachel; Hafner, Marc; Niepel, Mario; Sorger, Peter K; Dudley, Joel T; Bavari, Sina; Panchal, Rekha G; Ma’ayan, Avi

2016-01-01

The library of integrated network-based cellular signatures (LINCS) L1000 data set currently comprises of over a million gene expression profiles of chemically perturbed human cell lines. Through unique several intrinsic and extrinsic benchmarking schemes, we demonstrate that processing the L1000 data with the characteristic direction (CD) method significantly improves signal to noise compared with the MODZ method currently used to compute L1000 signatures. The CD processed L1000 signatures are served through a state-of-the-art web-based search engine application called L1000CDS2. The L1000CDS2 search engine provides prioritization of thousands of small-molecule signatures, and their pairwise combinations, predicted to either mimic or reverse an input gene expression signature using two methods. The L1000CDS2 search engine also predicts drug targets for all the small molecules profiled by the L1000 assay that we processed. Targets are predicted by computing the cosine similarity between the L1000 small-molecule signatures and a large collection of signatures extracted from the gene expression omnibus (GEO) for single-gene perturbations in mammalian cells. We applied L1000CDS2 to prioritize small molecules that are predicted to reverse expression in 670 disease signatures also extracted from GEO, and prioritized small molecules that can mimic expression of 22 endogenous ligand signatures profiled by the L1000 assay. As a case study, to further demonstrate the utility of L1000CDS2, we collected expression signatures from human cells infected with Ebola virus at 30, 60 and 120 min. Querying these signatures with L1000CDS2 we identified kenpaullone, a GSK3B/CDK2 inhibitor that we show, in subsequent experiments, has a dose-dependent efficacy in inhibiting Ebola infection in vitro without causing cellular toxicity in human cell lines. In summary, the L1000CDS2 tool can be applied in many biological and biomedical settings, while improving the extraction of knowledge from the LINCS L1000 resource. PMID:28413689

Design of Distortion-Invariant Optical ID Tags for Remote Identification and Verification of Objects

NASA Astrophysics Data System (ADS)

Pérez-Cabré, Elisabet; Millán, María Sagrario; Javidi, Bahram

Optical identification (ID) tags [1] have a promising future in a number of applications such as the surveillance of vehicles in transportation, control of restricted areas for homeland security, item tracking on conveyor belts or other industrial environment, etc. More specifically, passive optical ID tag [1] was introduced as an optical code containing a signature (that is, a characteristic image or other relevant information of the object), which permits its real-time remote detection and identification. Since their introduction in the literature [1], some contributions have been proposed to increase their usefulness and robustness. To increase security and avoid counterfeiting, the signature was introduced in the optical code as an encrypted function [2-5] following the double-phase encryption technique [6]. Moreover, the design of the optical ID tag was done in such a way that tolerance to variations in scale and rotation was achieved [2-5]. To do that, the encrypted information was multiplexed and distributed in the optical code following an appropriate topology. Further studies were carried out to analyze the influence of different sources of noise. In some proposals [5, 7], the designed ID tag consists of two optical codes where the complex-valued encrypted signature was separately introduced in two real-valued functions according to its magnitude and phase distributions. This solution was introduced to overcome some difficulties in the readout of complex values in outdoors environments. Recently, the fully phase encryption technique [8] has been proposed to increase noise robustness of the authentication system.

Individualized prediction of perineural invasion in colorectal cancer: development and validation of a radiomics prediction model.

PubMed

Huang, Yanqi; He, Lan; Dong, Di; Yang, Caiyun; Liang, Cuishan; Chen, Xin; Ma, Zelan; Huang, Xiaomei; Yao, Su; Liang, Changhong; Tian, Jie; Liu, Zaiyi

2018-02-01

To develop and validate a radiomics prediction model for individualized prediction of perineural invasion (PNI) in colorectal cancer (CRC). After computed tomography (CT) radiomics features extraction, a radiomics signature was constructed in derivation cohort (346 CRC patients). A prediction model was developed to integrate the radiomics signature and clinical candidate predictors [age, sex, tumor location, and carcinoembryonic antigen (CEA) level]. Apparent prediction performance was assessed. After internal validation, independent temporal validation (separate from the cohort used to build the model) was then conducted in 217 CRC patients. The final model was converted to an easy-to-use nomogram. The developed radiomics nomogram that integrated the radiomics signature and CEA level showed good calibration and discrimination performance [Harrell's concordance index (c-index): 0.817; 95% confidence interval (95% CI): 0.811-0.823]. Application of the nomogram in validation cohort gave a comparable calibration and discrimination (c-index: 0.803; 95% CI: 0.794-0.812). Integrating the radiomics signature and CEA level into a radiomics prediction model enables easy and effective risk assessment of PNI in CRC. This stratification of patients according to their PNI status may provide a basis for individualized auxiliary treatment.

A novel RNA-sequencing-based miRNA signature predicts with recurrence and outcome of hepatocellular carcinoma.

PubMed

Fumao, Bai; Zhou, Huaibin; Ma, Mengni; Guan, Chen; Lyu, Jianxin; Meng, Qing H

2018-05-02

Hepatocellular carcinoma (HCC) is the fifth most common type of cancer and the second leading cause of cancer-related deaths worldwide. Given that the rate of HCC recurrence 5 years after liver resection is as high as 70%, patient with HCC typically have a poor outcome. A biomarker or set of biomarkers that could predict disease recurrence would have a substantial clinical impact, allowing earlier detection of recurrence and more effective treatment. With the aim of identifying a new microRNA (miRNA) signature associated with HCC recurrence, we analyzed data on 306 HCC patients for whom both miRNA expression profiles and complete clinical information were available from The Cancer Genome Atlas (TCGA) database. Through this analysis, we identified a six-miRNA signature that could effectively predict patients' recurrence risk; the high-risk and low-risk groups had significantly different recurrence-free survival rates. Time-dependent receiver operating characteristic analysis indicated that this signature had a good predictive performance. Multivariable Cox regression and stratified analyses demonstrated that the six-miRNA signature was independent of other clinical features. Functional enrichment analysis of the gene targets of the six prognostic miRNAs indicated enrichment mainly in cancer-related pathways and important cell biological processes. Our results support use of this six-miRNA signature as an independent factor for predicting recurrence and outcome of patients with HCC. Molecular Oncology (2018) © 2018 The Authors. Published by FEBS Press and John Wiley & Sons Ltd.

Integrating Radiosensitivity and Immune Gene Signatures for Predicting Benefit of Radiotherapy in Breast Cancer.

PubMed

Cui, Yi; Li, Bailiang; Pollom, Erqi Liu; Horst, Kathleen; Li, Ruijiang

2018-06-19

Breast cancer is a heterogeneous disease and not all patients respond equally to adjuvant radiotherapy. Predictive biomarkers are needed to select patients who will benefit from the treatment and spare others the toxicity and burden of radiation. We first trained and tested an intrinsic radiosensitivity gene signature to predict local recurrence after radiotherapy in three cohorts of 948 patients. Next, we developed an antigen processing and presentation-based immune signature by maximizing the treatment interaction effect in 129 patients. To test their predictive value, we matched patients treated with or without radiotherapy in an independent validation cohort for clinicopathologic factors including age, ER status, HER2 status, stage, hormone-therapy, chemotherapy, and surgery. Disease specific survival (DSS) was the primary endpoint. Our validation cohort consisted of 1,439 patients. After matching and stratification by the radiosensitivity signature, patients who received radiotherapy had better DSS than patients who did not in the radiation-sensitive group (hazard ratio [HR]=0.68, P=0.059, n=322), while a reverse trend was observed in the radiation-resistant group (HR=1.53, P=0.059, n=202). Similarly, patients treated with radiotherapy had significantly better DSS in the immuneeffective group (HR=0.46, P=0.0076, n=180), with no difference in DSS in the immunedefective group (HR=1.27, P=0.16, n=348). Both signatures were predictive of radiotherapy benefit (P interaction =0.007 and 0.005). Integration of radiosensitivity and immune signatures further stratified patients into three groups with differential outcomes for those treated with or without radiotherapy (P interaction =0.003). The proposed signatures have the potential to select patients who are most likely to benefit from radiotherapy. Copyright ©2018, American Association for Cancer Research.

A Semi-Supervised Approach for Refining Transcriptional Signatures of Drug Response and Repositioning Predictions

PubMed Central

Iorio, Francesco; Shrestha, Roshan L.; Levin, Nicolas; Boilot, Viviane; Garnett, Mathew J.; Saez-Rodriguez, Julio; Draviam, Viji M.

2015-01-01

We present a novel strategy to identify drug-repositioning opportunities. The starting point of our method is the generation of a signature summarising the consensual transcriptional response of multiple human cell lines to a compound of interest (namely the seed compound). This signature can be derived from data in existing databases, such as the connectivity-map, and it is used at first instance to query a network interlinking all the connectivity-map compounds, based on the similarity of their transcriptional responses. This provides a drug neighbourhood, composed of compounds predicted to share some effects with the seed one. The original signature is then refined by systematically reducing its overlap with the transcriptional responses induced by drugs in this neighbourhood that are known to share a secondary effect with the seed compound. Finally, the drug network is queried again with the resulting refined signatures and the whole process is carried on for a number of iterations. Drugs in the final refined neighbourhood are then predicted to exert the principal mode of action of the seed compound. We illustrate our approach using paclitaxel (a microtubule stabilising agent) as seed compound. Our method predicts that glipizide and splitomicin perturb microtubule function in human cells: a result that could not be obtained through standard signature matching methods. In agreement, we find that glipizide and splitomicin reduce interphase microtubule growth rates and transiently increase the percentage of mitotic cells–consistent with our prediction. Finally, we validated the refined signatures of paclitaxel response by mining a large drug screening dataset, showing that human cancer cell lines whose basal transcriptional profile is anti-correlated to them are significantly more sensitive to paclitaxel and docetaxel. PMID:26452147

Landscape of somatic mutations in 560 breast cancer whole-genome sequences

DOE PAGES

Nik-Zainal, Serena; Davies, Helen; Staaf, Johan; ...

2016-05-02

Here, we analysed whole-genome sequences of 560 breast cancers to advance understanding of the driver mutations conferring clonal advantage and the mutational processes generating somatic mutations. We found that 93 protein-coding cancer genes carried probable driver mutations. Some non-coding regions exhibited high mutation frequencies, but most have distinctive structural features probably causing elevated mutation rates and do not contain driver mutations. Mutational signature analysis was extended to genome rearrangements and revealed twelve base substitution and six rearrangement signatures. Three rearrangement signatures, characterized by tandem duplications or deletions, appear associated with defective homologous-recombination-based DNA repair: one with deficient BRCA1 function, anothermore » with deficient BRCA1 or BRCA2 function, the cause of the third is unknown. This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operating, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer.« less

Landscape of somatic mutations in 560 breast cancer whole-genome sequences

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

Nik-Zainal, Serena; Davies, Helen; Staaf, Johan

Here, we analysed whole-genome sequences of 560 breast cancers to advance understanding of the driver mutations conferring clonal advantage and the mutational processes generating somatic mutations. We found that 93 protein-coding cancer genes carried probable driver mutations. Some non-coding regions exhibited high mutation frequencies, but most have distinctive structural features probably causing elevated mutation rates and do not contain driver mutations. Mutational signature analysis was extended to genome rearrangements and revealed twelve base substitution and six rearrangement signatures. Three rearrangement signatures, characterized by tandem duplications or deletions, appear associated with defective homologous-recombination-based DNA repair: one with deficient BRCA1 function, anothermore » with deficient BRCA1 or BRCA2 function, the cause of the third is unknown. This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operating, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer.« less

Landscape of somatic mutations in 560 breast cancer whole genome sequences

PubMed Central

Nik-Zainal, Serena; Davies, Helen; Staaf, Johan; Ramakrishna, Manasa; Glodzik, Dominik; Zou, Xueqing; Martincorena, Inigo; Alexandrov, Ludmil B.; Martin, Sancha; Wedge, David C.; Van Loo, Peter; Ju, Young Seok; Smid, Marcel; Brinkman, Arie B; Morganella, Sandro; Aure, Miriam R.; Lingjærde, Ole Christian; Langerød, Anita; Ringnér, Markus; Ahn, Sung-Min; Boyault, Sandrine; Brock, Jane E.; Broeks, Annegien; Butler, Adam; Desmedt, Christine; Dirix, Luc; Dronov, Serge; Fatima, Aquila; Foekens, John A.; Gerstung, Moritz; Hooijer, Gerrit KJ; Jang, Se Jin; Jones, David R.; Kim, Hyung-Yong; King, Tari A.; Krishnamurthy, Savitri; Lee, Hee Jin; Lee, Jeong-Yeon; Li, Yilong; McLaren, Stuart; Menzies, Andrew; Mustonen, Ville; O’Meara, Sarah; Pauporté, Iris; Pivot, Xavier; Purdie, Colin A.; Raine, Keiran; Ramakrishnan, Kamna; Rodríguez-González, F. Germán; Romieu, Gilles; Sieuwerts, Anieta M.; Simpson, Peter T; Shepherd, Rebecca; Stebbings, Lucy; Stefansson, Olafur A; Teague, Jon; Tommasi, Stefania; Treilleux, Isabelle; Van den Eynden, Gert G.; Vermeulen, Peter; Vincent-Salomon, Anne; Yates, Lucy; Caldas, Carlos; van’t Veer, Laura; Tutt, Andrew; Knappskog, Stian; Tan, Benita Kiat Tee; Jonkers, Jos; Borg, Åke; Ueno, Naoto T; Sotiriou, Christos; Viari, Alain; Futreal, P. Andrew; Campbell, Peter J; Span, Paul N.; Van Laere, Steven; Lakhani, Sunil R; Eyfjord, Jorunn E.; Thompson, Alastair M.; Birney, Ewan; Stunnenberg, Hendrik G; van de Vijver, Marc J; Martens, John W.M.; Børresen-Dale, Anne-Lise; Richardson, Andrea L.; Kong, Gu; Thomas, Gilles; Stratton, Michael R.

2016-01-01

We analysed whole genome sequences of 560 breast cancers to advance understanding of the driver mutations conferring clonal advantage and the mutational processes generating somatic mutations. 93 protein-coding cancer genes carried likely driver mutations. Some non-coding regions exhibited high mutation frequencies but most have distinctive structural features probably causing elevated mutation rates and do not harbour driver mutations. Mutational signature analysis was extended to genome rearrangements and revealed 12 base substitution and six rearrangement signatures. Three rearrangement signatures, characterised by tandem duplications or deletions, appear associated with defective homologous recombination based DNA repair: one with deficient BRCA1 function; another with deficient BRCA1 or BRCA2 function; the cause of the third is unknown. This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operative, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer. PMID:27135926

Design and Computational/Experimental Analysis of Low Sonic Boom Configurations

NASA Technical Reports Server (NTRS)

Cliff, Susan E.; Baker, Timothy J.; Hicks, Raymond M.

1999-01-01

Recent studies have shown that inviscid CFD codes combined with a planar extrapolation method give accurate sonic boom pressure signatures at distances greater than one body length from supersonic configurations if either adapted grids swept at the approximate Mach angle or very dense non-adapted grids are used. The validation of CFD for computing sonic boom pressure signatures provided the confidence needed to undertake the design of new supersonic transport configurations with low sonic boom characteristics. An aircraft synthesis code in combination with CFD and an extrapolation method were used to close the design. The principal configuration of this study is designated LBWT (Low Boom Wing Tail) and has a highly swept cranked arrow wing with conventional tails, and was designed to accommodate either 3 or 4 engines. The complete configuration including nacelles and boundary layer diverters was evaluated using the AIRPLANE code. This computer program solves the Euler equations on an unstructured tetrahedral mesh. Computations and wind tunnel data for the LBWT and two other low boom configurations designed at NASA Ames Research Center are presented. The two additional configurations are included to provide a basis for comparing the performance and sonic boom level of the LBWT with contemporary low boom designs and to give a broader experiment/CFD correlation study. The computational pressure signatures for the three configurations are contrasted with on-ground-track near-field experimental data from the NASA Ames 9x7 Foot Supersonic Wind Tunnel. Computed pressure signatures for the LBWT are also compared with experiment at approximately 15 degrees off ground track.

Computational Modeling of Meteor-Generated Ground Pressure Signatures

NASA Technical Reports Server (NTRS)

Nemec, Marian; Aftosmis, Michael J.; Brown, Peter G.

2017-01-01

We present a thorough validation of a computational approach to predict infrasonic signatures of centimeter-sized meteoroids. We assume that the energy deposition along the meteor trail is dominated by atmospheric drag and simulate the steady, inviscid flow of air in thermochemical equilibrium to compute the meteoroid's near-body pressure signature. This signature is then propagated through a stratified and windy atmosphere to the ground using a methodology adapted from aircraft sonic-boom analysis. An assessment of the numerical accuracy of the near field and the far field solver is presented. The results show that when the source of the signature is the cylindrical Mach-cone, the simulations closely match the observations. The prediction of the shock rise-time, the zero-peak amplitude of the waveform, and the duration of the positive pressure phase are consistently within 10% of the measurements. Uncertainty in the shape of the meteoroid results in a poorer prediction of the trailing part of the waveform. Overall, our results independently verify energy deposition estimates deduced from optical observations.

Beyond the scope of Free-Wilson analysis: building interpretable QSAR models with machine learning algorithms.

PubMed

Chen, Hongming; Carlsson, Lars; Eriksson, Mats; Varkonyi, Peter; Norinder, Ulf; Nilsson, Ingemar

2013-06-24

A novel methodology was developed to build Free-Wilson like local QSAR models by combining R-group signatures and the SVM algorithm. Unlike Free-Wilson analysis this method is able to make predictions for compounds with R-groups not present in a training set. Eleven public data sets were chosen as test cases for comparing the performance of our new method with several other traditional modeling strategies, including Free-Wilson analysis. Our results show that the R-group signature SVM models achieve better prediction accuracy compared with Free-Wilson analysis in general. Moreover, the predictions of R-group signature models are also comparable to the models using ECFP6 fingerprints and signatures for the whole compound. Most importantly, R-group contributions to the SVM model can be obtained by calculating the gradient for R-group signatures. For most of the studied data sets, a significant correlation with that of a corresponding Free-Wilson analysis is shown. These results suggest that the R-group contribution can be used to interpret bioactivity data and highlight that the R-group signature based SVM modeling method is as interpretable as Free-Wilson analysis. Hence the signature SVM model can be a useful modeling tool for any drug discovery project.

Building predictive gene signatures through simultaneous assessment of transcription factor activation and gene expression.

EPA Science Inventory

Building predictive gene signatures through simultaneous assessment of transcription factor activation and gene expression Exposure to many drugs and environmentally-relevant chemicals can cause adverse outcomes. These adverse outcomes, such as cancer, have been linked to mol...

Identifying developmental vascular disruptor compounds using a predictive signature and alternative toxicity models

EPA Science Inventory

Identifying Developmental Vascular Disruptor Compounds Using a Predictive Signature and Alternative Toxicity Models Presenting Author: Tamara Tal Affiliation: U.S. EPA/ORD/ISTD, RTP, NC, USA Chemically induced vascular toxicity during embryonic development can result in a wide...

A long non-coding RNA expression profile can predict early recurrence in hepatocellular carcinoma after curative resection.

PubMed

Lv, Yufeng; Wei, Wenhao; Huang, Zhong; Chen, Zhichao; Fang, Yuan; Pan, Lili; Han, Xueqiong; Xu, Zihai

2018-06-20

The aim of this study was to develop a novel long non-coding RNA (lncRNA) expression signature to accurately predict early recurrence for patients with hepatocellular carcinoma (HCC) after curative resection. Using expression profiles downloaded from The Cancer Genome Atlas database, we identified multiple lncRNAs with differential expression between early recurrence (ER) group and non-early recurrence (non-ER) group of HCC. Least absolute shrinkage and selection operator (LASSO) for logistic regression models were used to develop a lncRNA-based classifier for predicting ER in the training set. An independent test set was used to validated the predictive value of this classifier. Futhermore, a co-expression network based on these lncRNAs and its highly related genes was constructed and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of genes in the network were performed. We identified 10 differentially expressed lncRNAs, including 3 that were upregulated and 7 that were downregulated in ER group. The lncRNA-based classifier was constructed based on 7 lncRNAs (AL035661.1, PART1, AC011632.1, AC109588.1, AL365361.1, LINC00861 and LINC02084), and its accuracy was 0.83 in training set, 0.87 in test set and 0.84 in total set. And ROC curve analysis showed the AUROC was 0.741 in training set, 0.824 in the test set and 0.765 in total set. A functional enrichment analysis suggested that the genes of which is highly related to 4 lncRNAs were involved in immune system. This 7-lncRNA expression profile can effectively predict the early recurrence after surgical resection for HCC. This article is protected by copyright. All rights reserved.

Prediction of sonic boom from experimental near-field overpressure data. Volume 1: Method and results

NASA Technical Reports Server (NTRS)

Glatt, C. R.; Hague, D. S.; Reiners, S. J.

1975-01-01

A computerized procedure for predicting sonic boom from experimental near-field overpressure data has been developed. The procedure extrapolates near-field pressure signatures for a specified flight condition to the ground by the Thomas method. Near-field pressure signatures are interpolated from a data base of experimental pressure signatures. The program is an independently operated ODIN (Optimal Design Integration) program which obtains flight path information from other ODIN programs or from input.

Cognitive Code-Division Channelization

DTIC Science & Technology

2011-04-01

22] G. N. Karystinos and D. A. Pados, “New bounds on the total squared correlation and optimum design of DS - CDMA binary signature sets,” IEEE Trans...Commun., vol. 51, pp. 48-51, Jan. 2003. [23] C. Ding, M. Golin, and T. Klve, “Meeting the Welch and Karystinos- Pados bounds on DS - CDMA binary...receiver pair coexisting with a primary code-division multiple-access ( CDMA ) system. Our objective is to find the optimum transmitting power and code

Mal-Xtract: Hidden Code Extraction using Memory Analysis

NASA Astrophysics Data System (ADS)

Lim, Charles; Syailendra Kotualubun, Yohanes; Suryadi; Ramli, Kalamullah

2017-01-01

Software packer has been used effectively to hide the original code inside a binary executable, making it more difficult for existing signature based anti malware software to detect malicious code inside the executable. A new method of written and rewritten memory section is introduced to to detect the exact end time of unpacking routine and extract original code from packed binary executable using Memory Analysis running in an software emulated environment. Our experiment results show that at least 97% of the original code from the various binary executable packed with different software packers could be extracted. The proposed method has also been successfully extracted hidden code from recent malware family samples.

An Approach for Assessing the Signature Quality of Various Chemical Assays when Predicting the Culture Media Used to Grow Microorganisms

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

Holmes, Aimee E.; Sego, Landon H.; Webb-Robertson, Bobbie-Jo M.

We demonstrate an approach for assessing the quality of a signature system designed to predict the culture medium used to grow a microorganism. The system was comprised of four chemical assays designed to identify various ingredients that could be used to produce the culture medium. The analytical measurements resulting from any combination of these four assays can be used in a Bayesian network to predict the probabilities that the microorganism was grown using one of eleven culture media. We evaluated combinations of the signature system by removing one or more of the assays from the Bayes network. We measured andmore » compared the quality of the various Bayes nets in terms of fidelity, cost, risk, and utility, a method we refer to as Signature Quality Metrics« less

Simulation of reflectometry Bragg backscattering spectral responses in the absence of a cutoff layer.

PubMed

da Silva, F; da Graça, S; Heuraux, S; Conway, G D

2010-10-01

Experimental reflectometry signals obtained in the absence of a cutoff layer, with the possibility of interferometric operation excluded, show a coherent and recurrent frequency spectrum signature similar to an Alfvén cascade signature. A possible explanation resides in the modulation of a resonant Bragg backscattering response by an Alfvén mode structure located at the center of the plasma whose frequency of oscillation modulates the backscattered signal in a conformable way. This situation is modeled and simulated using an O-mode full-wave Maxwell finite-difference time-domain code and the resulting signatures are discussed.

An Integrated Fuselage-Sting Balance for a Sonic-Boom Wind-Tunnel Model

NASA Technical Reports Server (NTRS)

Mack, Robert J.

2004-01-01

Measured and predicted pressure signatures from a lifting wind-tunnel model can be compared when the lift on the model is accurately known. The model's lift can be set by bending the support sting to a desired angle of attack. This method is simple in practice, but difficult to accurately apply. A second method is to build a normal force/pitching moment balance into the aft end of the sting, and use an angle-of-attack mechanism to set model attitude. In this report, a method for designing a sting/balance into the aft fuselage/sting of a sonic-boom model is described. A computer code is given, and a sample sting design is outlined to demonstrate the method.

Decoding the usefulness of non-coding RNAs as breast cancer markers.

PubMed

Amorim, Maria; Salta, Sofia; Henrique, Rui; Jerónimo, Carmen

2016-09-15

Although important advances in the management of breast cancer (BC) have been recently accomplished, it still constitutes the leading cause of cancer death in women worldwide. BC is a heterogeneous and complex disease, making clinical prediction of outcome a very challenging task. In recent years, gene expression profiling emerged as a tool to assist in clinical decision, enabling the identification of genetic signatures that better predict prognosis and response to therapy. Nevertheless, translation to routine practice has been limited by economical and technical reasons and, thus, novel biomarkers, especially those requiring non-invasive or minimally invasive collection procedures, while retaining high sensitivity and specificity might represent a significant development in this field. An increasing amount of evidence demonstrates that non-coding RNAs (ncRNAs), particularly microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), are aberrantly expressed in several cancers, including BC. miRNAs are of particular interest as new, easily accessible, cost-effective and non-invasive tools for precise management of BC patients because they circulate in bodily fluids (e.g., serum and plasma) in a very stable manner, enabling BC assessment and monitoring through liquid biopsies. This review focus on how ncRNAs have the potential to answer present clinical needs in the personalized management of patients with BC and comprehensively describes the state of the art on the role of ncRNAs in the diagnosis, prognosis and prediction of response to therapy in BC.

Copy number variation signature to predict human ancestry

PubMed Central

2012-01-01

Background Copy number variations (CNVs) are genomic structural variants that are found in healthy populations and have been observed to be associated with disease susceptibility. Existing methods for CNV detection are often performed on a sample-by-sample basis, which is not ideal for large datasets where common CNVs must be estimated by comparing the frequency of CNVs in the individual samples. Here we describe a simple and novel approach to locate genome-wide CNVs common to a specific population, using human ancestry as the phenotype. Results We utilized our previously published Genome Alteration Detection Analysis (GADA) algorithm to identify common ancestry CNVs (caCNVs) and built a caCNV model to predict population structure. We identified a 73 caCNV signature using a training set of 225 healthy individuals from European, Asian, and African ancestry. The signature was validated on an independent test set of 300 individuals with similar ancestral background. The error rate in predicting ancestry in this test set was 2% using the 73 caCNV signature. Among the caCNVs identified, several were previously confirmed experimentally to vary by ancestry. Our signature also contains a caCNV region with a single microRNA (MIR270), which represents the first reported variation of microRNA by ancestry. Conclusions We developed a new methodology to identify common CNVs and demonstrated its performance by building a caCNV signature to predict human ancestry with high accuracy. The utility of our approach could be extended to large case–control studies to identify CNV signatures for other phenotypes such as disease susceptibility and drug response. PMID:23270563

Sea Surface Signature of Tropical Cyclones Using Microwave Remote Sensing

DTIC Science & Technology

2013-01-01

due to the ionosphere and troposphere, which have to be compensated for, and components due to the galactic and cosmic background radiation those...and corrections for sun glint, galactic and cosmic background radiation, and Stokes effects of the ionosphere. The accuracy of a given retrieval...RESPONSIBLE PERSON 19b. TELEPHONE NUMBER (Include area code) Sea surface signature of tropical cyclones using microwave remote sensing Bumjun Kil

In-depth characterization of breast cancer tumor-promoting cell transcriptome by RNA sequencing and microarrays

PubMed Central

Soldà, Giulia; Merlino, Giuseppe; Fina, Emanuela; Brini, Elena; Moles, Anna; Cappelletti, Vera; Daidone, Maria Grazia

2016-01-01

Numerous studies have reported the existence of tumor-promoting cells (TPC) with self-renewal potential and a relevant role in drug resistance. However, pathways and modifications involved in the maintenance of such tumor subpopulations are still only partially understood. Sequencing-based approaches offer the opportunity for a detailed study of TPC including their transcriptome modulation. Using microarrays and RNA sequencing approaches, we compared the transcriptional profiles of parental MCF7 breast cancer cells with MCF7-derived TPC (i.e. MCFS). Data were explored using different bioinformatic approaches, and major findings were experimentally validated. The different analytical pipelines (Lifescope and Cufflinks based) yielded similar although not identical results. RNA sequencing data partially overlapped microarray results and displayed a higher dynamic range, although overall the two approaches concordantly predicted pathway modifications. Several biological functions were altered in TPC, ranging from production of inflammatory cytokines (i.e., IL-8 and MCP-1) to proliferation and response to steroid hormones. More than 300 non-coding RNAs were defined as differentially expressed, and 2,471 potential splicing events were identified. A consensus signature of genes up-regulated in TPC was derived and was found to be significantly associated with insensitivity to fulvestrant in a public breast cancer patient dataset. Overall, we obtained a detailed portrait of the transcriptome of a breast cancer TPC line, highlighted the role of non-coding RNAs and differential splicing, and identified a gene signature with a potential as a context-specific biomarker in patients receiving endocrine treatment. PMID:26556871

Consensus Analysis of Whole Transcriptome Profiles from Two Breast Cancer Patient Cohorts Reveals Long Non-Coding RNAs Associated with Intrinsic Subtype and the Tumour Microenvironment.

PubMed

Bradford, James R; Cox, Angela; Bernard, Philip; Camp, Nicola J

2016-01-01

Long non-coding RNAs (lncRNAs) are emerging as crucial regulators of cellular processes and diseases such as cancer; however, their functions remain poorly characterised. Several studies have demonstrated that lncRNAs are typically disease and tumour subtype specific, particularly in breast cancer where lncRNA expression alone is sufficient to discriminate samples based on hormone status and molecular intrinsic subtype. However, little attempt has been made to assess the reproducibility of lncRNA signatures across more than one dataset. In this work, we derive consensus lncRNA signatures indicative of breast cancer subtype based on two clinical RNA-Seq datasets: the Utah Breast Cancer Study and The Cancer Genome Atlas, through integration of differential expression and hypothesis-free clustering analyses. The most consistent signature is associated with breast cancers of the basal-like subtype, leading us to generate a putative set of six lncRNA basal-like breast cancer markers, at least two of which may have a role in cis-regulation of known poor prognosis markers. Through in silico functional characterization of individual signatures and integration of expression data from pre-clinical cancer models, we discover that discordance between signatures derived from different clinical cohorts can arise from the strong influence of non-cancerous cells in tumour samples. As a consequence, we identify nine lncRNAs putatively associated with breast cancer associated fibroblasts, or the immune response. Overall, our study establishes the confounding effects of tumour purity on lncRNA signature derivation, and generates several novel hypotheses on the role of lncRNAs in basal-like breast cancers and the tumour microenvironment.

Issues and approaches for electronic document approval and transmittal using digital signatures and text authentication: Prototype documentation

NASA Astrophysics Data System (ADS)

Boling, M. E.

1989-09-01

Prototypes were assembled pursuant to recommendations made in report K/DSRD-96, Issues and Approaches for Electronic Document Approval and Transmittal Using Digital Signatures and Text Authentication, and to examine and discover the possibilities for integrating available hardware and software to provide cost effective systems for digital signatures and text authentication. These prototypes show that on a LAN, a multitasking, windowed, mouse/keyboard menu-driven interface can be assembled to provide easy and quick access to bit-mapped images of documents, electronic forms and electronic mail messages with a means to sign, encrypt, deliver, receive or retrieve and authenticate text and signatures. In addition they show that some of this same software may be used in a classified environment using host to terminal transactions to accomplish these same operations. Finally, a prototype was developed demonstrating that binary files may be signed electronically and sent by point to point communication and over ARPANET to remote locations where the authenticity of the code and signature may be verified. Related studies on the subject of electronic signatures and text authentication using public key encryption were done within the Department of Energy. These studies include timing studies of public key encryption software and hardware and testing of experimental user-generated host resident software for public key encryption. This software used commercially available command-line source code. These studies are responsive to an initiative within the Office of the Secretary of Defense (OSD) for the protection of unclassified but sensitive data. It is notable that these related studies are all built around the same commercially available public key encryption products from the private sector and that the software selection was made independently by each study group.

Species-Specific Predictive Signatures of Developmental Toxicity Using the ToxCast Chemical Library

EPA Science Inventory

EPA’s ToxCastTM project is profiling the in vitro bioactivity of chemicals to generate predictive signatures that correlate with observed in vivo toxicity. In vitro profiling methods from ToxCast data consist of over 600 high-throughput screening (HTS) and high-content screening ...

Optical spectral signatures of liquids by means of fiber optic technology for product and quality parameter identification

NASA Astrophysics Data System (ADS)

Mignani, A. G.; Ciaccheri, L.; Mencaglia, A. A.; Diaz-Herrera, N.; Garcia-Allende, P. B.; Ottevaere, H.; Thienpont, H.; Attilio, C.; Cimato, A.; Francalanci, S.; Paccagnini, A.; Pavone, F. S.

2009-01-01

Absorption spectroscopy in the wide 200-1700 nm spectral range is carried out by means of optical fiber instrumentation to achieve a digital mapping of liquids for the prediction of important quality parameters. Extra virgin olive oils from Italy and lubricant oils from turbines with different degrees of degradation were considered as "case studies". The spectral data were processed by means of multivariate analysis so as to obtain a correlation to quality parameters. In practice, the wide range absorption spectra were considered as an optical signature of the liquids from which to extract product quality information. The optical signatures of extra virgin olive oils were used to predict the content of the most important fatty acids. The optical signatures of lubricant oils were used to predict the concentration of the most important parameters for indicating the oil's degree of degradation, such as TAN, JOAP anti-wear index, and water content.

The Long Noncoding RNA Landscape of the Mouse Eye.

PubMed

Chen, Weiwei; Yang, Shuai; Zhou, Zhonglou; Zhao, Xiaoting; Zhong, Jiayun; Reinach, Peter S; Yan, Dongsheng

2017-12-01

Long noncoding RNAs (lncRNAs) are important regulators of diverse biological functions. However, an extensive in-depth analysis of their expression profile and function in mammalian eyes is still lacking. Here we describe comprehensive landscapes of stage-dependent and tissue-specific lncRNA expression in the mouse eye. Affymetrix transcriptome array profiled lncRNA signatures from six different ocular tissue subsets (i.e., cornea, lens, retina, RPE, choroid, and sclera) in newborn and 8-week-old mice. Quantitative RT-PCR analysis validated array findings. Cis analyses and Gene Ontology (GO) annotation of protein-coding genes adjacent to signature lncRNA loci clarified potential lncRNA roles in maintaining tissue identity and regulating eye maturation during the aforementioned phase. In newborn and 8-week-old mice, we identified 47,332 protein-coding and noncoding gene transcripts. LncRNAs comprise 19,313 of these transcripts annotated in public data banks. During this maturation phase of these six different tissue subsets, more than 1000 lncRNAs expression levels underwent ≥2-fold changes. qRT-PCR analysis confirmed part of the gene microarray analysis results. K-means clustering identified 910 lncRNAs in the P0 groups and 686 lncRNAs in the postnatal 8-week-old groups, suggesting distinct tissue-specific lncRNA clusters. GO analysis of protein-coding genes proximal to lncRNA signatures resolved close correlations with their tissue-specific functional maturation between P0 and 8 weeks of age in the 6 tissue subsets. Characterizating maturational changes in lncRNA expression patterns as well as tissue-specific lncRNA signatures in six ocular tissues suggest important contributions made by lncRNA to the control of developmental processes in the mouse eye.

Real-time scene and signature generation for ladar and imaging sensors

NASA Astrophysics Data System (ADS)

Swierkowski, Leszek; Christie, Chad L.; Antanovskii, Leonid; Gouthas, Efthimios

2014-05-01

This paper describes development of two key functionalities within the VIRSuite scene simulation program, broadening its scene generation capabilities and increasing accuracy of thermal signatures. Firstly, a new LADAR scene generation module has been designed. It is capable of simulating range imagery for Geiger mode LADAR, in addition to the already existing functionality for linear mode systems. Furthermore, a new 3D heat diffusion solver has been developed within the VIRSuite signature prediction module. It is capable of calculating the temperature distribution in complex three-dimensional objects for enhanced dynamic prediction of thermal signatures. With these enhancements, VIRSuite is now a robust tool for conducting dynamic simulation for missiles with multi-mode seekers.

Longitudinal changes in young children’s 0–100 to 0–1000 number-line error signatures

PubMed Central

Reeve, Robert A.; Paul, Jacob M.; Butterworth, Brian

2015-01-01

We use a latent difference score (LDS) model to examine changes in young children’s number-line (NL) error signatures (errors marking numbers on a NL) over 18 months. A LDS model (1) overcomes some of the inference limitations of analytic models used in previous research, and in particular (2) provides a more reliable test of hypotheses about the meaning and significance of changes in NL error signatures over time and task. The NL error signatures of 217 6-year-olds’ (on test occasion one) were assessed three times over 18 months, along with their math ability on two occasions. On the first occasion (T1) children completed a 0–100 NL task; on the second (T2) a 0–100 NL and a 0–1000 NL task; on the third (T3) occasion a 0–1000 NL task. On the third and fourth occasions (T3 and T4), children completed mental calculation tasks. Although NL error signatures changed over time, these were predictable from other NL task error signatures, and predicted calculation accuracy at T3, as well as changes in calculation between T3 and T4. Multiple indirect effects (change parameters) showed that associations between initial NL error signatures (0–100 NL) and later mental calculation ability were mediated by error signatures on the 0–1000 NL task. The pattern of findings from the LDS model highlight the value of identifying direct and indirect effects in characterizing changing relationships in cognitive representations over task and time. Substantively, they support the claim that children’s NL error signatures generalize over task and time and thus can be used to predict math ability. PMID:26029152

Molecular Characterization of a Catalase from Hydra vulgaris

PubMed Central

Dash, Bhagirathi; Phillips, Timothy D.

2012-01-01

Catalase, an antioxidant and hydroperoxidase enzyme protects the cellular environment from harmful effects of hydrogen peroxide by facilitating its degradation to oxygen and water. Molecular information on a cnidarian catalase and/or peroxidase is, however, limited. In this work an apparent full length cDNA sequence coding for a catalase (HvCatalase) was isolated from Hydra vulgaris using 3’- and 5’- (RLM) RACE approaches. The 1859 bp HvCatalase cDNA included an open reading frame of 1518 bp encoding a putative protein of 505 amino acids with a predicted molecular mass of 57.44 kDa. The deduced amino acid sequence of HvCatalase contained several highly conserved motifs including the heme-ligand signature sequence RLFSYGDTH and the active site signature FXRERIPERVVHAKGXGA. A comparative analysis showed the presence of conserved catalytic amino acids [His(71), Asn(145), and Tyr(354)] in HvCatalase as well. Homology modeling indicated the presence of the conserved features of mammalian catalase fold. Hydrae exposed to thermal, starvation, metal and oxidative stress responded by regulating its catalase mRNA transcription. These results indicated that the HvCatalase gene is involved in the cellular stress response and (anti)oxidative processes triggered by stressor and contaminant exposure. PMID:22521743

Validation of a remote sensing model to identify Simulium damnosum s.l. breeding sites in Sub-Saharan Africa.

PubMed

Jacob, Benjamin G; Novak, Robert J; Toe, Laurent D; Sanfo, Moussa; Griffith, Daniel A; Lakwo, Thomson L; Habomugisha, Peace; Katabarwa, Moses N; Unnasch, Thomas R

2013-01-01

Recently, most onchocerciasis control programs have begun to focus on elimination. Developing an effective elimination strategy relies upon accurately mapping the extent of endemic foci. In areas of Africa that suffer from a lack of infrastructure and/or political instability, developing such accurate maps has been difficult. Onchocerciasis foci are localized near breeding sites for the black fly vectors of the infection. The goal of this study was to conduct ground validation studies to evaluate the sensitivity and specificity of a remote sensing model developed to predict S. damnosum s.l. breeding sites. Remote sensing images from Togo were analyzed to identify areas containing signature characteristics of S. damnosum s.l. breeding habitat. All 30 sites with the spectral signature were found to contain S. damnosum larvae, while 0/52 other sites judged as likely to contain larvae were found to contain larvae. The model was then used to predict breeding sites in Northern Uganda. This area is hyper-endemic for onchocerciasis, but political instability had precluded mass distribution of ivermectin until 2009. Ground validation revealed that 23/25 sites with the signature contained S. damnosum larvae, while 8/10 sites examined lacking the signature were larvae free. Sites predicted to have larvae contained significantly more larvae than those that lacked the signature. This study suggests that a signature extracted from remote sensing images may be used to predict the location of S. damnosum s.l. breeding sites with a high degree of accuracy. This method should be of assistance in predicting communities at risk for onchocerciasis in areas of Africa where ground-based epidemiological surveys are difficult to implement.

Validation of a Remote Sensing Model to Identify Simulium damnosum s.l. Breeding Sites in Sub-Saharan Africa

PubMed Central

Jacob, Benjamin G.; Novak, Robert J.; Toe, Laurent D.; Sanfo, Moussa; Griffith, Daniel A.; Lakwo, Thomson L.; Habomugisha, Peace; Katabarwa, Moses N.; Unnasch, Thomas R.

2013-01-01

Background Recently, most onchocerciasis control programs have begun to focus on elimination. Developing an effective elimination strategy relies upon accurately mapping the extent of endemic foci. In areas of Africa that suffer from a lack of infrastructure and/or political instability, developing such accurate maps has been difficult. Onchocerciasis foci are localized near breeding sites for the black fly vectors of the infection. The goal of this study was to conduct ground validation studies to evaluate the sensitivity and specificity of a remote sensing model developed to predict S. damnosum s.l. breeding sites. Methodology/Principal Findings Remote sensing images from Togo were analyzed to identify areas containing signature characteristics of S. damnosum s.l. breeding habitat. All 30 sites with the spectral signature were found to contain S. damnosum larvae, while 0/52 other sites judged as likely to contain larvae were found to contain larvae. The model was then used to predict breeding sites in Northern Uganda. This area is hyper-endemic for onchocerciasis, but political instability had precluded mass distribution of ivermectin until 2009. Ground validation revealed that 23/25 sites with the signature contained S. damnosum larvae, while 8/10 sites examined lacking the signature were larvae free. Sites predicted to have larvae contained significantly more larvae than those that lacked the signature. Conclusions/Significance This study suggests that a signature extracted from remote sensing images may be used to predict the location of S. damnosum s.l. breeding sites with a high degree of accuracy. This method should be of assistance in predicting communities at risk for onchocerciasis in areas of Africa where ground-based epidemiological surveys are difficult to implement. PMID:23936571

Generation of Mid-Wave Infrared Signature Using Microradiating Devices for Vehicle Mounted Identification Friend or Foe Applications

DTIC Science & Technology

2009-06-01

M. Harkins Approved for public release; distribution is unlimited THIS PAGE INTENTIONALLY LEFT BLANK i REPORT DOCUMENTATION PAGE Form Approved...12a. DISTRIBUTION / AVAILABILITY STATEMENT Approved for public release; distribution is unlimited 12b. DISTRIBUTION CODE 13. ABSTRACT (maximum 200...The integration of a MWIR signature into VMIFF will add a daytime capability. A new generation of compact MWIR sources is emerging to meet demands

A four-gene signature predicts survival in clear-cell renal-cell carcinoma.

PubMed

Dai, Jun; Lu, Yuchao; Wang, Jinyu; Yang, Lili; Han, Yingyan; Wang, Ying; Yan, Dan; Ruan, Qiurong; Wang, Shaogang

2016-12-13

Clear-cell renal-cell carcinoma (ccRCC) is the most common pathological subtype of renal cell carcinoma (RCC), accounting for about 80% of RCC. In order to find potential prognostic biomarkers in ccRCC, we presented a four-gene signature to evaluate the prognosis of ccRCC. SurvExpress and immunohistochemical (IHC) staining of tissue microarrays were used to analyze the association between the four genes and the prognosis of ccRCC. Data from TCGA dataset revealed a prognostic prompt function of the four genes (PTEN, PIK3C2A, ITPA and BCL3). Further discovery suggested that the four-gene signature predicted survival better than any of the four genes alone. Moreover, IHC staining demonstrated a consistent result with TCGA, indicating that the signature was an independent prognostic factor of survival in ccRCC. Univariate and multivariate Cox proportional hazard regression analysis were conducted to verify the association of clinicopathological variables and the four genes' expression levels with survival. The results further testified that the risk (four-gene signature) was an independent prognostic factors of both Overall Survival (OS) and Disease-free Survival (DFS) (P<0.05). In conclusion, the four-gene signature was correlated with the survival of ccRCC, and therefore, may help to provide significant clinical implications for predicting the prognosis of patients.

Gene expression signature in urine for diagnosing and assessing aggressiveness of bladder urothelial carcinoma.

PubMed

Mengual, Lourdes; Burset, Moisès; Ribal, María José; Ars, Elisabet; Marín-Aguilera, Mercedes; Fernández, Manuel; Ingelmo-Torres, Mercedes; Villavicencio, Humberto; Alcaraz, Antonio

2010-05-01

To develop an accurate and noninvasive method for bladder cancer diagnosis and prediction of disease aggressiveness based on the gene expression patterns of urine samples. Gene expression patterns of 341 urine samples from bladder urothelial cell carcinoma (UCC) patients and 235 controls were analyzed via TaqMan Arrays. In a first phase of the study, three consecutive gene selection steps were done to identify a gene set expression signature to detect and stratify UCC in urine. Subsequently, those genes more informative for UCC diagnosis and prediction of tumor aggressiveness were combined to obtain a classification system of bladder cancer samples. In a second phase, the obtained gene set signature was evaluated in a routine clinical scenario analyzing only voided urine samples. We have identified a 12+2 gene expression signature for UCC diagnosis and prediction of tumor aggressiveness on urine samples. Overall, this gene set panel had 98% sensitivity (SN) and 99% specificity (SP) in discriminating between UCC and control samples and 79% SN and 92% SP in predicting tumor aggressiveness. The translation of the model to the clinically applicable format corroborates that the 12+2 gene set panel described maintains a high accuracy for UCC diagnosis (SN = 89% and SP = 95%) and tumor aggressiveness prediction (SN = 79% and SP = 91%) in voided urine samples. The 12+2 gene expression signature described in urine is able to identify patients suffering from UCC and predict tumor aggressiveness. We show that a panel of molecular markers may improve the schedule for diagnosis and follow-up in UCC patients. Copyright 2010 AACR.

CrossLink: a novel method for cross-condition classification of cancer subtypes.

PubMed

Ma, Chifeng; Sastry, Konduru S; Flore, Mario; Gehani, Salah; Al-Bozom, Issam; Feng, Yusheng; Serpedin, Erchin; Chouchane, Lotfi; Chen, Yidong; Huang, Yufei

2016-08-22

We considered the prediction of cancer classes (e.g. subtypes) using patient gene expression profiles that contain both systematic and condition-specific biases when compared with the training reference dataset. The conventional normalization-based approaches cannot guarantee that the gene signatures in the reference and prediction datasets always have the same distribution for all different conditions as the class-specific gene signatures change with the condition. Therefore, the trained classifier would work well under one condition but not under another. To address the problem of current normalization approaches, we propose a novel algorithm called CrossLink (CL). CL recognizes that there is no universal, condition-independent normalization mapping of signatures. In contrast, it exploits the fact that the signature is unique to its associated class under any condition and thus employs an unsupervised clustering algorithm to discover this unique signature. We assessed the performance of CL for cross-condition predictions of PAM50 subtypes of breast cancer by using a simulated dataset modeled after TCGA BRCA tumor samples with a cross-validation scheme, and datasets with known and unknown PAM50 classification. CL achieved prediction accuracy >73 %, highest among other methods we evaluated. We also applied the algorithm to a set of breast cancer tumors derived from Arabic population to assign a PAM50 classification to each tumor based on their gene expression profiles. A novel algorithm CrossLink for cross-condition prediction of cancer classes was proposed. In all test datasets, CL showed robust and consistent improvement in prediction performance over other state-of-the-art normalization and classification algorithms.

Mutational Signatures in Cancer (MuSiCa): a web application to implement mutational signatures analysis in cancer samples.

PubMed

Díaz-Gay, Marcos; Vila-Casadesús, Maria; Franch-Expósito, Sebastià; Hernández-Illán, Eva; Lozano, Juan José; Castellví-Bel, Sergi

2018-06-14

Mutational signatures have been proved as a valuable pattern in somatic genomics, mainly regarding cancer, with a potential application as a biomarker in clinical practice. Up to now, several bioinformatic packages to address this topic have been developed in different languages/platforms. MutationalPatterns has arisen as the most efficient tool for the comparison with the signatures currently reported in the Catalogue of Somatic Mutations in Cancer (COSMIC) database. However, the analysis of mutational signatures is nowadays restricted to a small community of bioinformatic experts. In this work we present Mutational Signatures in Cancer (MuSiCa), a new web tool based on MutationalPatterns and built using the Shiny framework in R language. By means of a simple interface suited to non-specialized researchers, it provides a comprehensive analysis of the somatic mutational status of the supplied cancer samples. It permits characterizing the profile and burden of mutations, as well as quantifying COSMIC-reported mutational signatures. It also allows classifying samples according to the above signature contributions. MuSiCa is a helpful web application to characterize mutational signatures in cancer samples. It is accessible online at http://bioinfo.ciberehd.org/GPtoCRC/en/tools.html and source code is freely available at https://github.com/marcos-diazg/musica .

Raman spectroscopy: in vivo quick response code of skin physiological status

NASA Astrophysics Data System (ADS)

Vyumvuhore, Raoul; Tfayli, Ali; Piot, Olivier; Le Guillou, Maud; Guichard, Nathalie; Manfait, Michel; Baillet-Guffroy, Arlette

2014-11-01

Dermatologists need to combine different clinically relevant characteristics for a better understanding of skin health. These characteristics are usually measured by different techniques, and some of them are highly time consuming. Therefore, a predicting model based on Raman spectroscopy and partial least square (PLS) regression was developed as a rapid multiparametric method. The Raman spectra collected from the five uppermost micrometers of 11 healthy volunteers were fitted to different skin characteristics measured by independent appropriate methods (transepidermal water loss, hydration, pH, relative amount of ceramides, fatty acids, and cholesterol). For each parameter, the obtained PLS model presented correlation coefficients higher than R2=0.9. This model enables us to obtain all the aforementioned parameters directly from the unique Raman signature. In addition to that, in-depth Raman analyses down to 20 μm showed different balances between partially bound water and unbound water with depth. In parallel, the increase of depth was followed by an unfolding process of the proteins. The combinations of all these information led to a multiparametric investigation, which better characterizes the skin status. Raman signal can thus be used as a quick response code (QR code). This could help dermatologic diagnosis of physiological variations and presents a possible extension to pathological characterization.

Raman spectroscopy: in vivo quick response code of skin physiological status.

PubMed

Vyumvuhore, Raoul; Tfayli, Ali; Piot, Olivier; Le Guillou, Maud; Guichard, Nathalie; Manfait, Michel; Baillet-Guffroy, Arlette

2014-01-01

Dermatologists need to combine different clinically relevant characteristics for a better understanding of skin health. These characteristics are usually measured by different techniques, and some of them are highly time consuming. Therefore, a predicting model based on Raman spectroscopy and partial least square (PLS) regression was developed as a rapid multiparametric method. The Raman spectra collected from the five uppermost micrometers of 11 healthy volunteers were fitted to different skin characteristics measured by independent appropriate methods (transepidermal water loss, hydration, pH, relative amount of ceramides, fatty acids, and cholesterol). For each parameter, the obtained PLS model presented correlation coefficients higher than R2=0.9. This model enables us to obtain all the aforementioned parameters directly from the unique Raman signature. In addition to that, in-depth Raman analyses down to 20 μm showed different balances between partially bound water and unbound water with depth. In parallel, the increase of depth was followed by an unfolding process of the proteins. The combinations of all these information led to a multiparametric investigation, which better characterizes the skin status. Raman signal can thus be used as a quick response code (QR code). This could help dermatologic diagnosis of physiological variations and presents a possible extension to pathological characterization.

Prediction of sonic boom from experimental near-field overpressure data. Volume 2: Data base construction

NASA Technical Reports Server (NTRS)

Glatt, C. R.; Reiners, S. J.; Hague, D. S.

1975-01-01

A computerized method for storing, updating and augmenting experimentally determined overpressure signatures has been developed. A data base of pressure signatures for a shuttle type vehicle has been stored. The data base has been used for the prediction of sonic boom with the program described in Volume I.

A Gene Expression Profile of BRCAness that Predicts for Responsiveness to Platinum and PARP Inhibitors

DTIC Science & Technology

2011-08-01

tumors as BRCA-like (BL) or non-BRCA-like ( NBL ) corresponding to tumors predicted to have a BRCAness phenotype (BL tumors) or not ( NBL tumors). In...of six specimens with ATM knock down had the BL signature and six of six control specimens had the NBL signature (Fisher’s exact two sided p=0.002...control specimens had the NBL signature (Fisher’s exact two sided p=0.067). Figure 2. BRCAness profile distinguishes between BRCA1 knock down

Dynamics of Magnetopause Reconnection in Response to Variable Solar Wind Conditions

NASA Astrophysics Data System (ADS)

Berchem, J.; Richard, R. L.; Escoubet, C. P.; Pitout, F.

2017-12-01

Quantifying the dynamics of magnetopause reconnection in response to variable solar wind driving is essential to advancing our predictive understanding of the interaction of the solar wind/IMF with the magnetosphere. To this end we have carried out numerical studies that combine global magnetohydrodynamic (MHD) and Large-Scale Kinetic (LSK) simulations to identify and understand the effects of solar wind/IMF variations. The use of the low dissipation, high resolution UCLA MHD code incorporating a non-linear local resistivity allows the representation of the global configuration of the dayside magnetosphere while the use of LSK ion test particle codes with distributed particle detectors allows us to compare the simulation results with spacecraft observations such as ion dispersion signatures observed by the Cluster spacecraft. We present the results of simulations that focus on the impacts of relatively simple solar wind discontinuities on the magnetopause and examine how the recent history of the interaction of the magnetospheric boundary with solar wind discontinuities can modify the dynamics of magnetopause reconnection in response to the solar wind input.

Genomic signatures predict migration and spawning failure in wild Canadian salmon.

PubMed

Miller, Kristina M; Li, Shaorong; Kaukinen, Karia H; Ginther, Norma; Hammill, Edd; Curtis, Janelle M R; Patterson, David A; Sierocinski, Thomas; Donnison, Louise; Pavlidis, Paul; Hinch, Scott G; Hruska, Kimberly A; Cooke, Steven J; English, Karl K; Farrell, Anthony P

2011-01-14

Long-term population viability of Fraser River sockeye salmon (Oncorhynchus nerka) is threatened by unusually high levels of mortality as they swim to their spawning areas before they spawn. Functional genomic studies on biopsied gill tissue from tagged wild adults that were tracked through ocean and river environments revealed physiological profiles predictive of successful migration and spawning. We identified a common genomic profile that was correlated with survival in each study. In ocean-tagged fish, a mortality-related genomic signature was associated with a 13.5-fold greater chance of dying en route. In river-tagged fish, the same genomic signature was associated with a 50% increase in mortality before reaching the spawning grounds in one of three stocks tested. At the spawning grounds, the same signature was associated with 3.7-fold greater odds of dying without spawning. Functional analysis raises the possibility that the mortality-related signature reflects a viral infection.

Gyneco-oncological genomics and emerging biomarkers for cancer treatment with immune-checkpoint inhibitors.

PubMed

Curigliano, Giuseppe

2018-05-15

In gynecological cancers tumor infiltrating lymphocytes and upregulation of immune-related gene signatures have been associated with a better prognosis. Knowledge of tumor immunogenicity and associated gene signatures suggests that the tumor immune landscape is a key determinant to define patient prognosis and potentially to predict response to immune-checkpoint inhibitors. The aim of this review is to give an overview of immune gene signatures across gynecology histological cancer types, defining their prognostic and potential predictive role. In the current review we will present data on these gene signatures, on immunohistochemical features and their potential importance to select patients potentially eligible to trials with immune-checkpoint inhibitors. Copyright © 2018 Elsevier Ltd. All rights reserved.

Signatures of Nonlinear Waves in Coronal Plumes and Holes

NASA Technical Reports Server (NTRS)

Ofman, Leon

1999-01-01

In recent Ultraviolet Coronagraph Spectrometer/Solar and Heliospheric Observatory (UVCS/SOHO) White Light Channel (WLC) observations we found quasi-periodic variations in the polarized brightness (pB) in the polar coronal holes at heliocentric distances of 1.9-2.45 solar radii. The motivation for the observation is the 2.5D Magnetohydrodynamics (MHD) model of solar wind acceleration by nonlinear waves, that predicts compressive fluctuations in coronal holes. To help identify the waves observed with the UVCS/WLC we model the propagation and dissipation of slow magnetosonic waves in polar plumes using 1D MHD code in spherical geometry, We find that the slow waves nonlinearly steepen in the gravitationally stratified plumes. The nonlinear steepening of the waves leads to enhanced dissipation due to compressive viscosity at the wave-fronts.

Gene-Expression Signature Predicts Postoperative Recurrence in Stage I Non-Small Cell Lung Cancer Patients

PubMed Central

Lu, Yan; Wang, Liang; Liu, Pengyuan; Yang, Ping; You, Ming

2012-01-01

About 30% stage I non-small cell lung cancer (NSCLC) patients undergoing resection will recur. Robust prognostic markers are required to better manage therapy options. The purpose of this study is to develop and validate a novel gene-expression signature that can predict tumor recurrence of stage I NSCLC patients. Cox proportional hazards regression analysis was performed to identify recurrence-related genes and a partial Cox regression model was used to generate a gene signature of recurrence in the training dataset −142 stage I lung adenocarcinomas without adjunctive therapy from the Director's Challenge Consortium. Four independent validation datasets, including GSE5843, GSE8894, and two other datasets provided by Mayo Clinic and Washington University, were used to assess the prediction accuracy by calculating the correlation between risk score estimated from gene expression and real recurrence-free survival time and AUC of time-dependent ROC analysis. Pathway-based survival analyses were also performed. 104 probesets correlated with recurrence in the training dataset. They are enriched in cell adhesion, apoptosis and regulation of cell proliferation. A 51-gene expression signature was identified to distinguish patients likely to develop tumor recurrence (Dxy = −0.83, P<1e-16) and this signature was validated in four independent datasets with AUC >85%. Multiple pathways including leukocyte transendothelial migration and cell adhesion were highly correlated with recurrence-free survival. The gene signature is highly predictive of recurrence in stage I NSCLC patients, which has important prognostic and therapeutic implications for the future management of these patients. PMID:22292069

Combining Gene Signatures Improves Prediction of Breast Cancer Survival

PubMed Central

Zhao, Xi; Naume, Bjørn; Langerød, Anita; Frigessi, Arnoldo; Kristensen, Vessela N.; Børresen-Dale, Anne-Lise; Lingjærde, Ole Christian

2011-01-01

Background Several gene sets for prediction of breast cancer survival have been derived from whole-genome mRNA expression profiles. Here, we develop a statistical framework to explore whether combination of the information from such sets may improve prediction of recurrence and breast cancer specific death in early-stage breast cancers. Microarray data from two clinically similar cohorts of breast cancer patients are used as training (n = 123) and test set (n = 81), respectively. Gene sets from eleven previously published gene signatures are included in the study. Principal Findings To investigate the relationship between breast cancer survival and gene expression on a particular gene set, a Cox proportional hazards model is applied using partial likelihood regression with an L2 penalty to avoid overfitting and using cross-validation to determine the penalty weight. The fitted models are applied to an independent test set to obtain a predicted risk for each individual and each gene set. Hierarchical clustering of the test individuals on the basis of the vector of predicted risks results in two clusters with distinct clinical characteristics in terms of the distribution of molecular subtypes, ER, PR status, TP53 mutation status and histological grade category, and associated with significantly different survival probabilities (recurrence: p = 0.005; breast cancer death: p = 0.014). Finally, principal components analysis of the gene signatures is used to derive combined predictors used to fit a new Cox model. This model classifies test individuals into two risk groups with distinct survival characteristics (recurrence: p = 0.003; breast cancer death: p = 0.001). The latter classifier outperforms all the individual gene signatures, as well as Cox models based on traditional clinical parameters and the Adjuvant! Online for survival prediction. Conclusion Combining the predictive strength of multiple gene signatures improves prediction of breast cancer survival. The presented methodology is broadly applicable to breast cancer risk assessment using any new identified gene set. PMID:21423775

A Sensitive and Specific Neural Signature for Picture-Induced Negative Affect

PubMed Central

Chang, Luke J.; Gianaros, Peter J.; Manuck, Stephen B.; Krishnan, Anjali; Wager, Tor D.

2015-01-01

Neuroimaging has identified many correlates of emotion but has not yet yielded brain representations predictive of the intensity of emotional experiences in individuals. We used machine learning to identify a sensitive and specific signature of emotional responses to aversive images. This signature predicted the intensity of negative emotion in individual participants in cross validation (n =121) and test (n = 61) samples (high–low emotion = 93.5% accuracy). It was unresponsive to physical pain (emotion–pain = 92% discriminative accuracy), demonstrating that it is not a representation of generalized arousal or salience. The signature was comprised of mesoscale patterns spanning multiple cortical and subcortical systems, with no single system necessary or sufficient for predicting experience. Furthermore, it was not reducible to activity in traditional “emotion-related” regions (e.g., amygdala, insula) or resting-state networks (e.g., “salience,” “default mode”). Overall, this work identifies differentiable neural components of negative emotion and pain, providing a basis for new, brain-based taxonomies of affective processes. PMID:26098873

Genomic scar signatures associated with homologous recombination deficiency predict adverse clinical outcomes in patients with ovarian clear cell carcinoma.

PubMed

Chao, Angel; Lai, Chyong-Huey; Wang, Tzu-Hao; Jung, Shih-Ming; Lee, Yun-Shien; Chang, Wei-Yang; Yang, Lan-Yang; Ku, Fei-Chun; Huang, Huei-Jean; Chao, An-Shine; Wang, Chin-Jung; Chang, Ting-Chang; Wu, Ren-Chin

2018-05-03

We investigated whether genomic scar signatures associated with homologous recombination deficiency (HRD), which include telomeric allelic imbalance (TAI), large-scale transition (LST), and loss of heterozygosity (LOH), can predict clinical outcomes in patients with ovarian clear cell carcinoma (OCCC). We enrolled patients with OCCC (n = 80) and high-grade serous carcinoma (HGSC; n = 92) subjected to primary cytoreductive surgery, most of whom received platinum-based adjuvant chemotherapy. Genomic scar signatures based on genome-wide copy number data were determined in all participants and investigated in relation to prognosis. OCCC had significantly lower genomic scar signature scores than HGSC (p < 0.001). Near-triploid OCCC specimens showed higher TAI and LST scores compared with diploid tumors (p < 0.001). While high scores of these genomic scar signatures were significantly associated with better clinical outcomes in patients with HGSC, the opposite was evident for OCCC. Multivariate survival analysis in patients with OCCC identified high LOH scores as the main independent adverse predictor for both cancer-specific (hazard ratio [HR] = 3.22, p = 0.005) and progression-free survival (HR = 2.54, p = 0.01). In conclusion, genomic scar signatures associated with HRD predict adverse clinical outcomes in patients with OCCC. The LOH score was identified as the strongest prognostic indicator in this patient group. Genomic scar signatures associated with HRD are less frequent in OCCC than in HGSC. Genomic scar signatures associated with HRD have an adverse prognostic impact in patients with OCCC. LOH score is the strongest adverse prognostic factor in patients with OCCC.

Trabecular morphometry by fractal signature analysis is a novel marker of osteoarthritis progression.

PubMed

Kraus, Virginia Byers; Feng, Sheng; Wang, ShengChu; White, Scott; Ainslie, Maureen; Brett, Alan; Holmes, Anthony; Charles, H Cecil

2009-12-01

To evaluate the effectiveness of using subchondral bone texture observed on a radiograph taken at baseline to predict progression of knee osteoarthritis (OA) over a 3-year period. A total of 138 participants in the Prediction of Osteoarthritis Progression study were evaluated at baseline and after 3 years. Fractal signature analysis (FSA) of the medial subchondral tibial plateau was performed on fixed flexion radiographs of 248 nonreplaced knees, using a commercially available software tool. OA progression was defined as a change in joint space narrowing (JSN) or osteophyte formation of 1 grade according to a standardized knee atlas. Statistical analysis of fractal signatures was performed using a new model based on correlating the overall shape of a fractal dimension curve with radius. Fractal signature of the medial tibial plateau at baseline was predictive of medial knee JSN progression (area under the curve [AUC] 0.75, of a receiver operating characteristic curve) but was not predictive of osteophyte formation or progression of JSN in the lateral compartment. Traditional covariates (age, sex, body mass index, knee pain), general bone mineral content, and joint space width at baseline were no more effective than random variables for predicting OA progression (AUC 0.52-0.58). The predictive model with maximum effectiveness combined fractal signature at baseline, knee alignment, traditional covariates, and bone mineral content (AUC 0.79). We identified a prognostic marker of OA that is readily extracted from a plain radiograph using FSA. Although the method needs to be validated in a second cohort, our results indicate that the global shape approach to analyzing these data is a potentially efficient means of identifying individuals at risk of knee OA progression.

HOXD-AS1 is a novel lncRNA encoded in HOXD cluster and a marker of neuroblastoma progression revealed via integrative analysis of noncoding transcriptome

PubMed Central

2014-01-01

Background Long noncoding RNAs (lncRNAs) constitute a major, but poorly characterized part of human transcriptome. Recent evidence indicates that many lncRNAs are involved in cancer and can be used as predictive and prognostic biomarkers. Significant fraction of lncRNAs is represented on widely used microarray platforms, however they have usually been ignored in cancer studies. Results We developed a computational pipeline to annotate lncRNAs on popular Affymetrix U133 microarrays, creating a resource allowing measurement of expression of 1581 lncRNAs. This resource can be utilized to interrogate existing microarray datasets for various lncRNA studies. We found that these lncRNAs fall into three distinct classes according to their statistical distribution by length. Remarkably, these three classes of lncRNAs were co-localized with protein coding genes exhibiting distinct gene ontology groups. This annotation was applied to microarray analysis which identified a 159 lncRNA signature that discriminates between localized and metastatic stages of neuroblastoma. Analysis of an independent patient cohort revealed that this signature differentiates also relapsing from non-relapsing primary tumors. This is the first example of the signature developed via the analysis of expression of lncRNAs solely. One of these lncRNAs, termed HOXD-AS1, is encoded in HOXD cluster. HOXD-AS1 is evolutionary conserved among hominids and has all bona fide features of a gene. Studying retinoid acid (RA) response of SH-SY5Y cell line, a model of human metastatic neuroblastoma, we found that HOXD-AS1 is a subject to morphogenic regulation, is activated by PI3K/Akt pathway and itself is involved in control of RA-induced cell differentiation. Knock-down experiments revealed that HOXD-AS1 controls expression levels of clinically significant protein-coding genes involved in angiogenesis and inflammation, the hallmarks of metastatic cancer. Conclusions Our findings greatly extend the number of noncoding RNAs functionally implicated in tumor development and patient treatment and highlight their role as potential prognostic biomarkers of neuroblastomas. PMID:25522241

Mechatronics technology in predictive maintenance method

NASA Astrophysics Data System (ADS)

Majid, Nurul Afiqah A.; Muthalif, Asan G. A.

2017-11-01

This paper presents recent mechatronics technology that can help to implement predictive maintenance by combining intelligent and predictive maintenance instrument. Vibration Fault Simulation System (VFSS) is an example of mechatronics system. The focus of this study is the prediction on the use of critical machines to detect vibration. Vibration measurement is often used as the key indicator of the state of the machine. This paper shows the choice of the appropriate strategy in the vibration of diagnostic process of the mechanical system, especially rotating machines, in recognition of the failure during the working process. In this paper, the vibration signature analysis is implemented to detect faults in rotary machining that includes imbalance, mechanical looseness, bent shaft, misalignment, missing blade bearing fault, balancing mass and critical speed. In order to perform vibration signature analysis for rotating machinery faults, studies have been made on how mechatronics technology is used as predictive maintenance methods. Vibration Faults Simulation Rig (VFSR) is designed to simulate and understand faults signatures. These techniques are based on the processing of vibrational data in frequency-domain. The LabVIEW-based spectrum analyzer software is developed to acquire and extract frequency contents of faults signals. This system is successfully tested based on the unique vibration fault signatures that always occur in a rotating machinery.

Whole-genome landscapes of major melanoma subtypes

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

Hayward, Nicholas K.; Wilmott, James S.; Waddell, Nicola

Melanoma of the skin is a common cancer only in Europeans, whereas it arises in internal body surfaces (mucosal sites) and on the hands and feet (acral sites) in people throughout the world. We report analysis of whole-genome sequences from cutaneous, acral and mucosal subtypes of melanoma. The heavily mutated landscape of coding and non-coding mutations in cutaneous melanoma resolved novel signatures of mutagenesis attributable to ultraviolet radiation. But, acral and mucosal melanomas were dominated by structural changes and mutation signatures of unknown aetiology, not previously identified in melanoma. The number of genes affected by recurrent mutations disrupting non-coding sequencesmore » was similar to that affected by recurrent mutations to coding sequences. Significantly mutated genes included BRAF, CDKN2A, NRAS and TP53 in cutaneous melanoma, BRAF, NRAS and NF1 in acral melanoma and SF3B1 in mucosal melanoma. Mutations affecting the TERT promoter were the most frequent of all; however, neither they nor ATRX mutations, which correlate with alternative telomere lengthening, were associated with greater telomere length. In most cases, melanomas had potentially actionable mutations, most in components of the mitogen-activated protein kinase and phosphoinositol kinase pathways. The whole-genome mutation landscape of melanoma reveals diverse carcinogenic processes across its subtypes, some unrelated to sun exposure, and extends potential involvement of the non-coding genome in its pathogenesis.« less

Whole-genome landscapes of major melanoma subtypes

DOE PAGES

Hayward, Nicholas K.; Wilmott, James S.; Waddell, Nicola; ...

2017-05-03

Melanoma of the skin is a common cancer only in Europeans, whereas it arises in internal body surfaces (mucosal sites) and on the hands and feet (acral sites) in people throughout the world. We report analysis of whole-genome sequences from cutaneous, acral and mucosal subtypes of melanoma. The heavily mutated landscape of coding and non-coding mutations in cutaneous melanoma resolved novel signatures of mutagenesis attributable to ultraviolet radiation. But, acral and mucosal melanomas were dominated by structural changes and mutation signatures of unknown aetiology, not previously identified in melanoma. The number of genes affected by recurrent mutations disrupting non-coding sequencesmore » was similar to that affected by recurrent mutations to coding sequences. Significantly mutated genes included BRAF, CDKN2A, NRAS and TP53 in cutaneous melanoma, BRAF, NRAS and NF1 in acral melanoma and SF3B1 in mucosal melanoma. Mutations affecting the TERT promoter were the most frequent of all; however, neither they nor ATRX mutations, which correlate with alternative telomere lengthening, were associated with greater telomere length. In most cases, melanomas had potentially actionable mutations, most in components of the mitogen-activated protein kinase and phosphoinositol kinase pathways. The whole-genome mutation landscape of melanoma reveals diverse carcinogenic processes across its subtypes, some unrelated to sun exposure, and extends potential involvement of the non-coding genome in its pathogenesis.« less

Molecular cloning and functional characterization of an antifungal PR-5 protein from Ocimum basilicum.

PubMed

Rather, Irshad Ahmad; Awasthi, Praveen; Mahajan, Vidushi; Bedi, Yashbir S; Vishwakarma, Ram A; Gandhi, Sumit G

2015-03-01

Pathogenesis-related (PR) proteins are involved in biotic and abiotic stress responses of plants and are grouped into 17 families (PR-1 to PR-17). PR-5 family includes proteins related to thaumatin and osmotin, with several members possessing antimicrobial properties. In this study, a PR-5 gene showing a high degree of homology with osmotin-like protein was isolated from sweet basil (Ocimum basilicum L.). A complete open reading frame consisting of 675 nucleotides, coding for a precursor protein, was obtained by PCR amplification. Based on sequence comparisons with tobacco osmotin and other osmotin-like proteins (OLPs), this protein was named ObOLP. The predicted mature protein is 225 amino acids in length and contains 16 cysteine residues that may potentially form eight disulfide bonds, a signature common to most PR-5 proteins. Among the various abiotic stress treatments tested, including high salt, mechanical wounding and exogenous phytohormone/elicitor treatments; methyl jasmonate (MeJA) and mechanical wounding significantly induced the expression of ObOLP gene. The coding sequence of ObOLP was cloned and expressed in a bacterial host resulting in a 25kDa recombinant-HIS tagged protein, displaying antifungal activity. The ObOLP protein sequence appears to contain an N-terminal signal peptide with signatures of secretory pathway. Further, our experimental data shows that ObOLP expression is regulated transcriptionally and in silico analysis suggests that it may be post-transcriptionally and post-translationally regulated through microRNAs and post-translational protein modifications, respectively. This study appears to be the first report of isolation and characterization of osmotin-like protein gene from O. basilicum. Copyright © 2014 Elsevier B.V. All rights reserved.

Supervised Multi-Authority Scheme with Blind Signature for IoT with Attribute Based Encryption

NASA Astrophysics Data System (ADS)

Nissenbaum, O. V.; Ponomarov, K. Y.; Zaharov, A. A.

2018-04-01

This article proposes a three-side cryptographic scheme for verifying device attributes with a Supervisor and a Certification Authority (CA) for attribute-based encryption. Two options are suggested: using a message authentication code and using a digital signature. The first version is suitable for networks with one CA, and the second one for networks with several CAs, including dynamic systems. Also, the addition of this scheme with a blind signature is proposed to preserve the confidentiality of the device attributes from the CA. The introduction gives a definition and a brief historical overview of attribute-based encryption (ABE), addresses the use of ABE in the Internet of Things.

A study of the limitations of linear theory methods as applied to sonic boom calculations

NASA Technical Reports Server (NTRS)

Darden, Christine M.

1990-01-01

Current sonic boom minimization theories have been reviewed to emphasize the capabilities and flexibilities of the methods. Flexibility is important because it is necessary for the designer to meet optimized area constraints while reducing the impact on vehicle aerodynamic performance. Preliminary comparisons of sonic booms predicted for two Mach 3 concepts illustrate the benefits of shaping. Finally, for very simple bodies of revolution, sonic boom predictions were made using two methods - a modified linear theory method and a nonlinear method - for signature shapes which were both farfield N-waves and midfield waves. Preliminary analysis on these simple bodies verified that current modified linear theory prediction methods become inadequate for predicting midfield signatures for Mach numbers above 3. The importance of impulse is sonic boom disturbance and the importance of three-dimensional effects which could not be simulated with the bodies of revolution will determine the validity of current modified linear theory methods in predicting midfield signatures at lower Mach numbers.

EO/IR scene generation open source initiative for real-time hardware-in-the-loop and all-digital simulation

NASA Astrophysics Data System (ADS)

Morris, Joseph W.; Lowry, Mac; Boren, Brett; Towers, James B.; Trimble, Darian E.; Bunfield, Dennis H.

2011-06-01

The US Army Aviation and Missile Research, Development and Engineering Center (AMRDEC) and the Redstone Test Center (RTC) has formed the Scene Generation Development Center (SGDC) to support the Department of Defense (DoD) open source EO/IR Scene Generation initiative for real-time hardware-in-the-loop and all-digital simulation. Various branches of the DoD have invested significant resources in the development of advanced scene and target signature generation codes. The SGDC goal is to maintain unlimited government rights and controlled access to government open source scene generation and signature codes. In addition, the SGDC provides development support to a multi-service community of test and evaluation (T&E) users, developers, and integrators in a collaborative environment. The SGDC has leveraged the DoD Defense Information Systems Agency (DISA) ProjectForge (https://Project.Forge.mil) which provides a collaborative development and distribution environment for the DoD community. The SGDC will develop and maintain several codes for tactical and strategic simulation, such as the Joint Signature Image Generator (JSIG), the Multi-spectral Advanced Volumetric Real-time Imaging Compositor (MAVRIC), and Office of the Secretary of Defense (OSD) Test and Evaluation Science and Technology (T&E/S&T) thermal modeling and atmospherics packages, such as EOView, CHARM, and STAR. Other utility packages included are the ContinuumCore for real-time messaging and data management and IGStudio for run-time visualization and scenario generation.

Ion channel gene expression predicts survival in glioma patients

PubMed Central

Wang, Rong; Gurguis, Christopher I.; Gu, Wanjun; Ko, Eun A; Lim, Inja; Bang, Hyoweon; Zhou, Tong; Ko, Jae-Hong

2015-01-01

Ion channels are important regulators in cell proliferation, migration, and apoptosis. The malfunction and/or aberrant expression of ion channels may disrupt these important biological processes and influence cancer progression. In this study, we investigate the expression pattern of ion channel genes in glioma. We designate 18 ion channel genes that are differentially expressed in high-grade glioma as a prognostic molecular signature. This ion channel gene expression based signature predicts glioma outcome in three independent validation cohorts. Interestingly, 16 of these 18 genes were down-regulated in high-grade glioma. This signature is independent of traditional clinical, molecular, and histological factors. Resampling tests indicate that the prognostic power of the signature outperforms random gene sets selected from human genome in all the validation cohorts. More importantly, this signature performs better than the random gene signatures selected from glioma-associated genes in two out of three validation datasets. This study implicates ion channels in brain cancer, thus expanding on knowledge of their roles in other cancers. Individualized profiling of ion channel gene expression serves as a superior and independent prognostic tool for glioma patients. PMID:26235283

Signatures of doubly-charged Higgsinos at colliders

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

Demir, D. A.; Deutsches Elektronen-Synchrotron, DESY, D-22603 Hamburg; Frank, M.

2008-11-23

Several supersymmetric models with extended gauge structures predict light doubly-charged Higgsinos. Their distinctive signature at the large hadron collider is highlighted by studying its production and decay characteristics.

Internet Protocol Security (IPSEC): Testing and Implications on IPv4 and IPv6 Networks

DTIC Science & Technology

2008-08-27

Message Authentication Code-Message Digest 5-96). Due to the processing power consumption and slowness of public key authentication methods, RSA ...MODP) group with a 768 -bit modulus 2. a MODP group with a 1024-bit modulus 3. an Elliptic Curve Group over GF[ 2n ] (EC2N) group with a 155-bit...nonces, digital signatures using the Digital Signature Algorithm, and the Rivest-Shamir- Adelman ( RSA ) algorithm. For more information about the

Security analysis of boolean algebra based on Zhang-Wang digital signature scheme

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

Zheng, Jinbin, E-mail: jbzheng518@163.com

2014-10-06

In 2005, Zhang and Wang proposed an improvement signature scheme without using one-way hash function and message redundancy. In this paper, we show that this scheme exits potential safety concerns through the analysis of boolean algebra, such as bitwise exclusive-or, and point out that mapping is not one to one between assembly instructions and machine code actually by means of the analysis of the result of the assembly program segment, and which possibly causes safety problems unknown to the software.

USM3D Analysis of Low Boom Configuration

NASA Technical Reports Server (NTRS)

Carter, Melissa B.; Campbell, Richard L.; Nayani, Sudheer N.

2011-01-01

In the past few years considerable improvement was made in NASA's in house boom prediction capability. As part of this improved capability, the USM3D Navier-Stokes flow solver, when combined with a suitable unstructured grid, went from accurately predicting boom signatures at 1 body length to 10 body lengths. Since that time, the research emphasis has shifted from analysis to the design of supersonic configurations with boom signature mitigation In order to design an aircraft, the techniques for accurately predicting boom and drag need to be determined. This paper compares CFD results with the wind tunnel experimental results conducted on a Gulfstream reduced boom and drag configuration. Two different wind-tunnel models were designed and tested for drag and boom data. The goal of this study was to assess USM3D capability for predicting both boom and drag characteristics. Overall, USM3D coupled with a grid that was sheared and stretched was able to reasonably predict boom signature. The computational drag polar matched the experimental results for a lift coefficient above 0.1 despite some mismatch in the predicted lift-curve slope.

A Gene Signature to Determine Metastatic Behavior in Thymomas

PubMed Central

Gökmen-Polar, Yesim; Wilkinson, Jeff; Maetzold, Derek; Stone, John F.; Oelschlager, Kristen M.; Vladislav, Ioan Tudor; Shirar, Kristen L.; Kesler, Kenneth A.; Loehrer, Patrick J.; Badve, Sunil

2013-01-01

Purpose Thymoma represents one of the rarest of all malignancies. Stage and completeness of resection have been used to ascertain postoperative therapeutic strategies albeit with limited prognostic accuracy. A molecular classifier would be useful to improve the assessment of metastatic behaviour and optimize patient management. Methods qRT-PCR assay for 23 genes (19 test and four reference genes) was performed on multi-institutional archival primary thymomas (n = 36). Gene expression levels were used to compute a signature, classifying tumors into classes 1 and 2, corresponding to low or high likelihood for metastases. The signature was validated in an independent multi-institutional cohort of patients (n = 75). Results A nine-gene signature that can predict metastatic behavior of thymomas was developed and validated. Using radial basis machine modeling in the training set, 5-year and 10-year metastasis-free survival rates were 77% and 26% for predicted low (class 1) and high (class 2) risk of metastasis (P = 0.0047, log-rank), respectively. For the validation set, 5-year metastasis-free survival rates were 97% and 30% for predicted low- and high-risk patients (P = 0.0004, log-rank), respectively. The 5-year metastasis-free survival rates for the validation set were 49% and 41% for Masaoka stages I/II and III/IV (P = 0.0537, log-rank), respectively. In univariate and multivariate Cox models evaluating common prognostic factors for thymoma metastasis, the nine-gene signature was the only independent indicator of metastases (P = 0.036). Conclusion A nine-gene signature was established and validated which predicts the likelihood of metastasis more accurately than traditional staging. This further underscores the biologic determinants of the clinical course of thymoma and may improve patient management. PMID:23894276

Prediction of Chemical Respiratory Sensitizers Using GARD, a Novel In Vitro Assay Based on a Genomic Biomarker Signature

PubMed Central

Albrekt, Ann-Sofie; Borrebaeck, Carl A. K.; Lindstedt, Malin

2015-01-01

Background Repeated exposure to certain low molecular weight (LMW) chemical compounds may result in development of allergic reactions in the skin or in the respiratory tract. In most cases, a certain LMW compound selectively sensitize the skin, giving rise to allergic contact dermatitis (ACD), or the respiratory tract, giving rise to occupational asthma (OA). To limit occurrence of allergic diseases, efforts are currently being made to develop predictive assays that accurately identify chemicals capable of inducing such reactions. However, while a few promising methods for prediction of skin sensitization have been described, to date no validated method, in vitro or in vivo, exists that is able to accurately classify chemicals as respiratory sensitizers. Results Recently, we presented the in vitro based Genomic Allergen Rapid Detection (GARD) assay as a novel testing strategy for classification of skin sensitizing chemicals based on measurement of a genomic biomarker signature. We have expanded the applicability domain of the GARD assay to classify also respiratory sensitizers by identifying a separate biomarker signature containing 389 differentially regulated genes for respiratory sensitizers in comparison to non-respiratory sensitizers. By using an independent data set in combination with supervised machine learning, we validated the assay, showing that the identified genomic biomarker is able to accurately classify respiratory sensitizers. Conclusions We have identified a genomic biomarker signature for classification of respiratory sensitizers. Combining this newly identified biomarker signature with our previously identified biomarker signature for classification of skin sensitizers, we have developed a novel in vitro testing strategy with a potent ability to predict both skin and respiratory sensitization in the same sample. PMID:25760038

Hyperspectral target detection analysis of a cluttered scene from a virtual airborne sensor platform using MuSES

NASA Astrophysics Data System (ADS)

Packard, Corey D.; Viola, Timothy S.; Klein, Mark D.

2017-10-01

The ability to predict spectral electro-optical (EO) signatures for various targets against realistic, cluttered backgrounds is paramount for rigorous signature evaluation. Knowledge of background and target signatures, including plumes, is essential for a variety of scientific and defense-related applications including contrast analysis, camouflage development, automatic target recognition (ATR) algorithm development and scene material classification. The capability to simulate any desired mission scenario with forecast or historical weather is a tremendous asset for defense agencies, serving as a complement to (or substitute for) target and background signature measurement campaigns. In this paper, a systematic process for the physical temperature and visible-through-infrared radiance prediction of several diverse targets in a cluttered natural environment scene is presented. The ability of a virtual airborne sensor platform to detect and differentiate targets from a cluttered background, from a variety of sensor perspectives and across numerous wavelengths in differing atmospheric conditions, is considered. The process described utilizes the thermal and radiance simulation software MuSES and provides a repeatable, accurate approach for analyzing wavelength-dependent background and target (including plume) signatures in multiple band-integrated wavebands (multispectral) or hyperspectrally. The engineering workflow required to combine 3D geometric descriptions, thermal material properties, natural weather boundary conditions, all modes of heat transfer and spectral surface properties is summarized. This procedure includes geometric scene creation, material and optical property attribution, and transient physical temperature prediction. Radiance renderings, based on ray-tracing and the Sandford-Robertson BRDF model, are coupled with MODTRAN for the inclusion of atmospheric effects. This virtual hyperspectral/multispectral radiance prediction methodology has been extensively validated and provides a flexible process for signature evaluation and algorithm development.

Genome signature analysis of thermal virus metagenomes reveals Archaea and thermophilic signatures

PubMed Central

Pride, David T; Schoenfeld, Thomas

2008-01-01

Background Metagenomic analysis provides a rich source of biological information for otherwise intractable viral communities. However, study of viral metagenomes has been hampered by its nearly complete reliance on BLAST algorithms for identification of DNA sequences. We sought to develop algorithms for examination of viral metagenomes to identify the origin of sequences independent of BLAST algorithms. We chose viral metagenomes obtained from two hot springs, Bear Paw and Octopus, in Yellowstone National Park, as they represent simple microbial populations where comparatively large contigs were obtained. Thermal spring metagenomes have high proportions of sequences without significant Genbank homology, which has hampered identification of viruses and their linkage with hosts. To analyze each metagenome, we developed a method to classify DNA fragments using genome signature-based phylogenetic classification (GSPC), where metagenomic fragments are compared to a database of oligonucleotide signatures for all previously sequenced Bacteria, Archaea, and viruses. Results From both Bear Paw and Octopus hot springs, each assembled contig had more similarity to other metagenome contigs than to any sequenced microbial genome based on GSPC analysis, suggesting a genome signature common to each of these extreme environments. While viral metagenomes from Bear Paw and Octopus share some similarity, the genome signatures from each locale are largely unique. GSPC using a microbial database predicts most of the Octopus metagenome has archaeal signatures, while bacterial signatures predominate in Bear Paw; a finding consistent with those of Genbank BLAST. When using a viral database, the majority of the Octopus metagenome is predicted to belong to archaeal virus Families Globuloviridae and Fuselloviridae, while none of the Bear Paw metagenome is predicted to belong to archaeal viruses. As expected, when microbial and viral databases are combined, each of the Octopus and Bear Paw metagenomic contigs are predicted to belong to viruses rather than to any Bacteria or Archaea, consistent with the apparent viral origin of both metagenomes. Conclusion That BLAST searches identify no significant homologs for most metagenome contigs, while GSPC suggests their origin as archaeal viruses or bacteriophages, indicates GSPC provides a complementary approach in viral metagenomic analysis. PMID:18798991

Genome signature analysis of thermal virus metagenomes reveals Archaea and thermophilic signatures.

PubMed

Pride, David T; Schoenfeld, Thomas

2008-09-17

Metagenomic analysis provides a rich source of biological information for otherwise intractable viral communities. However, study of viral metagenomes has been hampered by its nearly complete reliance on BLAST algorithms for identification of DNA sequences. We sought to develop algorithms for examination of viral metagenomes to identify the origin of sequences independent of BLAST algorithms. We chose viral metagenomes obtained from two hot springs, Bear Paw and Octopus, in Yellowstone National Park, as they represent simple microbial populations where comparatively large contigs were obtained. Thermal spring metagenomes have high proportions of sequences without significant Genbank homology, which has hampered identification of viruses and their linkage with hosts. To analyze each metagenome, we developed a method to classify DNA fragments using genome signature-based phylogenetic classification (GSPC), where metagenomic fragments are compared to a database of oligonucleotide signatures for all previously sequenced Bacteria, Archaea, and viruses. From both Bear Paw and Octopus hot springs, each assembled contig had more similarity to other metagenome contigs than to any sequenced microbial genome based on GSPC analysis, suggesting a genome signature common to each of these extreme environments. While viral metagenomes from Bear Paw and Octopus share some similarity, the genome signatures from each locale are largely unique. GSPC using a microbial database predicts most of the Octopus metagenome has archaeal signatures, while bacterial signatures predominate in Bear Paw; a finding consistent with those of Genbank BLAST. When using a viral database, the majority of the Octopus metagenome is predicted to belong to archaeal virus Families Globuloviridae and Fuselloviridae, while none of the Bear Paw metagenome is predicted to belong to archaeal viruses. As expected, when microbial and viral databases are combined, each of the Octopus and Bear Paw metagenomic contigs are predicted to belong to viruses rather than to any Bacteria or Archaea, consistent with the apparent viral origin of both metagenomes. That BLAST searches identify no significant homologs for most metagenome contigs, while GSPC suggests their origin as archaeal viruses or bacteriophages, indicates GSPC provides a complementary approach in viral metagenomic analysis.

Empirical source strength correlations for rans-based acoustic analogy methods

NASA Astrophysics Data System (ADS)

Kube-McDowell, Matthew Tyndall

JeNo is a jet noise prediction code based on an acoustic analogy method developed by Mani, Gliebe, Balsa, and Khavaran. Using the flow predictions from a standard Reynolds-averaged Navier-Stokes computational fluid dynamics solver, JeNo predicts the overall sound pressure level and angular spectra for high-speed hot jets over a range of observer angles, with a processing time suitable for rapid design purposes. JeNo models the noise from hot jets as a combination of two types of noise sources; quadrupole sources dependent on velocity fluctuations, which represent the major noise of turbulent mixing, and dipole sources dependent on enthalpy fluctuations, which represent the effects of thermal variation. These two sources are modeled by JeNo as propagating independently into the far-field, with no cross-correlation at the observer location. However, high-fidelity computational fluid dynamics solutions demonstrate that this assumption is false. In this thesis, the theory, assumptions, and limitations of the JeNo code are briefly discussed, and a modification to the acoustic analogy method is proposed in which the cross-correlation of the two primary noise sources is allowed to vary with the speed of the jet and the observer location. As a proof-of-concept implementation, an empirical correlation correction function is derived from comparisons between JeNo's noise predictions and a set of experimental measurements taken for the Air Force Aero-Propulsion Laboratory. The empirical correlation correction is then applied to JeNo's predictions of a separate data set of hot jets tested at NASA's Glenn Research Center. Metrics are derived to measure the qualitative and quantitative performance of JeNo's acoustic predictions, and the empirical correction is shown to provide a quantitative improvement in the noise prediction at low observer angles with no freestream flow, and a qualitative improvement in the presence of freestream flow. However, the results also demonstrate that there are underlying flaws in JeNo's ability to predict the behavior of a hot jet's acoustic signature at certain rear observer angles, and that this correlation correction is not able to correct these flaws.

Disentangling neural representations of value and salience in the human brain

PubMed Central

Kahnt, Thorsten; Park, Soyoung Q; Haynes, John-Dylan; Tobler, Philippe N.

2014-01-01

A large body of evidence has implicated the posterior parietal and orbitofrontal cortex in the processing of value. However, value correlates perfectly with salience when appetitive stimuli are investigated in isolation. Accordingly, considerable uncertainty has remained about the precise nature of the previously identified signals. In particular, recent evidence suggests that neurons in the primate parietal cortex signal salience instead of value. To investigate neural signatures of value and salience, here we apply multivariate (pattern-based) analyses to human functional MRI data acquired during a noninstrumental outcome-prediction task involving appetitive and aversive outcomes. Reaction time data indicated additive and independent effects of value and salience. Critically, we show that multivoxel ensemble activity in the posterior parietal cortex encodes predicted value and salience in superior and inferior compartments, respectively. These findings reinforce the earlier reports of parietal value signals and reconcile them with the recent salience report. Moreover, we find that multivoxel patterns in the orbitofrontal cortex correlate with value. Importantly, the patterns coding for the predicted value of appetitive and aversive outcomes are similar, indicating a common neural scale for appetite and aversive values in the orbitofrontal cortex. Thus orbitofrontal activity patterns satisfy a basic requirement for a neural value signal. PMID:24639493

Adding Spice to Vanilla LCDM simulations: Alternative Cosmologies & Lighting up Simulations

NASA Astrophysics Data System (ADS)

Jahan Elahi, Pascal

2015-08-01

Cold Dark Matter simulations have formed the backbone of our theoretical understanding of cosmological structure formation. Predictions from the Lambda Cold Dark Matter (LCDM) cosmology, where the Universe contains two dark components, namely Dark Matter & Dark Energy, are in excellent agreement with the Large-Scale Structures observed, i.e., the distribution of galaxies across cosmic time. However, this paradigm is in tension with observations at small-scales, from the number and properties of satellite galaxies around galaxies such as the Milky Way and Andromeda, to the lensing statistics of massive galaxy clusters. I will present several alternative models of cosmology (from Warm Dark Matter to coupled Dark Matter-Dark Energy models) and how they compare to vanilla LCDM by studying formation of groups and clusters dark matter only and adiabatic hydrodynamical zoom simulations. I will show how modifications to the dark sector can lead to some surprising results. For example, Warm Dark Matter, so often examined on small satellite galaxies scales, can be probed observationally using weak lensing at cluster scales. Coupled dark sectors, where dark matter decays into dark energy and experiences an effective gravitational potential that differs from that experienced by normal matter, is effectively hidden away from direct observations of galaxies. Studies like these are vital if we are to pinpoint observations which can look for unique signatures of the physics that governs the hidden Universe. Finally, I will discuss how all of these predictions are affected by uncertain galaxy formation physics. I will present results from a major comparison study of numerous hydrodynamical codes, the nIFTY cluster comparison project. This comparison aims to understand the code-to-code scatter in the properties of dark matter haloes and the galaxies that reside in them. We find that even in purely adiabatic simulations, different codes form clusters with very different X-ray profiles. The galaxies that form in these simulations, which all use codes that attempt to reproduce the observed galaxy population via not unreasonable subgrid physics, vary in stellar mass, morphology and gas fraction, sometimes by an order of magnitude. I will end with a discussion of precision cosmology in light of these results.

Predicting individual differences in decision-making process from signature movement styles: an illustrative study of leaders.

PubMed

Connors, Brenda L; Rende, Richard; Colton, Timothy J

2013-01-01

There has been a surge of interest in examining the utility of methods for capturing individual differences in decision-making style. We illustrate the potential offered by Movement Pattern Analysis (MPA), an observational methodology that has been used in business and by the US Department of Defense to record body movements that provide predictive insight into individual differences in decision-making motivations and actions. Twelve military officers participated in an intensive 2-h interview that permitted detailed and fine-grained observation and coding of signature movements by trained practitioners using MPA. Three months later, these subjects completed four hypothetical decision-making tasks in which the amount of information sought out before coming to a decision, as well as the time spent on the tasks, were under the partial control of the subject. A composite MPA indicator of how a person allocates decision-making actions and motivations to balance both Assertion (exertion of tangible movement effort on the environment to make something occur) and Perspective (through movements that support shaping in the body to perceive and create a suitable viewpoint for action) was highly correlated with the total number of information draws and total response time-individuals high on Assertion reached for less information and had faster response times than those high on Perspective. Discussion focuses on the utility of using movement-based observational measures to capture individual differences in decision-making style and the implications for application in applied settings geared toward investigations of experienced leaders and world statesmen where individuality rules the day.

Predicting individual differences in decision-making process from signature movement styles: an illustrative study of leaders

PubMed Central

Connors, Brenda L.; Rende, Richard; Colton, Timothy J.

2013-01-01

There has been a surge of interest in examining the utility of methods for capturing individual differences in decision-making style. We illustrate the potential offered by Movement Pattern Analysis (MPA), an observational methodology that has been used in business and by the US Department of Defense to record body movements that provide predictive insight into individual differences in decision-making motivations and actions. Twelve military officers participated in an intensive 2-h interview that permitted detailed and fine-grained observation and coding of signature movements by trained practitioners using MPA. Three months later, these subjects completed four hypothetical decision-making tasks in which the amount of information sought out before coming to a decision, as well as the time spent on the tasks, were under the partial control of the subject. A composite MPA indicator of how a person allocates decision-making actions and motivations to balance both Assertion (exertion of tangible movement effort on the environment to make something occur) and Perspective (through movements that support shaping in the body to perceive and create a suitable viewpoint for action) was highly correlated with the total number of information draws and total response time—individuals high on Assertion reached for less information and had faster response times than those high on Perspective. Discussion focuses on the utility of using movement-based observational measures to capture individual differences in decision-making style and the implications for application in applied settings geared toward investigations of experienced leaders and world statesmen where individuality rules the day. PMID:24069012

Auditory brainstem responses to stop consonants predict literacy.

PubMed

Neef, Nicole E; Schaadt, Gesa; Friederici, Angela D

2017-03-01

Precise temporal coding of speech plays a pivotal role in sound processing throughout the central auditory system, which, in turn, influences literacy acquisition. The current study tests whether an electrophysiological measure of this precision predicts literacy skills. Complex auditory brainstem responses were analysed from 62 native German-speaking children aged 11-13years. We employed the cross-phaseogram approach to compute the quality of the electrophysiological stimulus contrast [da] and [ba]. Phase shifts were expected to vary with literacy. Receiver operating curves demonstrated a feasible sensitivity and specificity of the electrophysiological measure. A multiple regression analysis resulted in a significant prediction of literacy by delta cross-phase as well as phonological awareness. A further commonality analysis separated a unique variance that was explained by the physiological measure, from a unique variance that was explained by the behavioral measure, and common effects of both. Despite multicollinearities between literacy, phonological awareness, and subcortical differentiation of stop consonants, a combined assessment of behavior and physiology strongly increases the ability to predict literacy skills. The strong link between the neurophysiological signature of sound encoding and literacy outcome suggests that the delta cross-phase could indicate the risk of dyslexia and thereby complement subjective psychometric measures for early diagnoses. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

A Web-based open-source database for the distribution of hyperspectral signatures

NASA Astrophysics Data System (ADS)

Ferwerda, J. G.; Jones, S. D.; Du, Pei-Jun

2006-10-01

With the coming of age of field spectroscopy as a non-destructive means to collect information on the physiology of vegetation, there is a need for storage of signatures, and, more importantly, their metadata. Without the proper organisation of metadata, the signatures itself become limited. In order to facilitate re-distribution of data, a database for the storage & distribution of hyperspectral signatures and their metadata was designed. The database was built using open-source software, and can be used by the hyperspectral community to share their data. Data is uploaded through a simple web-based interface. The database recognizes major file-formats by ASD, GER and International Spectronics. The database source code is available for download through the hyperspectral.info web domain, and we happily invite suggestion for additions & modification for the database to be submitted through the online forums on the same website.

Gamma signatures of the C-BORD Tagged Neutron Inspection System

NASA Astrophysics Data System (ADS)

Sardet, A.; Pérot, B.; Carasco, C.; Sannié, G.; Moretto, S.; Nebbia, G.; Fontana, C.; Pino, F.; Iovene, A.; Tintori, C.

2018-01-01

In the frame of C-BORD project (H2020 program of the EU), a Rapidly relocatable Tagged Neutron Inspection System (RRTNIS) is being developed to non-intrusively detect explosives, chemical threats, and other illicit goods in cargo containers. Material identification is performed through gamma spectroscopy, using twenty NaI detectors and four LaBr3 detectors, to determine the different elements composing the inspected item from their specific gamma signatures induced by fast neutrons. This is performed using an unfolding algorithm to decompose the energy spectrum of a suspect item, selected by X-ray radiography and on which the RRTNIS inspection is focused, on a database of pure element gamma signatures. This paper reports on simulated signatures for the NaI and LaBr3 detectors, constructed using the MCNP6 code. First experimental spectra of a few elements of interest are also presented.

Inflammatory macrophage-associated 3-gene signature predicts subclinical allograft injury and graft survival.

PubMed

Azad, Tej D; Donato, Michele; Heylen, Line; Liu, Andrew B; Shen-Orr, Shai S; Sweeney, Timothy E; Maltzman, Jonathan Scott; Naesens, Maarten; Khatri, Purvesh

2018-01-25

Late allograft failure is characterized by cumulative subclinical insults manifesting over many years. Although immunomodulatory therapies targeting host T cells have improved short-term survival rates, rates of chronic allograft loss remain high. We hypothesized that other immune cell types may drive subclinical injury, ultimately leading to graft failure. We collected whole-genome transcriptome profiles from 15 independent cohorts composed of 1,697 biopsy samples to assess the association of an inflammatory macrophage polarization-specific gene signature with subclinical injury. We applied penalized regression to a subset of the data sets and identified a 3-gene inflammatory macrophage-derived signature. We validated discriminatory power of the 3-gene signature in 3 independent renal transplant data sets with mean AUC of 0.91. In a longitudinal cohort, the 3-gene signature strongly correlated with extent of injury and accurately predicted progression of subclinical injury 18 months before clinical manifestation. The 3-gene signature also stratified patients at high risk of graft failure as soon as 15 days after biopsy. We found that the 3-gene signature also distinguished acute rejection (AR) accurately in 3 heart transplant data sets but not in lung transplant. Overall, we identified a parsimonious signature capable of diagnosing AR, recognizing subclinical injury, and risk-stratifying renal transplant patients. Our results strongly suggest that inflammatory macrophages may be a viable therapeutic target to improve long-term outcomes for organ transplantation patients.

Gene Expression Signatures Based on Variability can Robustly Predict Tumor Progression and Prognosis

PubMed Central

Dinalankara, Wikum; Bravo, Héctor Corrada

2015-01-01

Gene expression signatures are commonly used to create cancer prognosis and diagnosis methods, yet only a small number of them are successfully deployed in the clinic since many fail to replicate performance on subsequent validation. A primary reason for this lack of reproducibility is the fact that these signatures attempt to model the highly variable and unstable genomic behavior of cancer. Our group recently introduced gene expression anti-profiles as a robust methodology to derive gene expression signatures based on the observation that while gene expression measurements are highly heterogeneous across tumors of a specific cancer type relative to the normal tissue, their degree of deviation from normal tissue expression in specific genes involved in tissue differentiation is a stable tumor mark that is reproducible across experiments and cancer types. Here we show that constructing gene expression signatures based on variability and the anti-profile approach yields classifiers capable of successfully distinguishing benign growths from cancerous growths based on deviation from normal expression. We then show that this same approach generates stable and reproducible signatures that predict probability of relapse and survival based on tumor gene expression. These results suggest that using the anti-profile framework for the discovery of genomic signatures is an avenue leading to the development of reproducible signatures suitable for adoption in clinical settings. PMID:26078586

Sequencing Needs for Viral Diagnostics

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

Gardner, S N; Lam, M; Mulakken, N J

2004-01-26

We built a system to guide decisions regarding the amount of genomic sequencing required to develop diagnostic DNA signatures, which are short sequences that are sufficient to uniquely identify a viral species. We used our existing DNA diagnostic signature prediction pipeline, which selects regions of a target species genome that are conserved among strains of the target (for reliability, to prevent false negatives) and unique relative to other species (for specificity, to avoid false positives). We performed simulations, based on existing sequence data, to assess the number of genome sequences of a target species and of close phylogenetic relatives (''nearmore » neighbors'') that are required to predict diagnostic signature regions that are conserved among strains of the target species and unique relative to other bacterial and viral species. For DNA viruses such as variola (smallpox), three target genomes provide sufficient guidance for selecting species-wide signatures. Three near neighbor genomes are critical for species specificity. In contrast, most RNA viruses require four target genomes and no near neighbor genomes, since lack of conservation among strains is more limiting than uniqueness. SARS and Ebola Zaire are exceptional, as additional target genomes currently do not improve predictions, but near neighbor sequences are urgently needed. Our results also indicate that double stranded DNA viruses are more conserved among strains than are RNA viruses, since in most cases there was at least one conserved signature candidate for the DNA viruses and zero conserved signature candidates for the RNA viruses.« less

A peripheral blood transcriptomic signature predicts autoantibody development in infants at risk of type 1 diabetes.

PubMed

Mehdi, Ahmed M; Hamilton-Williams, Emma E; Cristino, Alexandre; Ziegler, Anette; Bonifacio, Ezio; Le Cao, Kim-Anh; Harris, Mark; Thomas, Ranjeny

2018-03-08

Autoimmune-mediated destruction of pancreatic islet β cells results in type 1 diabetes (T1D). Serum islet autoantibodies usually develop in genetically susceptible individuals in early childhood before T1D onset, with multiple islet autoantibodies predicting diabetes development. However, most at-risk children remain islet-antibody negative, and no test currently identifies those likely to seroconvert. We sought a genomic signature predicting seroconversion risk by integrating longitudinal peripheral blood gene expression profiles collected in high-risk children included in the BABYDIET and DIPP cohorts, of whom 50 seroconverted. Subjects were followed for 10 years to determine time of seroconversion. Any cohort effect and the time of seroconversion were corrected to uncover genes differentially expressed (DE) in seroconverting children. Gene expression signatures associated with seroconversion were evident during the first year of life, with 67 DE genes identified in seroconverting children relative to those remaining antibody negative. These genes contribute to T cell-, DC-, and B cell-related immune responses. Near-birth expression of ADCY9, PTCH1, MEX3B, IL15RA, ZNF714, TENM1, and PLEKHA5, along with HLA risk score predicted seroconversion (AUC 0.85). The ubiquitin-proteasome pathway linked DE genes and T1D susceptibility genes. Therefore, a gene expression signature in infancy predicts risk of seroconversion. Ubiquitination may play a mechanistic role in diabetes progression.

A peripheral blood transcriptomic signature predicts autoantibody development in infants at risk of type 1 diabetes

PubMed Central

Mehdi, Ahmed M.; Hamilton-Williams, Emma E.; Cristino, Alexandre; Ziegler, Anette; Harris, Mark

2018-01-01

Autoimmune-mediated destruction of pancreatic islet β cells results in type 1 diabetes (T1D). Serum islet autoantibodies usually develop in genetically susceptible individuals in early childhood before T1D onset, with multiple islet autoantibodies predicting diabetes development. However, most at-risk children remain islet-antibody negative, and no test currently identifies those likely to seroconvert. We sought a genomic signature predicting seroconversion risk by integrating longitudinal peripheral blood gene expression profiles collected in high-risk children included in the BABYDIET and DIPP cohorts, of whom 50 seroconverted. Subjects were followed for 10 years to determine time of seroconversion. Any cohort effect and the time of seroconversion were corrected to uncover genes differentially expressed (DE) in seroconverting children. Gene expression signatures associated with seroconversion were evident during the first year of life, with 67 DE genes identified in seroconverting children relative to those remaining antibody negative. These genes contribute to T cell–, DC-, and B cell–related immune responses. Near-birth expression of ADCY9, PTCH1, MEX3B, IL15RA, ZNF714, TENM1, and PLEKHA5, along with HLA risk score predicted seroconversion (AUC 0.85). The ubiquitin-proteasome pathway linked DE genes and T1D susceptibility genes. Therefore, a gene expression signature in infancy predicts risk of seroconversion. Ubiquitination may play a mechanistic role in diabetes progression. PMID:29515040

BlackMax: A black-hole event generator with rotation, recoil, split branes, and brane tension

NASA Astrophysics Data System (ADS)

Dai, De-Chang; Starkman, Glenn; Stojkovic, Dejan; Issever, Cigdem; Rizvi, Eram; Tseng, Jeff

2008-04-01

We present a comprehensive black-hole event generator, BlackMax, which simulates the experimental signatures of microscopic and Planckian black-hole production and evolution at the LHC in the context of brane world models with low-scale quantum gravity. The generator is based on phenomenologically realistic models free of serious problems that plague low-scale gravity, thus offering more realistic predictions for hadron-hadron colliders. The generator includes all of the black-hole gray-body factors known to date and incorporates the effects of black-hole rotation, splitting between the fermions, nonzero brane tension, and black-hole recoil due to Hawking radiation (although not all simultaneously). The generator can be interfaced with Herwig and Pythia. The main code can be downloaded from http://www-pnp.physics.ox.ac.uk/~issever/BlackMax/blackmax.html.

Vector Adaptive/Predictive Encoding Of Speech

NASA Technical Reports Server (NTRS)

Chen, Juin-Hwey; Gersho, Allen

1989-01-01

Vector adaptive/predictive technique for digital encoding of speech signals yields decoded speech of very good quality after transmission at coding rate of 9.6 kb/s and of reasonably good quality at 4.8 kb/s. Requires 3 to 4 million multiplications and additions per second. Combines advantages of adaptive/predictive coding, and code-excited linear prediction, yielding speech of high quality but requires 600 million multiplications and additions per second at encoding rate of 4.8 kb/s. Vector adaptive/predictive coding technique bridges gaps in performance and complexity between adaptive/predictive coding and code-excited linear prediction.

Transmitted/Founder HIV-1 Subtype C Viruses Show Distinctive Signature Patterns in Vif, Vpr, and Vpu That Are Under Subsequent Immune Pressure During Early Infection.

PubMed

Rossenkhan, Raabya; MacLeod, Iain J; Brumme, Zabrina L; Magaret, Craig A; Sebunya, Theresa K; Musonda, Rosemary; Gashe, Berhanu A; Edlefsen, Paul T; Novitsky, Vlad; Essex, M

Viral variants that predominate during early infection may exhibit constrained diversity compared with those found during chronic infection and could contain amino acid signature patterns that may enhance transmission, establish productive infection, and influence early events that modulate the infection course. We compared amino acid distributions in 17 patients recently infected with HIV-1C with patients with chronic infection. We found significantly lower entropy in inferred transmitted/founder (t/f) compared with chronic viruses and identified signature patterns in Vif and Vpr from inferred t/f viruses. We investigated sequence evolution longitudinally up to 500 days postseroconversion and compared the impact of selected substitutions on predicted human leukocyte antigen (HLA) binding affinities of published and predicted cytotoxic T-lymphocyte epitopes. Polymorphisms in Vif and Vpr during early infection occurred more frequently at epitope-HLA anchor residues and significantly decreased predicted epitope-HLA binding. Transmission-associated sequence signatures may have implications for novel strategies to prevent HIV-1 transmission.

Transmitted/Founder HIV-1 Subtype C Viruses Show Distinctive Signature Patterns in Vif, Vpr, and Vpu That Are Under Subsequent Immune Pressure During Early Infection

PubMed Central

Rossenkhan, Raabya; MacLeod, Iain J.; Brumme, Zabrina L.; Magaret, Craig A.; Sebunya, Theresa K.; Musonda, Rosemary; Gashe, Berhanu A.; Edlefsen, Paul T.; Novitsky, Vlad

2016-01-01

Abstract Viral variants that predominate during early infection may exhibit constrained diversity compared with those found during chronic infection and could contain amino acid signature patterns that may enhance transmission, establish productive infection, and influence early events that modulate the infection course. We compared amino acid distributions in 17 patients recently infected with HIV-1C with patients with chronic infection. We found significantly lower entropy in inferred transmitted/founder (t/f) compared with chronic viruses and identified signature patterns in Vif and Vpr from inferred t/f viruses. We investigated sequence evolution longitudinally up to 500 days postseroconversion and compared the impact of selected substitutions on predicted human leukocyte antigen (HLA) binding affinities of published and predicted cytotoxic T-lymphocyte epitopes. Polymorphisms in Vif and Vpr during early infection occurred more frequently at epitope-HLA anchor residues and significantly decreased predicted epitope-HLA binding. Transmission-associated sequence signatures may have implications for novel strategies to prevent HIV-1 transmission. PMID:27349335

A genomic biomarker signature can predict skin sensitizers using a cell-based in vitro alternative to animal tests

PubMed Central

2011-01-01

Background Allergic contact dermatitis is an inflammatory skin disease that affects a significant proportion of the population. This disease is caused by an adverse immune response towards chemical haptens, and leads to a substantial economic burden for society. Current test of sensitizing chemicals rely on animal experimentation. New legislations on the registration and use of chemicals within pharmaceutical and cosmetic industries have stimulated significant research efforts to develop alternative, human cell-based assays for the prediction of sensitization. The aim is to replace animal experiments with in vitro tests displaying a higher predictive power. Results We have developed a novel cell-based assay for the prediction of sensitizing chemicals. By analyzing the transcriptome of the human cell line MUTZ-3 after 24 h stimulation, using 20 different sensitizing chemicals, 20 non-sensitizing chemicals and vehicle controls, we have identified a biomarker signature of 200 genes with potent discriminatory ability. Using a Support Vector Machine for supervised classification, the prediction performance of the assay revealed an area under the ROC curve of 0.98. In addition, categorizing the chemicals according to the LLNA assay, this gene signature could also predict sensitizing potency. The identified markers are involved in biological pathways with immunological relevant functions, which can shed light on the process of human sensitization. Conclusions A gene signature predicting sensitization, using a human cell line in vitro, has been identified. This simple and robust cell-based assay has the potential to completely replace or drastically reduce the utilization of test systems based on experimental animals. Being based on human biology, the assay is proposed to be more accurate for predicting sensitization in humans, than the traditional animal-based tests. PMID:21824406

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

Genomic signatures characterize leukocyte infiltration in myositis muscles.

PubMed

Zhu, Wei; Streicher, Katie; Shen, Nan; Higgs, Brandon W; Morehouse, Chris; Greenlees, Lydia; Amato, Anthony A; Ranade, Koustubh; Richman, Laura; Fiorentino, David; Jallal, Bahija; Greenberg, Steven A; Yao, Yihong

2012-11-21

Leukocyte infiltration plays an important role in the pathogenesis and progression of myositis, and is highly associated with disease severity. Currently, there is a lack of: efficacious therapies for myositis; understanding of the molecular features important for disease pathogenesis; and potential molecular biomarkers for characterizing inflammatory myopathies to aid in clinical development. In this study, we developed a simple model and predicted that 1) leukocyte-specific transcripts (including both protein-coding transcripts and microRNAs) should be coherently overexpressed in myositis muscle and 2) the level of over-expression of these transcripts should be correlated with leukocyte infiltration. We applied this model to assess immune cell infiltration in myositis by examining mRNA and microRNA (miRNA) expression profiles in muscle biopsies from 31 myositis patients and 5 normal controls. Several gene signatures, including a leukocyte index, type 1 interferon (IFN), MHC class I, and immunoglobulin signature, were developed to characterize myositis patients at the molecular level. The leukocyte index, consisting of genes predominantly associated with immune function, displayed strong concordance with pathological assessment of immune cell infiltration. This leukocyte index was subsequently utilized to differentiate transcriptional changes due to leukocyte infiltration from other alterations in myositis muscle. Results from this differentiation revealed biologically relevant differences in the relationship between the type 1 IFN pathway, miR-146a, and leukocyte infiltration within various myositis subtypes. Results indicate that a likely interaction between miR-146a expression and the type 1 IFN pathway is confounded by the level of leukocyte infiltration into muscle tissue. Although the role of miR-146a in myositis remains uncertain, our results highlight the potential benefit of deconvoluting the source of transcriptional changes in myositis muscle or other heterogeneous tissue samples. Taken together, the leukocyte index and other gene signatures developed in this study may be potential molecular biomarkers to help to further characterize inflammatory myopathies and aid in clinical development. These hypotheses need to be confirmed in separate and sufficiently powered clinical trials.

Numerical simulation and validation of helicopter blade-vortex interaction using coupled CFD/CSD and three levels of aerodynamic modeling

NASA Astrophysics Data System (ADS)

Amiraux, Mathieu

Rotorcraft Blade-Vortex Interaction (BVI) remains one of the most challenging flow phenomenon to simulate numerically. Over the past decade, the HART-II rotor test and its extensive experimental dataset has been a major database for validation of CFD codes. Its strong BVI signature, with high levels of intrusive noise and vibrations, makes it a difficult test for computational methods. The main challenge is to accurately capture and preserve the vortices which interact with the rotor, while predicting correct blade deformations and loading. This doctoral dissertation presents the application of a coupled CFD/CSD methodology to the problem of helicopter BVI and compares three levels of fidelity for aerodynamic modeling: a hybrid lifting-line/free-wake (wake coupling) method, with modified compressible unsteady model; a hybrid URANS/free-wake method; and a URANS-based wake capturing method, using multiple overset meshes to capture the entire flow field. To further increase numerical correlation, three helicopter fuselage models are implemented in the framework. The first is a high resolution 3D GPU panel code; the second is an immersed boundary based method, with 3D elliptic grid adaption; the last one uses a body-fitted, curvilinear fuselage mesh. The main contribution of this work is the implementation and systematic comparison of multiple numerical methods to perform BVI modeling. The trade-offs between solution accuracy and computational cost are highlighted for the different approaches. Various improvements have been made to each code to enhance physical fidelity, while advanced technologies, such as GPU computing, have been employed to increase efficiency. The resulting numerical setup covers all aspects of the simulation creating a truly multi-fidelity and multi-physics framework. Overall, the wake capturing approach showed the best BVI phasing correlation and good blade deflection predictions, with slightly under-predicted aerodynamic loading magnitudes. However, it proved to be much more expensive than the other two methods. Wake coupling with RANS solver had very good loading magnitude predictions, and therefore good acoustic intensities, with acceptable computational cost. The lifting-line based technique often had over-predicted aerodynamic levels, due to the degree of empiricism of the model, but its very short run-times, thanks to GPU technology, makes it a very attractive approach.

NF-κB gene signature predicts prostate cancer progression

PubMed Central

Jin, Renjie; Yi, Yajun; Yull, Fiona E.; Blackwell, Timothy S.; Clark, Peter E.; Koyama, Tatsuki; Smith, Joseph A.; Matusik, Robert J.

2014-01-01

In many prostate cancer (PCa) patients, the cancer will be recurrent and eventually progress to lethal metastatic disease after primary treatment, such as surgery or radiation therapy. Therefore, it would be beneficial to better predict which patients with early-stage PCa would progress or recur after primary definitive treatment. In addition, many studies indicate that activation of NF-κB signaling correlates with PCa progression; however, the precise underlying mechanism is not fully understood. Our studies show that activation of NF-κB signaling via deletion of one allele of its inhibitor, IκBα, did not induce prostatic tumorigenesis in our mouse model. However, activation of NF-κB signaling did increase the rate of tumor progression in the Hi-Myc mouse PCa model when compared to Hi-Myc alone. Using the non-malignant NF-κB activated androgen depleted mouse prostate, a NF-κB Activated Recurrence Predictor 21 (NARP21) gene signature was generated. The NARP21 signature successfully predicted disease-specific survival and distant metastases-free survival in patients with PCa. This transgenic mouse model derived gene signature provides a useful and unique molecular profile for human PCa prognosis, which could be used on a prostatic biopsy to predict indolent versus aggressive behavior of the cancer after surgery. PMID:24686169

Numerical investigation and Uncertainty Quantification of the Impact of the geological and geomechanical properties on the seismo-acoustic responses of underground chemical explosions

NASA Astrophysics Data System (ADS)

Ezzedine, S. M.; Pitarka, A.; Vorobiev, O.; Glenn, L.; Antoun, T.

2017-12-01

We have performed three-dimensional high resolution simulations of underground chemical explosions conducted recently in jointed rock outcrop as part of the Source Physics Experiments (SPE) being conducted at the Nevada National Security Site (NNSS). The main goal of the current study is to investigate the effects of the structural and geomechanical properties on the spall phenomena due to underground chemical explosions and its subsequent effect on the seismo-acoustic signature at far distances. Two parametric studies have been undertaken to assess the impact of different 1) conceptual geological models including a single layer and two layers model, with and without joints and with and without varying geomechanical properties, and 2) depth of bursts of the chemical explosions and explosion yields. Through these investigations we have explored not only the near-field response of the chemical explosions but also the far-field responses of the seismic and the acoustic signatures. The near-field simulations were conducted using the Eulerian and Lagrangian codes, GEODYN and GEODYN -L, respectively, while the far-field seismic simulations were conducted using the elastic wave propagation code, WPP, and the acoustic response using the Kirchhoff-Helmholtz-Rayleigh time-dependent approximation code, KHR. Though a series of simulations we have recorded the velocity field histories a) at the ground surface on an acoustic-source-patch for the acoustic simulations, and 2) on a seismic-source-box for the seismic simulations. We first analyzed the SPE3 experimental data and simulated results, then simulated SPE4-prime, SPE5, and SPE6 to anticipate their seismo-acoustic responses given conditions of uncertainties. SPE experiments were conducted in a granitic formation; we have extended the parametric study to include other geological settings such dolomite and alluvial formations. These parametric studies enabled us 1) investigating the geotechnical and geophysical key parameters that impact the seismo-acoustic responses of underground chemical explosions and 2) deciphering and ranking through a global sensitivity analysis the most important key parameters to be characterized on site to minimize uncertainties in prediction and discrimination.

The bioenergetic signature of isogenic colon cancer cells predicts the cell death response to treatment with 3-bromopyruvate, iodoacetate or 5-fluorouracil.

PubMed

Sánchez-Aragó, María; Cuezva, José M

2011-02-08

Metabolic reprogramming resulting in enhanced glycolysis is a phenotypic trait of cancer cells, which is imposed by the tumor microenvironment and is linked to the down-regulation of the catalytic subunit of the mitochondrial H+-ATPase (β-F1-ATPase). The bioenergetic signature is a protein ratio (β-F1-ATPase/GAPDH), which provides an estimate of glucose metabolism in tumors and serves as a prognostic indicator for cancer patients. Targeting energetic metabolism could be a viable alternative to conventional anticancer chemotherapies. Herein, we document that the bioenergetic signature of isogenic colon cancer cells provides a gauge to predict the cell-death response to the metabolic inhibitors, 3-bromopyruvate (3BrP) and iodoacetate (IA), and the anti-metabolite, 5-fluorouracil (5-FU). The bioenergetic signature of the cells was determined by western blotting. Aerobic glycolysis was determined from lactate production rates. The cell death was analyzed by fluorescence microscopy and flow cytometry. Cellular ATP concentrations were determined using bioluminiscence. Pearson's correlation coefficient was applied to assess the relationship between the bioenergetic signature and the cell death response. In vivo tumor regression activities of the compounds were assessed using a xenograft mouse model injected with the highly glycolytic HCT116 colocarcinoma cells. We demonstrate that the bioenergetic signature of isogenic HCT116 cancer cells inversely correlates with the potential to execute necrosis in response to 3BrP or IA treatment. Conversely, the bioenergetic signature directly correlates with the potential to execute apoptosis in response to 5-FU treatment in the same cells. However, despite the large differences observed in the in vitro cell-death responses associated with 3BrP, IA and 5-FU, the in vivo tumor regression activities of these agents were comparable. Overall, we suggest that the determination of the bioenergetic signature of colon carcinomas could provide a tool for predicting the therapeutic response to various chemotherapeutic strategies aimed at combating tumor progression.

An FDA Perspective on the Regulatory Implications of Complex Signatures to Predict Response to Targeted Therapies

PubMed Central

Beaver, Julia A.; Tzou, Abraham; Blumenthal, Gideon M.; McKee, Amy E.; Kim, Geoffrey; Pazdur, Richard; Philip, Reena

2016-01-01

As technologies evolve, and diagnostics move from detection of single biomarkers toward complex signatures, an increase in the clinical use and regulatory submission of complex signatures is anticipated. However, to date, no complex signatures have been approved as companion diagnostics. In this article, we will describe the potential benefit of complex signatures and their unique regulatory challenges including analytical performance validation, complex signature simulation, and clinical performance evaluation. We also will review the potential regulatory pathways for clearance, approval, or acceptance of complex signatures by the U.S. Food and Drug Administration (FDA). These regulatory pathways include regulations applicable to in vitro diagnostic devices, including companion diagnostic devices, the potential for labeling as a complementary diagnostic, and the biomarker qualification program. PMID:27993967

Simulated GOLD Observations of Atmospheric Waves

NASA Astrophysics Data System (ADS)

Correira, J.; Evans, J. S.; Lumpe, J. D.; Rusch, D. W.; Chandran, A.; Eastes, R.; Codrescu, M.

2016-12-01

The Global-scale Observations of the Limb and Disk (GOLD) mission will measure structures in the Earth's airglow layer due to dynamical forcing by vertically and horizontally propagating waves. These measurements focus on global-scale structures, including compositional and temperature responses resulting from dynamical forcing. Daytime observations of far-UV emissions by GOLD will be used to generate two-dimensional maps of the ratio of atomic oxygen and molecular nitrogen column densities (ΣO/N2 ) as well as neutral temperature that provide signatures of large-scale spatial structure. In this presentation, we use simulations to demonstrate GOLD's capability to deduce periodicities and spatial dimensions of large-scale waves from the spatial and temporal evolution observed in composition and temperature maps. Our simulations include sophisticated forward modeling of the upper atmospheric airglow that properly accounts for anisotropy in neutral and ion composition, temperature, and solar illumination. Neutral densities and temperatures used in the simulations are obtained from global circulation and climatology models that have been perturbed by propagating waves with a range of amplitudes, periods, and sources of excitation. Modeling of airglow emission and predictions of ΣO/N2 and neutral temperatures are performed with the Atmospheric Ultraviolet Radiance Integrated Code (AURIC) and associated derived product algorithms. Predicted structure in ΣO/N2 and neutral temperature due to dynamical forcing by propagating waves is compared to existing observations. Realistic GOLD Level 2 data products are generated from simulated airglow emission using algorithm code that will be implemented operationally at the GOLD Science Data Center.

Chromatin-bound RNA and the neurobiology of psychiatric disease.

PubMed

Tushir, J S; Akbarian, S

2014-04-04

A large, and still rapidly expanding literature on epigenetic regulation in the nervous system has provided fundamental insights into the dynamic regulation of DNA methylation and post-translational histone modifications in the context of neuronal plasticity in health and disease. Remarkably, however, very little is known about the potential role of chromatin-bound RNAs, including many long non-coding transcripts and various types of small RNAs. Here, we provide an overview on RNA-mediated regulation of chromatin structure and function, with focus on histone lysine methylation and psychiatric disease. Examples of recently discovered chromatin-bound long non-coding RNAs important for neuronal health and function include the brain-derived neurotrophic factor antisense transcript (Bdnf-AS) which regulates expression of the corresponding sense transcript, and LOC389023 which is associated with human-specific histone methylation signatures at the chromosome 2q14.1 neurodevelopmental risk locus by regulating expression of DPP10, an auxillary subunit for voltage-gated K(+) channels. We predict that the exploration of chromatin-bound RNA will significantly advance our current knowledge base in neuroepigenetics and biological psychiatry. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

Connection anonymity analysis in coded-WDM PONs

NASA Astrophysics Data System (ADS)

Sue, Chuan-Ching

2008-04-01

A coded wavelength division multiplexing passive optical network (WDM PON) is presented for fiber to the home (FTTH) systems to protect against eavesdropping. The proposed scheme applies spectral amplitude coding (SAC) with a unipolar maximal-length sequence (M-sequence) code matrix to generate a specific signature address (coding) and to retrieve its matching address codeword (decoding) by exploiting the cyclic properties inherent in array waveguide grating (AWG) routers. In addition to ensuring the confidentiality of user data, the proposed coded-WDM scheme is also a suitable candidate for the physical layer with connection anonymity. Under the assumption that the eavesdropper applies a photo-detection strategy, it is shown that the coded WDM PON outperforms the conventional TDM PON and WDM PON schemes in terms of a higher degree of connection anonymity. Additionally, the proposed scheme allows the system operator to partition the optical network units (ONUs) into appropriate groups so as to achieve a better degree of anonymity.

Predicting Zoonotic Risk of Influenza A Viruses from Host Tropism Protein Signature Using Random Forest

PubMed Central

Eng, Christine L. P.; Tong, Joo Chuan; Tan, Tin Wee

2017-01-01

Influenza A viruses remain a significant health problem, especially when a novel subtype emerges from the avian population to cause severe outbreaks in humans. Zoonotic viruses arise from the animal population as a result of mutations and reassortments, giving rise to novel strains with the capability to evade the host species barrier and cause human infections. Despite progress in understanding interspecies transmission of influenza viruses, we are no closer to predicting zoonotic strains that can lead to an outbreak. We have previously discovered distinct host tropism protein signatures of avian, human and zoonotic influenza strains obtained from host tropism predictions on individual protein sequences. Here, we apply machine learning approaches on the signatures to build a computational model capable of predicting zoonotic strains. The zoonotic strain prediction model can classify avian, human or zoonotic strains with high accuracy, as well as providing an estimated zoonotic risk. This would therefore allow us to quickly determine if an influenza virus strain has the potential to be zoonotic using only protein sequences. The swift identification of potential zoonotic strains in the animal population using the zoonotic strain prediction model could provide us with an early indication of an imminent influenza outbreak. PMID:28587080

Predicting Zoonotic Risk of Influenza A Viruses from Host Tropism Protein Signature Using Random Forest.

PubMed

Eng, Christine L P; Tong, Joo Chuan; Tan, Tin Wee

2017-05-25

Influenza A viruses remain a significant health problem, especially when a novel subtype emerges from the avian population to cause severe outbreaks in humans. Zoonotic viruses arise from the animal population as a result of mutations and reassortments, giving rise to novel strains with the capability to evade the host species barrier and cause human infections. Despite progress in understanding interspecies transmission of influenza viruses, we are no closer to predicting zoonotic strains that can lead to an outbreak. We have previously discovered distinct host tropism protein signatures of avian, human and zoonotic influenza strains obtained from host tropism predictions on individual protein sequences. Here, we apply machine learning approaches on the signatures to build a computational model capable of predicting zoonotic strains. The zoonotic strain prediction model can classify avian, human or zoonotic strains with high accuracy, as well as providing an estimated zoonotic risk. This would therefore allow us to quickly determine if an influenza virus strain has the potential to be zoonotic using only protein sequences. The swift identification of potential zoonotic strains in the animal population using the zoonotic strain prediction model could provide us with an early indication of an imminent influenza outbreak.

Signatures of selection in tilapia revealed by whole genome resequencing.

PubMed

Xia, Jun Hong; Bai, Zhiyi; Meng, Zining; Zhang, Yong; Wang, Le; Liu, Feng; Jing, Wu; Wan, Zi Yi; Li, Jiale; Lin, Haoran; Yue, Gen Hua

2015-09-16

Natural selection and selective breeding for genetic improvement have left detectable signatures within the genome of a species. Identification of selection signatures is important in evolutionary biology and for detecting genes that facilitate to accelerate genetic improvement. However, selection signatures, including artificial selection and natural selection, have only been identified at the whole genome level in several genetically improved fish species. Tilapia is one of the most important genetically improved fish species in the world. Using next-generation sequencing, we sequenced the genomes of 47 tilapia individuals. We identified a total of 1.43 million high-quality SNPs and found that the LD block sizes ranged from 10-100 kb in tilapia. We detected over a hundred putative selective sweep regions in each line of tilapia. Most selection signatures were located in non-coding regions of the tilapia genome. The Wnt signaling, gonadotropin-releasing hormone receptor and integrin signaling pathways were under positive selection in all improved tilapia lines. Our study provides a genome-wide map of genetic variation and selection footprints in tilapia, which could be important for genetic studies and accelerating genetic improvement of tilapia.

Cognitive Airborne Networking: Self-Aware Communications via Sensing, Adaptation, and Cross-Layer Optimization

DTIC Science & Technology

2011-03-01

Karystinos and D. A. Pados, “New bounds on the total squared correlation and optimum design of DS - CDMA binary signature sets,” IEEE Trans. Commun...vol. 51, pp. 48-51, Jan. 2003. [99] C. Ding, M. Golin, and T. Klφve, “Meeting the Welch and Karystinos-Pados bounds on DS - CDMA binary signature sets...Designs, Codes and Cryptography, vol. 30, pp. 73-84, Aug. 2003. [100] V. P. Ipatov, “On the Karystinos-Pados bounds and optimal binary DS - CDMA

Direct modeling parameter signature analysis and failure mode prediction of physical systems using hybrid computer optimization

NASA Technical Reports Server (NTRS)

Drake, R. L.; Duvoisin, P. F.; Asthana, A.; Mather, T. W.

1971-01-01

High speed automated identification and design of dynamic systems, both linear and nonlinear, are discussed. Special emphasis is placed on developing hardware and techniques which are applicable to practical problems. The basic modeling experiment and new results are described. Using the improvements developed successful identification of several systems, including a physical example as well as simulated systems, was obtained. The advantages of parameter signature analysis over signal signature analysis in go-no go testing of operational systems were demonstrated. The feasibility of using these ideas in failure mode prediction in operating systems was also investigated. An improved digital controlled nonlinear function generator was developed, de-bugged, and completely documented.

Molecular Signature for Lymphatic Invasion Associated with Survival of Epithelial Ovarian Cancer.

PubMed

Paik, E Sun; Choi, Hyun Jin; Kim, Tae-Joong; Lee, Jeong-Won; Kim, Byoung-Gie; Bae, Duk-Soo; Choi, Chel Hun

2018-04-01

We aimed to develop molecular classifier that can predict lymphatic invasion and their clinical significance in epithelial ovarian cancer (EOC) patients. We analyzed gene expression (mRNA, methylated DNA) in data from The Cancer Genome Atlas. To identify molecular signatures for lymphatic invasion, we found differentially expressed genes. The performance of classifier was validated by receiver operating characteristics analysis, logistic regression, linear discriminant analysis (LDA), and support vector machine (SVM). We assessed prognostic role of classifier using random survival forest (RSF) model and pathway deregulation score (PDS). For external validation,we analyzed microarray data from 26 EOC samples of Samsung Medical Center and curatedOvarianData database. We identified 21 mRNAs, and seven methylated DNAs from primary EOC tissues that predicted lymphatic invasion and created prognostic models. The classifier predicted lymphatic invasion well, which was validated by logistic regression, LDA, and SVM algorithm (C-index of 0.90, 0.71, and 0.74 for mRNA and C-index of 0.64, 0.68, and 0.69 for DNA methylation). Using RSF model, incorporating molecular data with clinical variables improved prediction of progression-free survival compared with using only clinical variables (p < 0.001 and p=0.008). Similarly, PDS enabled us to classify patients into high-risk and low-risk group, which resulted in survival difference in mRNA profiles (log-rank p-value=0.011). In external validation, gene signature was well correlated with prediction of lymphatic invasion and patients' survival. Molecular signature model predicting lymphatic invasion was well performed and also associated with survival of EOC patients.

A 16-Gene Signature Distinguishes Anaplastic Astrocytoma from Glioblastoma

PubMed Central

Rao, Soumya Alige Mahabala; Srinivasan, Sujaya; Patric, Irene Rosita Pia; Hegde, Alangar Sathyaranjandas; Chandramouli, Bangalore Ashwathnarayanara; Arimappamagan, Arivazhagan; Santosh, Vani; Kondaiah, Paturu; Rao, Manchanahalli R. Sathyanarayana; Somasundaram, Kumaravel

2014-01-01

Anaplastic astrocytoma (AA; Grade III) and glioblastoma (GBM; Grade IV) are diffusely infiltrating tumors and are called malignant astrocytomas. The treatment regimen and prognosis are distinctly different between anaplastic astrocytoma and glioblastoma patients. Although histopathology based current grading system is well accepted and largely reproducible, intratumoral histologic variations often lead to difficulties in classification of malignant astrocytoma samples. In order to obtain a more robust molecular classifier, we analysed RT-qPCR expression data of 175 differentially regulated genes across astrocytoma using Prediction Analysis of Microarrays (PAM) and found the most discriminatory 16-gene expression signature for the classification of anaplastic astrocytoma and glioblastoma. The 16-gene signature obtained in the training set was validated in the test set with diagnostic accuracy of 89%. Additionally, validation of the 16-gene signature in multiple independent cohorts revealed that the signature predicted anaplastic astrocytoma and glioblastoma samples with accuracy rates of 99%, 88%, and 92% in TCGA, GSE1993 and GSE4422 datasets, respectively. The protein-protein interaction network and pathway analysis suggested that the 16-genes of the signature identified epithelial-mesenchymal transition (EMT) pathway as the most differentially regulated pathway in glioblastoma compared to anaplastic astrocytoma. In addition to identifying 16 gene classification signature, we also demonstrated that genes involved in epithelial-mesenchymal transition may play an important role in distinguishing glioblastoma from anaplastic astrocytoma. PMID:24475040

A PRIM approach to predictive-signature development for patient stratification

PubMed Central

Chen, Gong; Zhong, Hua; Belousov, Anton; Devanarayan, Viswanath

2015-01-01

Patients often respond differently to a treatment because of individual heterogeneity. Failures of clinical trials can be substantially reduced if, prior to an investigational treatment, patients are stratified into responders and nonresponders based on biological or demographic characteristics. These characteristics are captured by a predictive signature. In this paper, we propose a procedure to search for predictive signatures based on the approach of patient rule induction method. Specifically, we discuss selection of a proper objective function for the search, present its algorithm, and describe a resampling scheme that can enhance search performance. Through simulations, we characterize conditions under which the procedure works well. To demonstrate practical uses of the procedure, we apply it to two real-world data sets. We also compare the results with those obtained from a recent regression-based approach, Adaptive Index Models, and discuss their respective advantages. In this study, we focus on oncology applications with survival responses. PMID:25345685

Specific expression of novel long non-coding RNAs in high-hyperdiploid childhood acute lymphoblastic leukemia

PubMed Central

Drouin, Simon; Caron, Maxime; St-Onge, Pascal; Gioia, Romain; Richer, Chantal; Oualkacha, Karim; Droit, Arnaud; Sinnett, Daniel

2017-01-01

Pre-B cell childhood acute lymphoblastic leukemia (pre-B cALL) is a heterogeneous disease involving many subtypes typically stratified using a combination of cytogenetic and molecular-based assays. These methods, although widely used, rely on the presence of known chromosomal translocations, which is a limiting factor. There is therefore a need for robust, sensitive, and specific molecular biomarkers unaffected by such limitations that would allow better risk stratification and consequently better clinical outcome. In this study we performed a transcriptome analysis of 56 pre-B cALL patients to identify expression signatures in different subtypes. In both protein-coding and long non-coding RNAs (lncRNA), we identified subtype-specific gene signatures distinguishing pre-B cALL subtypes, particularly in t(12;21) and hyperdiploid cases. The genes up-regulated in pre-B cALL subtypes were enriched in bivalent chromatin marks in their promoters. LncRNAs is a new and under-studied class of transcripts. The subtype-specific nature of lncRNAs suggests they may be suitable clinical biomarkers to guide risk stratification and targeted therapies in pre-B cALL patients. PMID:28346506

Selection signatures in four lignin genes from switchgrass populations divergently selected for in vitro dry matter digestibility

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

Chen, Shiyu; Kaeppler, Shawn M.; Vogel, Kenneth P.

Switchgrass is undergoing development as a dedicated cellulosic bioenergy crop. Fermentation of lignocellulosic biomass to ethanol in a bioenergy system or to volatile fatty acids in a livestock production system is strongly and negatively influenced by lignification of cell walls. This study detects specific loci that exhibit selection signatures across switchgrass breeding populations that differ in in vitro dry matter digestibility (IVDMD), ethanol yield, and lignin concentration. Allele frequency changes in candidate genes were used to detect loci under selection. Out of the 183 polymorphisms identified in the four candidate genes, twenty-five loci in the intron regions and four locimore » in coding regions were found to display a selection signature. All loci in the coding regions are synonymous substitutions. Selection in both directions were observed on polymorphisms that appeared to be under selection. Genetic diversity and linkage disequilibrium within the candidate genes were low. The recurrent divergent selection caused excessive moderate allele frequencies in the cycle 3 reduced lignin population as compared to the base population. As a result, this study provides valuable insight on genetic changes occurring in short-term selection in the polyploid populations, and discovered potential markers for breeding switchgrass with improved biomass quality.« less

Selection signatures in four lignin genes from switchgrass populations divergently selected for in vitro dry matter digestibility

DOE PAGES

Chen, Shiyu; Kaeppler, Shawn M.; Vogel, Kenneth P.; ...

2016-11-28

Switchgrass is undergoing development as a dedicated cellulosic bioenergy crop. Fermentation of lignocellulosic biomass to ethanol in a bioenergy system or to volatile fatty acids in a livestock production system is strongly and negatively influenced by lignification of cell walls. This study detects specific loci that exhibit selection signatures across switchgrass breeding populations that differ in in vitro dry matter digestibility (IVDMD), ethanol yield, and lignin concentration. Allele frequency changes in candidate genes were used to detect loci under selection. Out of the 183 polymorphisms identified in the four candidate genes, twenty-five loci in the intron regions and four locimore » in coding regions were found to display a selection signature. All loci in the coding regions are synonymous substitutions. Selection in both directions were observed on polymorphisms that appeared to be under selection. Genetic diversity and linkage disequilibrium within the candidate genes were low. The recurrent divergent selection caused excessive moderate allele frequencies in the cycle 3 reduced lignin population as compared to the base population. As a result, this study provides valuable insight on genetic changes occurring in short-term selection in the polyploid populations, and discovered potential markers for breeding switchgrass with improved biomass quality.« less

Screening for angiogenic inhibitors in zebrafish to evaluate a predictive model for developmental vascular toxicity.

PubMed

Tal, Tamara; Kilty, Claire; Smith, Andrew; LaLone, Carlie; Kennedy, Brendán; Tennant, Alan; McCollum, Catherine W; Bondesson, Maria; Knudsen, Thomas; Padilla, Stephanie; Kleinstreuer, Nicole

2017-06-01

Chemically-induced vascular toxicity during embryonic development may cause a wide range of adverse effects. To identify putative vascular disrupting chemicals (pVDCs), a predictive pVDC signature was constructed from 124 U.S. EPA ToxCast high-throughput screening (HTS) assays and used to rank 1060 chemicals for their potential to disrupt vascular development. Thirty-seven compounds were selected for targeted testing in transgenic Tg(kdrl:EGFP) and Tg(fli1:EGFP) zebrafish embryos to identify chemicals that impair developmental angiogenesis. We hypothesized that zebrafish angiogenesis toxicity data would correlate with human cell-based and cell-free in vitro HTS ToxCast data. Univariate statistical associations used to filter HTS data based on correlations with zebrafish angiogenic inhibition in vivo revealed 132 total significant associations, 33 of which were already captured in the pVDC signature, and 689 non-significant assay associations. Correlated assays were enriched in cytokine and extracellular matrix pathways. Taken together, the findings indicate the utility of zebrafish assays to evaluate an HTS-based predictive toxicity signature and also provide an experimental basis for expansion of the pVDC signature with novel HTS assays. Published by Elsevier Inc.

A VEGF-dependent gene signature enriched in mesenchymal ovarian cancer predicts patient prognosis.

PubMed

Yin, Xia; Wang, Xiaojie; Shen, Boqiang; Jing, Ying; Li, Qing; Cai, Mei-Chun; Gu, Zhuowei; Yang, Qi; Zhang, Zhenfeng; Liu, Jin; Li, Hongxia; Di, Wen; Zhuang, Guanglei

2016-08-08

We have previously reported surrogate biomarkers of VEGF pathway activities with the potential to provide predictive information for anti-VEGF therapies. The aim of this study was to systematically evaluate a new VEGF-dependent gene signature (VDGs) in relation to molecular subtypes of ovarian cancer and patient prognosis. Using microarray profiling and cross-species analysis, we identified 140-gene mouse VDGs and corresponding 139-gene human VDGs, which displayed enrichment of vasculature and basement membrane genes. In patients who received bevacizumab therapy and showed partial response, the expressions of VDGs (summarized to yield VDGs scores) were markedly decreased in post-treatment biopsies compared with pre-treatment baselines. In contrast, VDGs scores were not significantly altered following bevacizumab treatment in patients with stable or progressive disease. Analysis of VDGs in ovarian cancer showed that VDGs as a prognostic signature was able to predict patient outcome. Correlation estimation of VDGs scores and molecular features revealed that VDGs was overrepresented in mesenchymal subtype and BRCA mutation carriers. These findings highlighted the prognostic role of VEGF-mediated angiogenesis in ovarian cancer, and proposed a VEGF-dependent gene signature as a molecular basis for developing novel diagnostic strategies to aid patient selection for VEGF-targeted agents.

Spatial and Temporal Signatures of Flux Transfer Events in Global Simulations of Magnetopause Dynamics

NASA Technical Reports Server (NTRS)

Kuznetsova, Maria M.; Sibeck, David Gary; Hesse, Michael; Berrios, David; Rastaetter, Lutz; Toth, Gabor; Gombosi, Tamas I.

2011-01-01

Flux transfer events (FTEs) were originally identified by transient bipolar variations of the magnetic field component normal to the nominal magnetopause centered on enhancements in the total magnetic field strength. Recent Cluster and THEMIS multi-point measurements provided a wide range of signatures that are interpreted as evidence for FTE passage (e.g., crater FTE's, traveling magnetic erosion regions). We use the global magnetohydrodynamic (MHD) code BATS-R-US developed at the University of Michigan to model the global three-dimensional structure and temporal evolution of FTEs during multi-spacecraft magnetopause crossing events. Comparison of observed and simulated signatures and sensitivity analysis of the results to the probe location will be presented. We will demonstrate a variety of observable signatures in magnetic field profile that depend on space probe location with respect to the FTE passage. The global structure of FTEs will be illustrated using advanced visualization tools developed at the Community Coordinated Modeling Center

With or without you: predictive coding and Bayesian inference in the brain

PubMed Central

Aitchison, Laurence; Lengyel, Máté

2018-01-01

Two theoretical ideas have emerged recently with the ambition to provide a unifying functional explanation of neural population coding and dynamics: predictive coding and Bayesian inference. Here, we describe the two theories and their combination into a single framework: Bayesian predictive coding. We clarify how the two theories can be distinguished, despite sharing core computational concepts and addressing an overlapping set of empirical phenomena. We argue that predictive coding is an algorithmic / representational motif that can serve several different computational goals of which Bayesian inference is but one. Conversely, while Bayesian inference can utilize predictive coding, it can also be realized by a variety of other representations. We critically evaluate the experimental evidence supporting Bayesian predictive coding and discuss how to test it more directly. PMID:28942084

A comparison of machine learning techniques for survival prediction in breast cancer

PubMed Central

2011-01-01

Background The ability to accurately classify cancer patients into risk classes, i.e. to predict the outcome of the pathology on an individual basis, is a key ingredient in making therapeutic decisions. In recent years gene expression data have been successfully used to complement the clinical and histological criteria traditionally used in such prediction. Many "gene expression signatures" have been developed, i.e. sets of genes whose expression values in a tumor can be used to predict the outcome of the pathology. Here we investigate the use of several machine learning techniques to classify breast cancer patients using one of such signatures, the well established 70-gene signature. Results We show that Genetic Programming performs significantly better than Support Vector Machines, Multilayered Perceptrons and Random Forests in classifying patients from the NKI breast cancer dataset, and comparably to the scoring-based method originally proposed by the authors of the 70-gene signature. Furthermore, Genetic Programming is able to perform an automatic feature selection. Conclusions Since the performance of Genetic Programming is likely to be improvable compared to the out-of-the-box approach used here, and given the biological insight potentially provided by the Genetic Programming solutions, we conclude that Genetic Programming methods are worth further investigation as a tool for cancer patient classification based on gene expression data. PMID:21569330

Performance of Trellis Coded 256 QAM super-multicarrier modem VLSI's for SDH interface outage-free digital microwave radio

NASA Astrophysics Data System (ADS)

Aikawa, Satoru; Nakamura, Yasuhisa; Takanashi, Hitoshi

1994-02-01

This paper describes the performance of an outage free SXH (Synchronous Digital Hierarchy) interface 256 QAM modem. An outage free DMR (Digital Microwave Radio) is achieved by a high coding gain trellis coded SPORT QAM and Super Multicarrier modem. A new frame format and its associated circuits connect the outage free modem to the SDH interface. The newly designed VLSI's are key devices for developing the modem. As an overall modem performance, BER (bit error rate) characteristics and equipment signatures are presented. A coding gain of 4.7 dB (at a BER of 10(exp -4)) is obtained using SPORT 256 QAM and Viterbi decoding. This coding gain is realized by trellis coding as well as by increasing of transmission rate. Roll-off factor is decreased to maintain the same frequency occupation and modulation level as ordinary SDH 256 QAM modern.

Simulation of Turbine Tone Noise Generation Using a Turbomachinery Aerodynamics Solver

NASA Technical Reports Server (NTRS)

VanZante, Dale; Envia, Edmane

2010-01-01

As turbofan engine bypass ratios continue to increase, the contribution of the turbine to the engine noise signature is receiving more attention. Understanding the relative importance of the various turbine noise generation mechanisms and the characteristics of the turbine acoustic transmission loss are essential ingredients in developing robust reduced-order models for predicting the turbine noise signature. A computationally based investigation has been undertaken to help guide the development of a turbine noise prediction capability that does not rely on empiricism. As proof-of-concept for this approach, two highly detailed numerical simulations of the unsteady flow field inside the first stage of a modern high-pressure turbine were carried out. The simulations were computed using TURBO, which is an unsteady Reynolds-Averaged Navier-Stokes code capable of multi-stage simulations. Spectral and modal analysis of the unsteady pressure data from the numerical simulation of the turbine stage show a circumferential modal distribution that is consistent with the Tyler-Sofrin rule. Within the high-pressure turbine, the interaction of velocity, pressure and temperature fluctuations with the downstream blade rows are all possible tone noise source mechanisms. We have taken the initial step in determining the source strength hierarchy by artificially reducing the level of temperature fluctuations in the turbine flowfield. This was accomplished by changing the vane cooling flow temperature in order to mitigate the vane thermal wake in the second of the two simulations. The results indicated that, despite a dramatic change in the vane cooling flow, the computed modal levels changed very little indicating that the contribution of temperature fluctuations to the overall pressure field is rather small compared with the viscous and potential field interaction mechanisms.

Signature-forecasting and early outbreak detection system

PubMed Central

Naumova, Elena N.; MacNeill, Ian B.

2008-01-01

SUMMARY Daily disease monitoring via a public health surveillance system provides valuable information on population risks. Efficient statistical tools for early detection of rapid changes in the disease incidence are a must for modern surveillance. The need for statistical tools for early detection of outbreaks that are not based on historical information is apparent. A system is discussed for monitoring cases of infections with a view to early detection of outbreaks and to forecasting the extent of detected outbreaks. We propose a set of adaptive algorithms for early outbreak detection that does not rely on extensive historical recording. We also include knowledge of infection disease epidemiology into forecasts. To demonstrate this system we use data from the largest water-borne outbreak of cryptosporidiosis, which occurred in Milwaukee in 1993. Historical data are smoothed using a loess-type smoother. Upon receipt of a new datum, the smoothing is updated and estimates are made of the first two derivatives of the smooth curve, and these are used for near-term forecasting. Recent data and the near-term forecasts are used to compute a color-coded warning index, which quantify the level of concern. The algorithms for computing the warning index have been designed to balance Type I errors (false prediction of an epidemic) and Type II errors (failure to correctly predict an epidemic). If the warning index signals a sufficiently high probability of an epidemic, then a forecast of the possible size of the outbreak is made. This longer term forecast is made by fitting a ‘signature’ curve to the available data. The effectiveness of the forecast depends upon the extent to which the signature curve captures the shape of outbreaks of the infection under consideration. PMID:18716671

Inference of Heating Properties from "Hot" Non-flaring Plasmas in Active Region Cores. I. Single Nanoflares

NASA Astrophysics Data System (ADS)

Barnes, W. T.; Cargill, P. J.; Bradshaw, S. J.

2016-09-01

The properties that are expected of “hot” non-flaring plasmas due to nanoflare heating in active regions are investigated using hydrodynamic modeling tools, including a two-fluid development of the Enthalpy Based Thermal Evolution of Loops code. Here we study a single nanoflare and show that while simple models predict an emission measure distribution extending well above 10 MK, which is consistent with cooling by thermal conduction, many other effects are likely to limit the existence and detectability of such plasmas. These include: differential heating between electrons and ions, ionization non-equilibrium, and for short nanoflares, the time taken for the coronal density to increase. The most useful temperature range to look for this plasma, often called the “smoking gun” of nanoflare heating, lies between 106.6 and 107 K. Signatures of the actual heating may be detectable in some instances.

"Hot" Non-flaring Plasmas in Active Region Cores Heated by Single Nanoflares

NASA Astrophysics Data System (ADS)

Barnes, Will Thomas; Cargill, Peter; Bradshaw, Stephen

2016-05-01

We use hydrodynamic modeling tools, including a two-fluid development of the EBTEL code, to investigate the properties expected of "hot" (i.e. between 106.7 and 107.2 K) non-flaring plasmas due to nanoflare heating in active regions. Here we focus on single nanoflares and show that while simple models predict an emission measure distribution extending well above 10 MK that is consistent with cooling by thermal conduction, many other effects are likely to limit the existence and detectability of such plasmas. These include: differential heating between electrons and ions, ionization non-equilibrium and, for short nanoflares, the time taken for the coronal density to increase. The most useful temperature range to look for this plasma, often called the "smoking gun" of nanoflare heating, lies between 1 MK and 10 MK. Signatures of the actual heating may be detectable in some instances.

Can microRNAs act as biomarkers of aging?

PubMed Central

Kashyap, Luv

2011-01-01

Aging can be defined as a progressive decline in physiological efficiency regulated by an extremely complex multifactorial process. The genetic makeup of an individual appears to dictate this rate of aging in a species specific manner. For decades now, scientists have tried to look for tiny signatures or signs which might help us predict this rate of aging. MicroRNAs (miRNAs) are a unique class of short, non-coding RNAs that mediate the post-transcriptional regulation of gene expression ranging from developmental processes to disease induction or amelioration. Recently, they have also been implicated to have a role in aging in C.elegans. Based on the fact that there is a considerable similarity between aging in C.elegans and humans, these recent findings might suggest a possible role of miRNAs as bio-markers of aging. This mini-review brushes through the possibilities towards this direction. PMID:21383908

Can microRNAs act as biomarkers of aging?

PubMed

Kashyap, Luv

2011-02-07

Aging can be defined as a progressive decline in physiological efficiency regulated by an extremely complex multifactorial process. The genetic makeup of an individual appears to dictate this rate of aging in a species specific manner. For decades now, scientists have tried to look for tiny signatures or signs which might help us predict this rate of aging. MicroRNAs (miRNAs) are a unique class of short, non-coding RNAs that mediate the post-transcriptional regulation of gene expression ranging from developmental processes to disease induction or amelioration. Recently, they have also been implicated to have a role in aging in C.elegans. Based on the fact that there is a considerable similarity between aging in C.elegans and humans, these recent findings might suggest a possible role of miRNAs as bio-markers of aging. This mini-review brushes through the possibilities towards this direction.

BlackMax: A black-hole event generator with rotation, recoil, split branes, and brane tension

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

Dai Dechang; Starkman, Glenn; Stojkovic, Dejan

2008-04-01

We present a comprehensive black-hole event generator, BlackMax, which simulates the experimental signatures of microscopic and Planckian black-hole production and evolution at the LHC in the context of brane world models with low-scale quantum gravity. The generator is based on phenomenologically realistic models free of serious problems that plague low-scale gravity, thus offering more realistic predictions for hadron-hadron colliders. The generator includes all of the black-hole gray-body factors known to date and incorporates the effects of black-hole rotation, splitting between the fermions, nonzero brane tension, and black-hole recoil due to Hawking radiation (although not all simultaneously). The generator can bemore » interfaced with Herwig and Pythia. The main code can be downloaded from http://www-pnp.physics.ox.ac.uk/{approx}issever/BlackMax/blackmax.html.« less

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

Barnes, W. T.; Bradshaw, S. J.; Cargill, P. J., E-mail: will.t.barnes@rice.edu

The properties that are expected of “hot” non-flaring plasmas due to nanoflare heating in active regions are investigated using hydrodynamic modeling tools, including a two-fluid development of the Enthalpy Based Thermal Evolution of Loops code. Here we study a single nanoflare and show that while simple models predict an emission measure distribution extending well above 10 MK, which is consistent with cooling by thermal conduction, many other effects are likely to limit the existence and detectability of such plasmas. These include: differential heating between electrons and ions, ionization non-equilibrium, and for short nanoflares, the time taken for the coronal densitymore » to increase. The most useful temperature range to look for this plasma, often called the “smoking gun” of nanoflare heating, lies between 10{sup 6.6} and 10{sup 7} K. Signatures of the actual heating may be detectable in some instances.« less

Helicopter Non-Unique Trim Strategies for Blade-Vortex Interaction (BVI) Noise Reduction

NASA Technical Reports Server (NTRS)

Malpica, Carlos; Greenwood, Eric; Sim, Ben W.

2016-01-01

An acoustics parametric analysis of the effect of fuselage drag and pitching moment on the Blade-Vortex Interaction (BVI) noise radiated by a medium lift helicopter (S-70UH-60) in a descending flight condition was conducted. The comprehensive analysis CAMRAD II was used for the calculation of vehicle trim, wake geometry and integrated air loads on the blade. The acoustics prediction code PSU-WOPWOP was used for calculating acoustic pressure signatures for a hemispherical grid centered at the hub. This paper revisits the concept of the X-force controller for BVI noise reduction, and investigates its effectiveness on an S-70 helicopter. The analysis showed that further BVI noise reductions were achievable by controlling the fuselage pitching moment. Reductions in excess of 6 dB of the peak BVI noise radiated towards the ground were demonstrated by compounding the effect of airframe drag and pitching moment simultaneously.

A review of predictive coding algorithms.

PubMed

Spratling, M W

2017-03-01

Predictive coding is a leading theory of how the brain performs probabilistic inference. However, there are a number of distinct algorithms which are described by the term "predictive coding". This article provides a concise review of these different predictive coding algorithms, highlighting their similarities and differences. Five algorithms are covered: linear predictive coding which has a long and influential history in the signal processing literature; the first neuroscience-related application of predictive coding to explaining the function of the retina; and three versions of predictive coding that have been proposed to model cortical function. While all these algorithms aim to fit a generative model to sensory data, they differ in the type of generative model they employ, in the process used to optimise the fit between the model and sensory data, and in the way that they are related to neurobiology. Copyright © 2016 Elsevier Inc. All rights reserved.

Determination of community structure through deconvolution of PLFA-FAME signature of mixed population.

PubMed

Dey, Dipesh K; Guha, Saumyen

2007-02-15

Phospholipid fatty acids (PLFAs) as biomarkers are well established in the literature. A general method based on least square approximation (LSA) was developed for the estimation of community structure from the PLFA signature of a mixed population where biomarker PLFA signatures of the component species were known. Fatty acid methyl ester (FAME) standards were used as species analogs and mixture of the standards as representative of the mixed population. The PLFA/FAME signatures were analyzed by gas chromatographic separation, followed by detection in flame ionization detector (GC-FID). The PLFAs in the signature were quantified as relative weight percent of the total PLFA. The PLFA signatures were analyzed by the models to predict community structure of the mixture. The LSA model results were compared with the existing "functional group" approach. Both successfully predicted community structure of mixed population containing completely unrelated species with uncommon PLFAs. For slightest intersection in PLFA signatures of component species, the LSA model produced better results. This was mainly due to inability of the "functional group" approach to distinguish the relative amounts of the common PLFA coming from more than one species. The performance of the LSA model was influenced by errors in the chromatographic analyses. Suppression (or enhancement) of a component's PLFA signature in chromatographic analysis of the mixture, led to underestimation (or overestimation) of the component's proportion in the mixture by the model. In mixtures of closely related species with common PLFAs, the errors in the common components were adjusted across the species by the model.

A genome-wide signature of positive selection in ancient and recent invasive expansions of the honey bee Apis mellifera

PubMed Central

Zayed, Amro; Whitfield, Charles W.

2008-01-01

Apis mellifera originated in Africa and extended its range into Eurasia in two or more ancient expansions. In 1956, honey bees of African origin were introduced into South America, their descendents admixing with previously introduced European bees, giving rise to the highly invasive and economically devastating “Africanized” honey bee. Here we ask whether the honey bee's out-of-Africa expansions, both ancient and recent (invasive), were associated with a genome-wide signature of positive selection, detected by contrasting genetic differentiation estimates (FST) between coding and noncoding SNPs. In native populations, SNPs in protein-coding regions had significantly higher FST estimates than those in noncoding regions, indicating adaptive evolution in the genome driven by positive selection. This signal of selection was associated with the expansion of honey bees from Africa into Western and Northern Europe, perhaps reflecting adaptation to temperate environments. We estimate that positive selection acted on a minimum of 852–1,371 genes or ≈10% of the bee's coding genome. We also detected positive selection associated with the invasion of African-derived honey bees in the New World. We found that introgression of European-derived alleles into Africanized bees was significantly greater for coding than noncoding regions. Our findings demonstrate that Africanized bees exploited the genetic diversity present from preexisting introductions in an adaptive way. Finally, we found a significant negative correlation between FST estimates and the local GC content surrounding coding SNPs, suggesting that AT-rich genes play an important role in adaptive evolution in the honey bee. PMID:18299560

A genome-wide signature of positive selection in ancient and recent invasive expansions of the honey bee Apis mellifera.

PubMed

Zayed, Amro; Whitfield, Charles W

2008-03-04

Apis mellifera originated in Africa and extended its range into Eurasia in two or more ancient expansions. In 1956, honey bees of African origin were introduced into South America, their descendents admixing with previously introduced European bees, giving rise to the highly invasive and economically devastating "Africanized" honey bee. Here we ask whether the honey bee's out-of-Africa expansions, both ancient and recent (invasive), were associated with a genome-wide signature of positive selection, detected by contrasting genetic differentiation estimates (F(ST)) between coding and noncoding SNPs. In native populations, SNPs in protein-coding regions had significantly higher F(ST) estimates than those in noncoding regions, indicating adaptive evolution in the genome driven by positive selection. This signal of selection was associated with the expansion of honey bees from Africa into Western and Northern Europe, perhaps reflecting adaptation to temperate environments. We estimate that positive selection acted on a minimum of 852-1,371 genes or approximately 10% of the bee's coding genome. We also detected positive selection associated with the invasion of African-derived honey bees in the New World. We found that introgression of European-derived alleles into Africanized bees was significantly greater for coding than noncoding regions. Our findings demonstrate that Africanized bees exploited the genetic diversity present from preexisting introductions in an adaptive way. Finally, we found a significant negative correlation between F(ST) estimates and the local GC content surrounding coding SNPs, suggesting that AT-rich genes play an important role in adaptive evolution in the honey bee.

Landscape genomics: natural selection drives the evolution of mitogenome in penguins.

PubMed

Ramos, Barbara; González-Acuña, Daniel; Loyola, David E; Johnson, Warren E; Parker, Patricia G; Massaro, Melanie; Dantas, Gisele P M; Miranda, Marcelo D; Vianna, Juliana A

2018-01-16

Mitochondria play a key role in the balance of energy and heat production, and therefore the mitochondrial genome is under natural selection by environmental temperature and food availability, since starvation can generate more efficient coupling of energy production. However, selection over mitochondrial DNA (mtDNA) genes has usually been evaluated at the population level. We sequenced by NGS 12 mitogenomes and with four published genomes, assessed genetic variation in ten penguin species distributed from the equator to Antarctica. Signatures of selection of 13 mitochondrial protein-coding genes were evaluated by comparing among species within and among genera (Spheniscus, Pygoscelis, Eudyptula, Eudyptes and Aptenodytes). The genetic data were correlated with environmental data obtained through remote sensing (sea surface temperature [SST], chlorophyll levels [Chl] and a combination of SST and Chl [COM]) through the distribution of these species. We identified the complete mtDNA genomes of several penguin species, including ND6 and 8 tRNAs on the light strand and 12 protein coding genes, 14 tRNAs and two rRNAs positioned on the heavy strand. The highest diversity was found in NADH dehydrogenase genes and the lowest in COX genes. The lowest evolutionary divergence among species was between Humboldt (Spheniscus humboldti) and Galapagos (S. mendiculus) penguins (0.004), while the highest was observed between little penguin (Eudyptula minor) and Adélie penguin (Pygoscelis adeliae) (0.097). We identified a signature of purifying selection (Ka/Ks < 1) across the mitochondrial genome, which is consistent with the hypothesis that purifying selection is constraining mitogenome evolution to maintain Oxidative phosphorylation (OXPHOS) proteins and functionality. Pairwise species maximum-likelihood analyses of selection at codon sites suggest positive selection has occurred on ATP8 (Fixed-Effects Likelihood, FEL) and ND4 (Single Likelihood Ancestral Counting, SLAC) in all penguins. In contrast, COX1 had a signature of strong negative selection. ND4 Ka/Ks ratios were highly correlated with SST (Mantel, p-value: 0.0001; GLM, p-value: 0.00001) and thus may be related to climate adaptation throughout penguin speciation. These results identify mtDNA candidate genes under selection which could be involved in broad-scale adaptations of penguins to their environment. Such knowledge may be particularly useful for developing predictive models of how these species may respond to severe climatic changes in the future.

Fine-grained temporal coding of visually-similar categories in the ventral visual pathway and prefrontal cortex

PubMed Central

Xu, Yang; D'Lauro, Christopher; Pyles, John A.; Kass, Robert E.; Tarr, Michael J.

2013-01-01

Humans are remarkably proficient at categorizing visually-similar objects. To better understand the cortical basis of this categorization process, we used magnetoencephalography (MEG) to record neural activity while participants learned–with feedback–to discriminate two highly-similar, novel visual categories. We hypothesized that although prefrontal regions would mediate early category learning, this role would diminish with increasing category familiarity and that regions within the ventral visual pathway would come to play a more prominent role in encoding category-relevant information as learning progressed. Early in learning we observed some degree of categorical discriminability and predictability in both prefrontal cortex and the ventral visual pathway. Predictability improved significantly above chance in the ventral visual pathway over the course of learning with the left inferior temporal and fusiform gyri showing the greatest improvement in predictability between 150 and 250 ms (M200) during category learning. In contrast, there was no comparable increase in discriminability in prefrontal cortex with the only significant post-learning effect being a decrease in predictability in the inferior frontal gyrus between 250 and 350 ms (M300). Thus, the ventral visual pathway appears to encode learned visual categories over the long term. At the same time these results add to our understanding of the cortical origins of previously reported signature temporal components associated with perceptual learning. PMID:24146656

Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome.

PubMed

Davatzikos, Christos; Rathore, Saima; Bakas, Spyridon; Pati, Sarthak; Bergman, Mark; Kalarot, Ratheesh; Sridharan, Patmaa; Gastounioti, Aimilia; Jahani, Nariman; Cohen, Eric; Akbari, Hamed; Tunc, Birkan; Doshi, Jimit; Parker, Drew; Hsieh, Michael; Sotiras, Aristeidis; Li, Hongming; Ou, Yangming; Doot, Robert K; Bilello, Michel; Fan, Yong; Shinohara, Russell T; Yushkevich, Paul; Verma, Ragini; Kontos, Despina

2018-01-01

The growth of multiparametric imaging protocols has paved the way for quantitative imaging phenotypes that predict treatment response and clinical outcome, reflect underlying cancer molecular characteristics and spatiotemporal heterogeneity, and can guide personalized treatment planning. This growth has underlined the need for efficient quantitative analytics to derive high-dimensional imaging signatures of diagnostic and predictive value in this emerging era of integrated precision diagnostics. This paper presents cancer imaging phenomics toolkit (CaPTk), a new and dynamically growing software platform for analysis of radiographic images of cancer, currently focusing on brain, breast, and lung cancer. CaPTk leverages the value of quantitative imaging analytics along with machine learning to derive phenotypic imaging signatures, based on two-level functionality. First, image analysis algorithms are used to extract comprehensive panels of diverse and complementary features, such as multiparametric intensity histogram distributions, texture, shape, kinetics, connectomics, and spatial patterns. At the second level, these quantitative imaging signatures are fed into multivariate machine learning models to produce diagnostic, prognostic, and predictive biomarkers. Results from clinical studies in three areas are shown: (i) computational neuro-oncology of brain gliomas for precision diagnostics, prediction of outcome, and treatment planning; (ii) prediction of treatment response for breast and lung cancer, and (iii) risk assessment for breast cancer.

Regulatory versus coding signatures of natural selection in a candidate gene involved in the adaptive divergence of whitefish species pairs (Coregonus spp.)

PubMed Central

Jeukens, Julie; Bernatchez, Louis

2012-01-01

While gene expression divergence is known to be involved in adaptive phenotypic divergence and speciation, the relative importance of regulatory and structural evolution of genes is poorly understood. A recent next-generation sequencing experiment allowed identifying candidate genes potentially involved in the ongoing speciation of sympatric dwarf and normal lake whitefish (Coregonus clupeaformis), such as cytosolic malate dehydrogenase (MDH1), which showed both significant expression and sequence divergence. The main goal of this study was to investigate into more details the signatures of natural selection in the regulatory and coding sequences of MDH1 in lake whitefish and test for parallelism of these signatures with other coregonine species. Sequencing of the two regions in 118 fish from four sympatric pairs of whitefish and two cisco species revealed a total of 35 single nucleotide polymorphisms (SNPs), with more genetic diversity in European compared to North American coregonine species. While the coding region was found to be under purifying selection, an SNP in the proximal promoter exhibited significant allele frequency divergence in a parallel manner among independent sympatric pairs of North American lake whitefish and European whitefish (C. lavaretus). According to transcription factor binding simulation for 22 regulatory haplotypes of MDH1, putative binding profiles were fairly conserved among species, except for the region around this SNP. Moreover, we found evidence for the role of this SNP in the regulation of MDH1 expression level. Overall, these results provide further evidence for the role of natural selection in gene regulation evolution among whitefish species pairs and suggest its possible link with patterns of phenotypic diversity observed in coregonine species. PMID:22408741

Regulatory versus coding signatures of natural selection in a candidate gene involved in the adaptive divergence of whitefish species pairs (Coregonus spp.).

PubMed

Jeukens, Julie; Bernatchez, Louis

2012-01-01

While gene expression divergence is known to be involved in adaptive phenotypic divergence and speciation, the relative importance of regulatory and structural evolution of genes is poorly understood. A recent next-generation sequencing experiment allowed identifying candidate genes potentially involved in the ongoing speciation of sympatric dwarf and normal lake whitefish (Coregonus clupeaformis), such as cytosolic malate dehydrogenase (MDH1), which showed both significant expression and sequence divergence. The main goal of this study was to investigate into more details the signatures of natural selection in the regulatory and coding sequences of MDH1 in lake whitefish and test for parallelism of these signatures with other coregonine species. Sequencing of the two regions in 118 fish from four sympatric pairs of whitefish and two cisco species revealed a total of 35 single nucleotide polymorphisms (SNPs), with more genetic diversity in European compared to North American coregonine species. While the coding region was found to be under purifying selection, an SNP in the proximal promoter exhibited significant allele frequency divergence in a parallel manner among independent sympatric pairs of North American lake whitefish and European whitefish (C. lavaretus). According to transcription factor binding simulation for 22 regulatory haplotypes of MDH1, putative binding profiles were fairly conserved among species, except for the region around this SNP. Moreover, we found evidence for the role of this SNP in the regulation of MDH1 expression level. Overall, these results provide further evidence for the role of natural selection in gene regulation evolution among whitefish species pairs and suggest its possible link with patterns of phenotypic diversity observed in coregonine species.

Sparse generalized linear model with L0 approximation for feature selection and prediction with big omics data.

PubMed

Liu, Zhenqiu; Sun, Fengzhu; McGovern, Dermot P

2017-01-01

Feature selection and prediction are the most important tasks for big data mining. The common strategies for feature selection in big data mining are L 1 , SCAD and MC+. However, none of the existing algorithms optimizes L 0 , which penalizes the number of nonzero features directly. In this paper, we develop a novel sparse generalized linear model (GLM) with L 0 approximation for feature selection and prediction with big omics data. The proposed approach approximate the L 0 optimization directly. Even though the original L 0 problem is non-convex, the problem is approximated by sequential convex optimizations with the proposed algorithm. The proposed method is easy to implement with only several lines of code. Novel adaptive ridge algorithms ( L 0 ADRIDGE) for L 0 penalized GLM with ultra high dimensional big data are developed. The proposed approach outperforms the other cutting edge regularization methods including SCAD and MC+ in simulations. When it is applied to integrated analysis of mRNA, microRNA, and methylation data from TCGA ovarian cancer, multilevel gene signatures associated with suboptimal debulking are identified simultaneously. The biological significance and potential clinical importance of those genes are further explored. The developed Software L 0 ADRIDGE in MATLAB is available at https://github.com/liuzqx/L0adridge.

Prediction methodologies for target scene generation in the aerothermal targets analysis program (ATAP)

NASA Astrophysics Data System (ADS)

Hudson, Douglas J.; Torres, Manuel; Dougherty, Catherine; Rajendran, Natesan; Thompson, Rhoe A.

2003-09-01

The Air Force Research Laboratory (AFRL) Aerothermal Targets Analysis Program (ATAP) is a user-friendly, engineering-level computational tool that features integrated aerodynamics, six-degree-of-freedom (6-DoF) trajectory/motion, convective and radiative heat transfer, and thermal/material response to provide an optimal blend of accuracy and speed for design and analysis applications. ATAP is sponsored by the Kinetic Kill Vehicle Hardware-in-the-Loop Simulator (KHILS) facility at Eglin AFB, where it is used with the CHAMP (Composite Hardbody and Missile Plume) technique for rapid infrared (IR) signature and imagery predictions. ATAP capabilities include an integrated 1-D conduction model for up to 5 in-depth material layers (with options for gaps/voids with radiative heat transfer), fin modeling, several surface ablation modeling options, a materials library with over 250 materials, options for user-defined materials, selectable/definable atmosphere and earth models, multiple trajectory options, and an array of aerodynamic prediction methods. All major code modeling features have been validated with ground-test data from wind tunnels, shock tubes, and ballistics ranges, and flight-test data for both U.S. and foreign strategic and theater systems. Numerous applications include the design and analysis of interceptors, booster and shroud configurations, window environments, tactical missiles, and reentry vehicles.

A prospective blood RNA signature for tuberculosis disease risk

PubMed Central

Zak, Daniel E.; Penn-Nicholson, Adam; Scriba, Thomas J.; Thompson, Ethan; Suliman, Sara; Amon, Lynn M.; Mahomed, Hassan; Erasmus, Mzwandile; Whatney, Wendy; Hussey, Gregory D.; Abrahams, Deborah; Kafaar, Fazlin; Hawkridge, Tony; Verver, Suzanne; Hughes, E. Jane; Ota, Martin; Sutherland, Jayne; Howe, Rawleigh; Dockrell, Hazel M.; Boom, W. Henry; Thiel, Bonnie; Ottenhoff, Tom H.M.; Mayanja-Kizza, Harriet; Crampin, Amelia C; Downing, Katrina; Hatherill, Mark; Valvo, Joe; Shankar, Smitha; Parida, Shreemanta K; Kaufmann, Stefan H.E.; Walzl, Gerhard; Aderem, Alan; Hanekom, Willem A.

2016-01-01

Background Identification of blood biomarkers that prospectively predict progression of Mycobacterium tuberculosis infection to tuberculosis disease may lead to interventions that impact the epidemic. Methods Healthy, M. tuberculosis infected South African adolescents were followed for 2 years; blood was collected every 6 months. A prospective signature of risk was derived from whole blood RNA-Sequencing data by comparing participants who ultimately developed active tuberculosis disease (progressors) with those who remained healthy (matched controls). After adaptation to multiplex qRT-PCR, the signature was used to predict tuberculosis disease in untouched adolescent samples and in samples from independent cohorts of South African and Gambian adult progressors and controls. The latter participants were household contacts of adults with active pulmonary tuberculosis disease. Findings Of 6,363 adolescents screened, 46 progressors and 107 matched controls were identified. A 16 gene signature of risk was identified. The signature predicted tuberculosis progression with a sensitivity of 66·1% (95% confidence interval, 63·2–68·9) and a specificity of 80·6% (79·2–82·0) in the 12 months preceding tuberculosis diagnosis. The risk signature was validated in an untouched group of adolescents (p=0·018 for RNA-Seq and p=0·0095 for qRT-PCR) and in the independent South African and Gambian cohorts (p values <0·0001 by qRT-PCR) with a sensitivity of 53·7% (42·6–64·3) and a specificity of 82·8% (76·7–86) in 12 months preceding tuberculosis. Interpretation The whole blood tuberculosis risk signature prospectively identified persons at risk of developing active tuberculosis, opening the possibility for targeted intervention to prevent the disease. Funding Bill and Melinda Gates Foundation, the National Institutes of Health, Aeras, the European Union and the South African Medical Research Council (detail at end of text). PMID:27017310

Simulation of the vibrational chemistry and the infrared signature induced by a Sprite streamer in the mesosphere

NASA Astrophysics Data System (ADS)

Romand, F.; Payan, S.; Croize, L.

2017-12-01

Since their first observation in 1989, effect of TLEs on the atmospheric composition has become an open and important question. The lack of suitable experimental data is a shortcoming that hampers our understanding of the physics and chemistry induced by these effects. HALESIS (High-Altitude Luminous Events Studied by Infrared Spectro-imagery) is a future experiment dedicated to the measurement of the atmospheric perturbation induced by a TLE in the minutes following its occurrence, from a stratospheric balloon flying at an altitude of 25 km to 40 km. This work aims to quantify the local chemical impact of sprites in the stratosphere and mesosphere. In this paper, we will present the development of a tool which simulates (i) the impact of a sprite on the vibrational chemistry, (ii) the resulting infrared signature and (iii) the propagation of this signature through the atmosphere to an observer. First the Non Local Thermodynamic Equilibrium populations of a background atmosphere were computed using SAMM2 code. The initial thermodynamic and chemical description of atmosphere comes from the Whole Atmosphere community Climate Model (WACCM). Then a perturbation was applied to simulate a sprite. Chemistry due to TLEs was computed using Gordillo-Vazquez kinetic model. Rate coefficients that depend on the electron energy distribution function were calculated from collision cross-section data by solving the electron Boltzmann equation (BE). Time evolutions of the species densities and of vibrational populations in the non-thermal plasma consecutive to sprite discharge were simulated using the computer code ZDPlasKin (S. Pancheshn et al.). Finally, the resulting infrared signatures were propagated from the disturbed area through the atmosphere to an instrument placed in a limb line of sight using a line by line radiative transfer model. We will conclude that sprite could produce a significant infrared signature that last a few tens of seconds after the visible flash.

Influence Of Momentum Excess On The Pattern And Dynamics Of Intermediate-Range Stratified Wakes

DTIC Science & Technology

2016-06-01

excess in order to model the fundamental differences between signatures generated by towed and self- propelled bodies in various ocean states. In cases...which can be used on the operational level for developing and improving algorithms for non- acoustic signature prediction and detection. 14. SUBJECT...order to model the fundamental differences between signatures generated by towed and self- propelled bodies in various ocean states. In cases where

Novel algorithm to identify and differentiate specific digital signature of breath sound in patients with diffuse parenchymal lung disease.

PubMed

Bhattacharyya, Parthasarathi; Mondal, Ashok; Dey, Rana; Saha, Dipanjan; Saha, Goutam

2015-05-01

Auscultation is an important part of the clinical examination of different lung diseases. Objective analysis of lung sounds based on underlying characteristics and its subsequent automatic interpretations may help a clinical practice. We collected the breath sounds from 8 normal subjects and 20 diffuse parenchymal lung disease (DPLD) patients using a newly developed instrument and then filtered off the heart sounds using a novel technology. The collected sounds were thereafter analysed digitally on several characteristics as dynamical complexity, texture information and regularity index to find and define their unique digital signatures for differentiating normality and abnormality. For convenience of testing, these characteristic signatures of normal and DPLD lung sounds were transformed into coloured visual representations. The predictive power of these images has been validated by six independent observers that include three physicians. The proposed method gives a classification accuracy of 100% for composite features for both the normal as well as lung sound signals from DPLD patients. When tested by independent observers on the visually transformed images, the positive predictive value to diagnose the normality and DPLD remained 100%. The lung sounds from the normal and DPLD subjects could be differentiated and expressed according to their digital signatures. On visual transformation to coloured images, they retain 100% predictive power. This technique may assist physicians to diagnose DPLD from visual images bearing the digital signature of the condition. © 2015 Asian Pacific Society of Respirology.

Analysis of 6,515 exomes reveals the recent origin of most human protein-coding variants.

PubMed

Fu, Wenqing; O'Connor, Timothy D; Jun, Goo; Kang, Hyun Min; Abecasis, Goncalo; Leal, Suzanne M; Gabriel, Stacey; Rieder, Mark J; Altshuler, David; Shendure, Jay; Nickerson, Deborah A; Bamshad, Michael J; Akey, Joshua M

2013-01-10

Establishing the age of each mutation segregating in contemporary human populations is important to fully understand our evolutionary history and will help to facilitate the development of new approaches for disease-gene discovery. Large-scale surveys of human genetic variation have reported signatures of recent explosive population growth, notable for an excess of rare genetic variants, suggesting that many mutations arose recently. To more quantitatively assess the distribution of mutation ages, we resequenced 15,336 genes in 6,515 individuals of European American and African American ancestry and inferred the age of 1,146,401 autosomal single nucleotide variants (SNVs). We estimate that approximately 73% of all protein-coding SNVs and approximately 86% of SNVs predicted to be deleterious arose in the past 5,000-10,000 years. The average age of deleterious SNVs varied significantly across molecular pathways, and disease genes contained a significantly higher proportion of recently arisen deleterious SNVs than other genes. Furthermore, European Americans had an excess of deleterious variants in essential and Mendelian disease genes compared to African Americans, consistent with weaker purifying selection due to the Out-of-Africa dispersal. Our results better delimit the historical details of human protein-coding variation, show the profound effect of recent human history on the burden of deleterious SNVs segregating in contemporary populations, and provide important practical information that can be used to prioritize variants in disease-gene discovery.

Apparatuses and methods of determining if a person operating equipment is experiencing an elevated cognitive load

DOEpatents

Watkins, Michael L.; Keller, Paul Edwin; Amaya, Ivan A.

2015-06-16

A method of, and apparatus for, determining if a person operating equipment is experiencing an elevated cognitive load, wherein the person's use of a device at a first time is monitored so as to set a baseline signature. Then, at a later time, the person's use of the device is monitored to determine the person's performance at the second time, as represented by a performance signature. This performance signature can then be compared against the baseline signature to predict whether the person is experiencing an elevated cognitive load.

Machine learning algorithm accurately detects fMRI signature of vulnerability to major depression.

PubMed

Sato, João R; Moll, Jorge; Green, Sophie; Deakin, John F W; Thomaz, Carlos E; Zahn, Roland

2015-08-30

Standard functional magnetic resonance imaging (fMRI) analyses cannot assess the potential of a neuroimaging signature as a biomarker to predict individual vulnerability to major depression (MD). Here, we use machine learning for the first time to address this question. Using a recently identified neural signature of guilt-selective functional disconnection, the classification algorithm was able to distinguish remitted MD from control participants with 78.3% accuracy. This demonstrates the high potential of our fMRI signature as a biomarker of MD vulnerability. Crown Copyright © 2015. Published by Elsevier Ireland Ltd. All rights reserved.

A Simple and Efficient Computational Approach to Chafed Cable Time-Domain Reflectometry Signature Prediction

NASA Technical Reports Server (NTRS)

Kowalski, Marc Edward

2009-01-01

A method for the prediction of time-domain signatures of chafed coaxial cables is presented. The method is quasi-static in nature, and is thus efficient enough to be included in inference and inversion routines. Unlike previous models proposed, no restriction on the geometry or size of the chafe is required in the present approach. The model is validated and its speed is illustrated via comparison to simulations from a commercial, three-dimensional electromagnetic simulator.

The bioenergetic signature of isogenic colon cancer cells predicts the cell death response to treatment with 3-bromopyruvate, iodoacetate or 5-fluorouracil

PubMed Central

2011-01-01

Background Metabolic reprogramming resulting in enhanced glycolysis is a phenotypic trait of cancer cells, which is imposed by the tumor microenvironment and is linked to the down-regulation of the catalytic subunit of the mitochondrial H+-ATPase (β-F1-ATPase). The bioenergetic signature is a protein ratio (β-F1-ATPase/GAPDH), which provides an estimate of glucose metabolism in tumors and serves as a prognostic indicator for cancer patients. Targeting energetic metabolism could be a viable alternative to conventional anticancer chemotherapies. Herein, we document that the bioenergetic signature of isogenic colon cancer cells provides a gauge to predict the cell-death response to the metabolic inhibitors, 3-bromopyruvate (3BrP) and iodoacetate (IA), and the anti-metabolite, 5-fluorouracil (5-FU). Methods The bioenergetic signature of the cells was determined by western blotting. Aerobic glycolysis was determined from lactate production rates. The cell death was analyzed by fluorescence microscopy and flow cytometry. Cellular ATP concentrations were determined using bioluminiscence. Pearson's correlation coefficient was applied to assess the relationship between the bioenergetic signature and the cell death response. In vivo tumor regression activities of the compounds were assessed using a xenograft mouse model injected with the highly glycolytic HCT116 colocarcinoma cells. Results We demonstrate that the bioenergetic signature of isogenic HCT116 cancer cells inversely correlates with the potential to execute necrosis in response to 3BrP or IA treatment. Conversely, the bioenergetic signature directly correlates with the potential to execute apoptosis in response to 5-FU treatment in the same cells. However, despite the large differences observed in the in vitro cell-death responses associated with 3BrP, IA and 5-FU, the in vivo tumor regression activities of these agents were comparable. Conclusions Overall, we suggest that the determination of the bioenergetic signature of colon carcinomas could provide a tool for predicting the therapeutic response to various chemotherapeutic strategies aimed at combating tumor progression. PMID:21303518

Visibility Data Filters for Europe

DTIC Science & Technology

1990-04-14

Manager Atmospheric Optics Branch FOR THE COMMANDER (Signature) R. Earl Good, Director Optical and Infrared Techn logy Division This report has been...recorded under code WW1, WW2 , etc. Unfortunately for most of the European stations contained in the DATSAV database, the precipitation flags are missing

A Serum Circulating miRNA Signature for Short-Term Risk of Progression to Active Tuberculosis Among Household Contacts.

PubMed

Duffy, Fergal J; Thompson, Ethan; Downing, Katrina; Suliman, Sara; Mayanja-Kizza, Harriet; Boom, W Henry; Thiel, Bonnie; Weiner Iii, January; Kaufmann, Stefan H E; Dover, Drew; Tabb, David L; Dockrell, Hazel M; Ottenhoff, Tom H M; Tromp, Gerard; Scriba, Thomas J; Zak, Daniel E; Walzl, Gerhard

2018-01-01

Biomarkers that predict who among recently Mycobacterium tuberculosis (MTB)-exposed individuals will progress to active tuberculosis are urgently needed. Intracellular microRNAs (miRNAs) regulate the host response to MTB and circulating miRNAs (c-miRNAs) have been developed as biomarkers for other diseases. We performed machine-learning analysis of c-miRNA measurements in the serum of adult household contacts (HHCs) of TB index cases from South Africa and Uganda and developed a c-miRNA-based signature of risk for progression to active TB. This c-miRNA-based signature significantly discriminated HHCs within 6 months of progression to active disease from HHCs that remained healthy in an independent test set [ROC area under the ROC curve (AUC) 0.74, progressors < 6 Mo to active TB and ROC AUC 0.66, up to 24 Mo to active TB], and complements the predictions of a previous cellular mRNA-based signature of TB risk.

Signatures of selection in tilapia revealed by whole genome resequencing

PubMed Central

Hong Xia, Jun; Bai, Zhiyi; Meng, Zining; Zhang, Yong; Wang, Le; Liu, Feng; Jing, Wu; Yi Wan, Zi; Li, Jiale; Lin, Haoran; Hua Yue, Gen

2015-01-01

Natural selection and selective breeding for genetic improvement have left detectable signatures within the genome of a species. Identification of selection signatures is important in evolutionary biology and for detecting genes that facilitate to accelerate genetic improvement. However, selection signatures, including artificial selection and natural selection, have only been identified at the whole genome level in several genetically improved fish species. Tilapia is one of the most important genetically improved fish species in the world. Using next-generation sequencing, we sequenced the genomes of 47 tilapia individuals. We identified a total of 1.43 million high-quality SNPs and found that the LD block sizes ranged from 10–100 kb in tilapia. We detected over a hundred putative selective sweep regions in each line of tilapia. Most selection signatures were located in non-coding regions of the tilapia genome. The Wnt signaling, gonadotropin-releasing hormone receptor and integrin signaling pathways were under positive selection in all improved tilapia lines. Our study provides a genome-wide map of genetic variation and selection footprints in tilapia, which could be important for genetic studies and accelerating genetic improvement of tilapia. PMID:26373374

On the information content of hydrological signatures and their relationship to catchment attributes

NASA Astrophysics Data System (ADS)

Addor, Nans; Clark, Martyn P.; Prieto, Cristina; Newman, Andrew J.; Mizukami, Naoki; Nearing, Grey; Le Vine, Nataliya

2017-04-01

Hydrological signatures, which are indices characterizing hydrologic behavior, are increasingly used for the evaluation, calibration and selection of hydrological models. Their key advantage is to provide more direct insights into specific hydrological processes than aggregated metrics (e.g., the Nash-Sutcliffe efficiency). A plethora of signatures now exists, which enable characterizing a variety of hydrograph features, but also makes the selection of signatures for new studies challenging. Here we propose that the selection of signatures should be based on their information content, which we estimated using several approaches, all leading to similar conclusions. To explore the relationship between hydrological signatures and the landscape, we extended a previously published data set of hydrometeorological time series for 671 catchments in the contiguous United States, by characterizing the climatic conditions, topography, soil, vegetation and stream network of each catchment. This new catchment attributes data set will soon be in open access, and we are looking forward to introducing it to the community. We used this data set in a data-learning algorithm (random forests) to explore whether hydrological signatures could be inferred from catchment attributes alone. We find that some signatures can be predicted remarkably well by random forests and, interestingly, the same signatures are well captured when simulating discharge using a conceptual hydrological model. We discuss what this result reveals about our understanding of hydrological processes shaping hydrological signatures. We also identify which catchment attributes exert the strongest control on catchment behavior, in particular during extreme hydrological events. Overall, climatic attributes have the most significant influence, and strongly condition how well hydrological signatures can be predicted by random forests and simulated by the hydrological model. In contrast, soil characteristics at the catchment scale are not found to be significant predictors by random forests, which raises questions on how to best use soil data for hydrological modeling, for instance for parameter estimation. We finally demonstrate that signatures with high spatial variability are poorly captured by random forests and model simulations, which makes their regionalization delicate. We conclude with a ranking of signatures based on their information content, and propose that the signatures with high information content are best suited for model calibration, model selection and understanding hydrologic similarity.

Predicted osteotomy planes are accurate when using patient-specific instrumentation for total knee arthroplasty in cadavers: a descriptive analysis.

PubMed

Kievit, A J; Dobbe, J G G; Streekstra, G J; Blankevoort, L; Schafroth, M U

2018-06-01

Malalignment of implants is a major source of failure during total knee arthroplasty. To achieve more accurate 3D planning and execution of the osteotomy cuts during surgery, the Signature (Biomet, Warsaw) patient-specific instrumentation (PSI) was used to produce pin guides for the positioning of the osteotomy blocks by means of computer-aided manufacture based on CT scan images. The research question of this study is: what is the transfer accuracy of osteotomy planes predicted by the Signature PSI system for preoperative 3D planning and intraoperative block-guided pin placement to perform total knee arthroplasty procedures? The transfer accuracy achieved by using the Signature PSI system was evaluated by comparing the osteotomy planes predicted preoperatively with the osteotomy planes seen intraoperatively in human cadaveric legs. Outcomes were measured in terms of translational and rotational errors (varus, valgus, flexion, extension and axial rotation) for both tibia and femur osteotomies. Average translational errors between the osteotomy planes predicted using the Signature system and the actual osteotomy planes achieved was 0.8 mm (± 0.5 mm) for the tibia and 0.7 mm (± 4.0 mm) for the femur. Average rotational errors in relation to predicted and achieved osteotomy planes were 0.1° (± 1.2°) of varus and 0.4° (± 1.7°) of anterior slope (extension) for the tibia, and 2.8° (± 2.0°) of varus and 0.9° (± 2.7°) of flexion and 1.4° (± 2.2°) of external rotation for the femur. The similarity between osteotomy planes predicted using the Signature system and osteotomy planes actually achieved was excellent for the tibia although some discrepancies were seen for the femur. The use of 3D system techniques in TKA surgery can provide accurate intraoperative guidance, especially for patients with deformed bone, tailored to individual patients and ensure better placement of the implant.

The non-coding RNA landscape of human hematopoiesis and leukemia.

PubMed

Schwarzer, Adrian; Emmrich, Stephan; Schmidt, Franziska; Beck, Dominik; Ng, Michelle; Reimer, Christina; Adams, Felix Ferdinand; Grasedieck, Sarah; Witte, Damian; Käbler, Sebastian; Wong, Jason W H; Shah, Anushi; Huang, Yizhou; Jammal, Razan; Maroz, Aliaksandra; Jongen-Lavrencic, Mojca; Schambach, Axel; Kuchenbauer, Florian; Pimanda, John E; Reinhardt, Dirk; Heckl, Dirk; Klusmann, Jan-Henning

2017-08-09

Non-coding RNAs have emerged as crucial regulators of gene expression and cell fate decisions. However, their expression patterns and regulatory functions during normal and malignant human hematopoiesis are incompletely understood. Here we present a comprehensive resource defining the non-coding RNA landscape of the human hematopoietic system. Based on highly specific non-coding RNA expression portraits per blood cell population, we identify unique fingerprint non-coding RNAs-such as LINC00173 in granulocytes-and assign these to critical regulatory circuits involved in blood homeostasis. Following the incorporation of acute myeloid leukemia samples into the landscape, we further uncover prognostically relevant non-coding RNA stem cell signatures shared between acute myeloid leukemia blasts and healthy hematopoietic stem cells. Our findings highlight the importance of the non-coding transcriptome in the formation and maintenance of the human blood hierarchy.While micro-RNAs are known regulators of haematopoiesis and leukemogenesis, the role of long non-coding RNAs is less clear. Here the authors provide a non-coding RNA expression landscape of the human hematopoietic system, highlighting their role in the formation and maintenance of the human blood hierarchy.

Summary of Pressure Gain Combustion Research at NASA

NASA Technical Reports Server (NTRS)

Perkins, H. Douglas; Paxson, Daniel E.

2018-01-01

NASA has undertaken a systematic exploration of many different facets of pressure gain combustion over the last 25 years in an effort to exploit the inherent thermodynamic advantage of pressure gain combustion over the constant pressure combustion process used in most aerospace propulsion systems. Applications as varied as small-scale UAV's, rotorcraft, subsonic transports, hypersonics and launch vehicles have been considered. In addition to studying pressure gain combustor concepts such as wave rotors, pulse detonation engines, pulsejets, and rotating detonation engines, NASA has studied inlets, nozzles, ejectors and turbines which must also process unsteady flow in an integrated propulsion system. Other design considerations such as acoustic signature, combustor material life and heat transfer that are unique to pressure gain combustors have also been addressed in NASA research projects. In addition to a wide range of experimental studies, a number of computer codes, from 0-D up through 3-D, have been developed or modified to specifically address the analysis of unsteady flow fields. Loss models have also been developed and incorporated into these codes that improve the accuracy of performance predictions and decrease computational time. These codes have been validated numerous times across a broad range of operating conditions, and it has been found that once validated for one particular pressure gain combustion configuration, these codes are readily adaptable to the others. All in all, the documentation of this work has encompassed approximately 170 NASA technical reports, conference papers and journal articles to date. These publications are very briefly summarized herein, providing a single point of reference for all of NASA's pressure gain combustion research efforts. This documentation does not include the significant contributions made by NASA research staff to the programs of other agencies, universities, industrial partners and professional society committees through serving as technical advisors, technical reviewers and research consultants.

A PRIM approach to predictive-signature development for patient stratification.

PubMed

Chen, Gong; Zhong, Hua; Belousov, Anton; Devanarayan, Viswanath

2015-01-30

Patients often respond differently to a treatment because of individual heterogeneity. Failures of clinical trials can be substantially reduced if, prior to an investigational treatment, patients are stratified into responders and nonresponders based on biological or demographic characteristics. These characteristics are captured by a predictive signature. In this paper, we propose a procedure to search for predictive signatures based on the approach of patient rule induction method. Specifically, we discuss selection of a proper objective function for the search, present its algorithm, and describe a resampling scheme that can enhance search performance. Through simulations, we characterize conditions under which the procedure works well. To demonstrate practical uses of the procedure, we apply it to two real-world data sets. We also compare the results with those obtained from a recent regression-based approach, Adaptive Index Models, and discuss their respective advantages. In this study, we focus on oncology applications with survival responses. © 2014 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Establishment of a 12-gene expression signature to predict colon cancer prognosis

PubMed Central

Zhao, Guangxi; Dong, Pingping; Wu, Bingrui

2018-01-01

A robust and accurate gene expression signature is essential to assist oncologists to determine which subset of patients at similar Tumor-Lymph Node-Metastasis (TNM) stage has high recurrence risk and could benefit from adjuvant therapies. Here we applied a two-step supervised machine-learning method and established a 12-gene expression signature to precisely predict colon adenocarcinoma (COAD) prognosis by using COAD RNA-seq transcriptome data from The Cancer Genome Atlas (TCGA). The predictive performance of the 12-gene signature was validated with two independent gene expression microarray datasets: GSE39582 includes 566 COAD cases for the development of six molecular subtypes with distinct clinical, molecular and survival characteristics; GSE17538 is a dataset containing 232 colon cancer patients for the generation of a metastasis gene expression profile to predict recurrence and death in COAD patients. The signature could effectively separate the poor prognosis patients from good prognosis group (disease specific survival (DSS): Kaplan Meier (KM) Log Rank p = 0.0034; overall survival (OS): KM Log Rank p = 0.0336) in GSE17538. For patients with proficient mismatch repair system (pMMR) in GSE39582, the signature could also effectively distinguish high risk group from low risk group (OS: KM Log Rank p = 0.005; Relapse free survival (RFS): KM Log Rank p = 0.022). Interestingly, advanced stage patients were significantly enriched in high 12-gene score group (Fisher’s exact test p = 0.0003). After stage stratification, the signature could still distinguish poor prognosis patients in GSE17538 from good prognosis within stage II (Log Rank p = 0.01) and stage II & III (Log Rank p = 0.017) in the outcome of DFS. Within stage III or II/III pMMR patients treated with Adjuvant Chemotherapies (ACT) and patients with higher 12-gene score showed poorer prognosis (III, OS: KM Log Rank p = 0.046; III & II, OS: KM Log Rank p = 0.041). Among stage II/III pMMR patients with lower 12-gene scores in GSE39582, the subgroup receiving ACT showed significantly longer OS time compared with those who received no ACT (Log Rank p = 0.021), while there is no obvious difference between counterparts among patients with higher 12-gene scores (Log Rank p = 0.12). Besides COAD, our 12-gene signature is multifunctional in several other cancer types including kidney cancer, lung cancer, uveal and skin melanoma, brain cancer, and pancreatic cancer. Functional classification showed that seven of the twelve genes are involved in immune system function and regulation, so our 12-gene signature could potentially be used to guide decisions about adjuvant therapy for patients with stage II/III and pMMR COAD.

Probing the ToxCast Chemical Library for Predictive Signatures of Developmental Toxicity

EPA Science Inventory

EPA’s ToxCast™ project is profiling the in vitro bioactivity of chemical compounds to assess pathway-level and cell-based signatures that correlate with observed in vivo toxicity. We hypothesize that cell signaling pathways are primary targets for diverse environmental chemicals ...

Optimization Of Engine Heat Transfer Mechanisms For Ground Combat Vehicle Signature Models

NASA Astrophysics Data System (ADS)

Gonda, T.; Rogers, P.; Gerhart, G.; Reynolds, W. R.

1988-08-01

A thermodynamic model for predicting the behavior of selected internal thermal sources of an M2 Bradley Infantry Fighting Vehicle is described. The modeling methodology is expressed in terms of first principle heat transfer equations along with a brief history of TACOM's experience with thermal signature modeling techniques. The dynamic operation of the internal thermal sources is presented along with limited test data and an examination of their effect on the vehicle signature.

Searching for evidence of quasi-periodic pulsations in solar flares using the AFINO code

NASA Astrophysics Data System (ADS)

Inglis, Andrew; Ireland, Jack; Dennis, Brian R.; Hayes, Laura Ann; Gallagher, Peter T.

2017-08-01

The AFINO (Automated Flare Inference of Oscillations) code is a new tool to allow analysis of temporal solar data in search of oscillatory signatures. Using AFINO, we carry out a large-scale search for evidence of signals consistent with quasi-periodic pulsations (QPP) in solar flares, focusing on the 1-300 s timescale. We analyze 675 M- and X-class flares observed by GOES in 1-8 Å soft X-rays between 2011 February 1 and 2015 December 31. Additionally, over the same era we analyze Fermi/GBM 15-25 keV X-ray data for each of these flares associated with a GBM solar flare trigger, a total of 261 events. Using a model comparison method and the Bayesian Information Criterion statistic, we determine whether there is evidence for a substantial enhancement in the Fourier power spectrum that may be consistent with a QPP-like signature.Quasi-steady periodic signatures appear more prevalently in thermal soft X-ray data than in the counterpart hard X-ray emission: according to AFINO ~30% of GOES flares but only ~8% of the same flares observed by GBM show strong signatures consistent with classical interpretations of QPP, which include MHD wave processes and oscillatory reconnection events. For both datasets, preferred characteristic timescales of ~5-30 s were found in the QPP-like events, with no clear dependence on flare magnitude. Individual events in the sample also show similar characteristic timescales in both GBM and GOES data sets, indicating that the same phenomenon is sometimes observed simultaneously in soft and hard X-rays. We discuss the implications of these survey results, and future developments of the analysis method. AFINO continues to run daily on new flares observed by GOES, and the full AFINO catalogue is made available online.

Signature of chaos in the 4 f -core-excited states for highly-charged tungsten ions

NASA Astrophysics Data System (ADS)

Safronova, Ulyana; Safronova, Alla

2014-05-01

We evaluate radiative and autoionizing transition rates in highly charged W ions in search for the signature of chaos. In particularly, previously published results for Ag-like W27+, Tm-like W5+, and Yb-like W4+ ions as well as newly obtained for I-like W21+, Xe-like W20+, Cs-like W19+, and La-like W17+ ions (with ground configuration [Kr] 4d10 4fk with k = 7, 8, 9, and 11, respectively) are considered that were calculated using the multiconfiguration relativistic Hebrew University Lawrence Livermore Atomic Code (HULLAC code) and the Hartree-Fock-Relativistic method (COWAN code). The main emphasis was on verification of Gaussian statistics of rates as a function of transition energy. There was no evidence of such statistics for above mentioned previously published results as well as for the transitions between the excited and autoionizing states for newly calculated results. However, we did find the Gaussian profile for the transitions between excited states such as the [Kr] 4d10 4fk - [Kr] 4d10 4f k - 1 5 d transitions , for newly calculated W ions. This work is supported in part by DOE under NNSA Cooperative Agreement DE-NA0001984.

Long non-coding RNAs as novel expression signatures modulate DNA damage and repair in cadmium toxicology

NASA Astrophysics Data System (ADS)

Zhou, Zhiheng; Liu, Haibai; Wang, Caixia; Lu, Qian; Huang, Qinhai; Zheng, Chanjiao; Lei, Yixiong

2015-10-01

Increasing evidence suggests that long non-coding RNAs (lncRNAs) are involved in a variety of physiological and pathophysiological processes. Our study was to investigate whether lncRNAs as novel expression signatures are able to modulate DNA damage and repair in cadmium(Cd) toxicity. There were aberrant expression profiles of lncRNAs in 35th Cd-induced cells as compared to untreated 16HBE cells. siRNA-mediated knockdown of ENST00000414355 inhibited the growth of DNA-damaged cells and decreased the expressions of DNA-damage related genes (ATM, ATR and ATRIP), while increased the expressions of DNA-repair related genes (DDB1, DDB2, OGG1, ERCC1, MSH2, RAD50, XRCC1 and BARD1). Cadmium increased ENST00000414355 expression in the lung of Cd-exposed rats in a dose-dependent manner. A significant positive correlation was observed between blood ENST00000414355 expression and urinary/blood Cd concentrations, and there were significant correlations of lncRNA-ENST00000414355 expression with the expressions of target genes in the lung of Cd-exposed rats and the blood of Cd exposed workers. These results indicate that some lncRNAs are aberrantly expressed in Cd-treated 16HBE cells. lncRNA-ENST00000414355 may serve as a signature for DNA damage and repair related to the epigenetic mechanisms underlying the cadmium toxicity and become a novel biomarker of cadmium toxicity.

SPECT3D - A multi-dimensional collisional-radiative code for generating diagnostic signatures based on hydrodynamics and PIC simulation output

NASA Astrophysics Data System (ADS)

MacFarlane, J. J.; Golovkin, I. E.; Wang, P.; Woodruff, P. R.; Pereyra, N. A.

2007-05-01

SPECT3D is a multi-dimensional collisional-radiative code used to post-process the output from radiation-hydrodynamics (RH) and particle-in-cell (PIC) codes to generate diagnostic signatures (e.g. images, spectra) that can be compared directly with experimental measurements. This ability to post-process simulation code output plays a pivotal role in assessing the reliability of RH and PIC simulation codes and their physics models. SPECT3D has the capability to operate on plasmas in 1D, 2D, and 3D geometries. It computes a variety of diagnostic signatures that can be compared with experimental measurements, including: time-resolved and time-integrated spectra, space-resolved spectra and streaked spectra; filtered and monochromatic images; and X-ray diode signals. Simulated images and spectra can include the effects of backlighters, as well as the effects of instrumental broadening and time-gating. SPECT3D also includes a drilldown capability that shows where frequency-dependent radiation is emitted and absorbed as it propagates through the plasma towards the detector, thereby providing insights on where the radiation seen by a detector originates within the plasma. SPECT3D has the capability to model a variety of complex atomic and radiative processes that affect the radiation seen by imaging and spectral detectors in high energy density physics (HEDP) experiments. LTE (local thermodynamic equilibrium) or non-LTE atomic level populations can be computed for plasmas. Photoabsorption rates can be computed using either escape probability models or, for selected 1D and 2D geometries, multi-angle radiative transfer models. The effects of non-thermal (i.e. non-Maxwellian) electron distributions can also be included. To study the influence of energetic particles on spectra and images recorded in intense short-pulse laser experiments, the effects of both relativistic electrons and energetic proton beams can be simulated. SPECT3D is a user-friendly software package that runs on Windows, Linux, and Mac platforms. A parallel version of SPECT3D is supported for Linux clusters for large-scale calculations. We will discuss the major features of SPECT3D, and present example results from simulations and comparisons with experimental data.

Assessment of Current Jet Noise Prediction Capabilities

NASA Technical Reports Server (NTRS)

Hunter, Craid A.; Bridges, James E.; Khavaran, Abbas

2008-01-01

An assessment was made of the capability of jet noise prediction codes over a broad range of jet flows, with the objective of quantifying current capabilities and identifying areas requiring future research investment. Three separate codes in NASA s possession, representative of two classes of jet noise prediction codes, were evaluated, one empirical and two statistical. The empirical code is the Stone Jet Noise Module (ST2JET) contained within the ANOPP aircraft noise prediction code. It is well documented, and represents the state of the art in semi-empirical acoustic prediction codes where virtual sources are attributed to various aspects of noise generation in each jet. These sources, in combination, predict the spectral directivity of a jet plume. A total of 258 jet noise cases were examined on the ST2JET code, each run requiring only fractions of a second to complete. Two statistical jet noise prediction codes were also evaluated, JeNo v1, and Jet3D. Fewer cases were run for the statistical prediction methods because they require substantially more resources, typically a Reynolds-Averaged Navier-Stokes solution of the jet, volume integration of the source statistical models over the entire plume, and a numerical solution of the governing propagation equation within the jet. In the evaluation process, substantial justification of experimental datasets used in the evaluations was made. In the end, none of the current codes can predict jet noise within experimental uncertainty. The empirical code came within 2dB on a 1/3 octave spectral basis for a wide range of flows. The statistical code Jet3D was within experimental uncertainty at broadside angles for hot supersonic jets, but errors in peak frequency and amplitude put it out of experimental uncertainty at cooler, lower speed conditions. Jet3D did not predict changes in directivity in the downstream angles. The statistical code JeNo,v1 was within experimental uncertainty predicting noise from cold subsonic jets at all angles, but did not predict changes with heating of the jet and did not account for directivity changes at supersonic conditions. Shortcomings addressed here give direction for future work relevant to the statistical-based prediction methods. A full report will be released as a chapter in a NASA publication assessing the state of the art in aircraft noise prediction.

Probing the ToxCastTM Chemical Library for Predictive Signatures of Developmental Toxicity -NLTO Poster

EPA Science Inventory

EPA’s ToxCast™ project is profiling the in vitro bioactivity of chemical compounds to assess pathway-level and cell-based signatures that correlate with observed in vivo toxicity. We hypothesize that cell signaling pathways are primary targets for diverse environmental chemicals ...

LLE Review Quarterly Report (January-March 1999). Volume 78

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

Regan, Sean P.

1999-03-01

This volume of the LLE Review, covering the period January-March 1999, features two articles concerning issues relevant to 2-D SSD laser-beam smoothing on OMEGA. In the first article J. D. Zuegel and J. A. Marozas present the design of an efficient, bulk phase modulator operating at approximately 10.5 GHz, which can produce substantial phase-modulated bandwidth with modest microwave drive power. This modulator is the cornerstone of the 1-THz UV bandwidth operation planned for OMEGA this year. In the second article J. A. Marozas and J. H. Kelly describe a recently developed code -- Waasese -- that simulates the collective behaviormore » of the optical components in the SSD driver line. The measurable signatures predicted by the code greatly enhance the diagnostic capability of the SSD driver line. Other articles in this volume are titled: Hollow-Shell Implosion Studies on the 60-Beam, UC OMEGA Laser System; Simultaneous Measurements of Fuel Areal Density, Shell Areal Density, and Fuel Temperature in D 3He-Filled Imploding Capsules; The Design of Optical Pulse Shapes with an Aperture-Coupled-Stripline Pulse-Shaping System; Measurement Technique for Characterization of Rapidly Time- and Frequency-Varying Electronic Devices; and, Damage to Fused-Silica, Spatial-Filter Lenses on the OMEGA Laser System.« less

Peripheral Blood Gene Expression as a Novel Genomic Biomarker in Complicated Sarcoidosis

PubMed Central

Sweiss, Nadera J.; Chen, Edward S.; Moller, David R.; Knox, Kenneth S.; Ma, Shwu-Fan; Wade, Michael S.; Noth, Imre; Machado, Roberto F.; Garcia, Joe G. N.

2012-01-01

Sarcoidosis, a systemic granulomatous syndrome invariably affecting the lung, typically spontaneously remits but in ∼20% of cases progresses with severe lung dysfunction or cardiac and neurologic involvement (complicated sarcoidosis). Unfortunately, current biomarkers fail to distinguish patients with remitting (uncomplicated) sarcoidosis from other fibrotic lung disorders, and fail to identify individuals at risk for complicated sarcoidosis. We utilized genome-wide peripheral blood gene expression analysis to identify a 20-gene sarcoidosis biomarker signature distinguishing sarcoidosis (n = 39) from healthy controls (n = 35, 86% classification accuracy) and which served as a molecular signature for complicated sarcoidosis (n = 17). As aberrancies in T cell receptor (TCR) signaling, JAK-STAT (JS) signaling, and cytokine-cytokine receptor (CCR) signaling are implicated in sarcoidosis pathogenesis, a 31-gene signature comprised of T cell signaling pathway genes associated with sarcoidosis (TCR/JS/CCR) was compared to the unbiased 20-gene biomarker signature but proved inferior in prediction accuracy in distinguishing complicated from uncomplicated sarcoidosis. Additional validation strategies included significant association of single nucleotide polymorphisms (SNPs) in signature genes with sarcoidosis susceptibility and severity (unbiased signature genes - CX3CR1, FKBP1A, NOG, RBM12B, SENS3, TSHZ2; T cell/JAK-STAT pathway genes such as AKT3, CBLB, DLG1, IFNG, IL2RA, IL7R, ITK, JUN, MALT1, NFATC2, PLCG1, SPRED1). In summary, this validated peripheral blood molecular gene signature appears to be a valuable biomarker in identifying cases with sarcoidoisis and predicting risk for complicated sarcoidosis. PMID:22984568

Profiling persistent tubercule bacilli from patient sputa during therapy predicts early drug efficacy.

PubMed

Honeyborne, Isobella; McHugh, Timothy D; Kuittinen, Iitu; Cichonska, Anna; Evangelopoulos, Dimitrios; Ronacher, Katharina; van Helden, Paul D; Gillespie, Stephen H; Fernandez-Reyes, Delmiro; Walzl, Gerhard; Rousu, Juho; Butcher, Philip D; Waddell, Simon J

2016-04-07

New treatment options are needed to maintain and improve therapy for tuberculosis, which caused the death of 1.5 million people in 2013 despite potential for an 86 % treatment success rate. A greater understanding of Mycobacterium tuberculosis (M.tb) bacilli that persist through drug therapy will aid drug development programs. Predictive biomarkers for treatment efficacy are also a research priority. Genome-wide transcriptional profiling was used to map the mRNA signatures of M.tb from the sputa of 15 patients before and 3, 7 and 14 days after the start of standard regimen drug treatment. The mRNA profiles of bacilli through the first 2 weeks of therapy reflected drug activity at 3 days with transcriptional signatures at days 7 and 14 consistent with reduced M.tb metabolic activity similar to the profile of pre-chemotherapy bacilli. These results suggest that a pre-existing drug-tolerant M.tb population dominates sputum before and after early drug treatment, and that the mRNA signature at day 3 marks the killing of a drug-sensitive sub-population of bacilli. Modelling patient indices of disease severity with bacterial gene expression patterns demonstrated that both microbiological and clinical parameters were reflected in the divergent M.tb responses and provided evidence that factors such as bacterial load and disease pathology influence the host-pathogen interplay and the phenotypic state of bacilli. Transcriptional signatures were also defined that predicted measures of early treatment success (rate of decline in bacterial load over 3 days, TB test positivity at 2 months, and bacterial load at 2 months). This study defines the transcriptional signature of M.tb bacilli that have been expectorated in sputum after two weeks of drug therapy, characterizing the phenotypic state of bacilli that persist through treatment. We demonstrate that variability in clinical manifestations of disease are detectable in bacterial sputa signatures, and that the changing M.tb mRNA profiles 0-2 weeks into chemotherapy predict the efficacy of treatment 6 weeks later. These observations advocate assaying dynamic bacterial phenotypes through drug therapy as biomarkers for treatment success.

Study of Dynamic Characteristics of Aeroelastic Systems Utilizing Randomdec Signatures

NASA Technical Reports Server (NTRS)

Chang, C. S.

1975-01-01

The feasibility of utilizing the random decrement method in conjunction with a signature analysis procedure to determine the dynamic characteristics of an aeroelastic system for the purpose of on-line prediction of potential on-set of flutter was examined. Digital computer programs were developed to simulate sampled response signals of a two-mode aeroelastic system. Simulated response data were used to test the random decrement method. A special curve-fit approach was developed for analyzing the resulting signatures. A number of numerical 'experiments' were conducted on the combined processes. The method is capable of determining frequency and damping values accurately from randomdec signatures of carefully selected lengths.

Comparison of GLIMPS and HFAST Stirling engine code predictions with experimental data

NASA Technical Reports Server (NTRS)

Geng, Steven M.; Tew, Roy C.

1992-01-01

Predictions from GLIMPS and HFAST design codes are compared with experimental data for the RE-1000 and SPRE free piston Stirling engines. Engine performance and available power loss predictions are compared. Differences exist between GLIMPS and HFAST loss predictions. Both codes require engine specific calibration to bring predictions and experimental data into agreement.

9 CFR 205.202 - “Effective financing statement” or EFS.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Uniform Commercial Code (or equivalent document under future successor State law), but can be an entirely separate document meeting the definition in (c)(4). Note that (c)(4) contains a comprehensive definition of... State allows electronic filing of financing statements without the signature of the debtor under...

9 CFR 205.202 - “Effective financing statement” or EFS.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Uniform Commercial Code (or equivalent document under future successor State law), but can be an entirely separate document meeting the definition in (c)(4). Note that (c)(4) contains a comprehensive definition of... State allows electronic filing of financing statements without the signature of the debtor under...

Cancer-cell intrinsic gene expression signatures overcome intratumoural heterogeneity bias in colorectal cancer patient classification

PubMed Central

Dunne, Philip D.; Alderdice, Matthew; O'Reilly, Paul G.; Roddy, Aideen C.; McCorry, Amy M. B.; Richman, Susan; Maughan, Tim; McDade, Simon S.; Johnston, Patrick G.; Longley, Daniel B.; Kay, Elaine; McArt, Darragh G.; Lawler, Mark

2017-01-01

Stromal-derived intratumoural heterogeneity (ITH) has been shown to undermine molecular stratification of patients into appropriate prognostic/predictive subgroups. Here, using several clinically relevant colorectal cancer (CRC) gene expression signatures, we assessed the susceptibility of these signatures to the confounding effects of ITH using gene expression microarray data obtained from multiple tumour regions of a cohort of 24 patients, including central tumour, the tumour invasive front and lymph node metastasis. Sample clustering alongside correlative assessment revealed variation in the ability of each signature to cluster samples according to patient-of-origin rather than region-of-origin within the multi-region dataset. Signatures focused on cancer-cell intrinsic gene expression were found to produce more clinically useful, patient-centred classifiers, as exemplified by the CRC intrinsic signature (CRIS), which robustly clustered samples by patient-of-origin rather than region-of-origin. These findings highlight the potential of cancer-cell intrinsic signatures to reliably stratify CRC patients by minimising the confounding effects of stromal-derived ITH. PMID:28561046

A 3-Protein Expression Signature of Neuroblastoma for Outcome Prediction.

PubMed

Xie, Yi; Xu, Hua; Fang, Fang; Li, Zhiheng; Zhou, Huiting; Pan, Jian; Guo, Wanliang; Zhu, Xueming; Wang, Jian; Wu, Yi

2018-05-22

Neuroblastoma (NB) is the most common extracranial solid tumor in children with contrasting outcomes. Precise risk assessment contributes to prognosis prediction, which is critical for treatment strategy decisions. In this study, we developed a 3-protein predictor model, including the neural stem cell marker Msi1, neural differentiation marker ID1, and proliferation marker proliferating cell nuclear antigen (PCNA), to improve clinical risk assessment of patients with NB. Kaplan-Meier analysis in the microarray data (GSE16476) revealed that low expression of ID1 and high expression of Msi1 and PCNA were associated with poor prognosis in NB patients. Combined application of these 3 markers to constitute a signature further stratified NB patients into different risk subgroups can help obtain more accurate prediction performance. Survival prognostic power of age and Msi1_ID1_PCNA signature by receiver operating characteristics analysis showed that this signature predicted more effectively and sensitively compared with classic risk stratification system, compensating for the deficiency of the prediction function of the age. Furthermore, we validated the expressions of these 3 proteins in neuroblastic tumor spectrum tissues by immunohistochemistry revealed that Msi1 and PCNA exhibited increased expression in NB compared with intermedial ganglioneuroblastoma and benign ganglioneuroma, whereas ID1 levels were reduced in NB. In conclusion, we established a robust risk assessment predictor model based on simple immunohistochemistry for therapeutic decisions of NB patients.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0/.

Muscle myeloid type I interferon gene expression may predict therapeutic responses to rituximab in myositis patients

PubMed Central

Nagaraju, Kanneboyina; Ghimbovschi, Svetlana; Rayavarapu, Sree; Phadke, Aditi; Rider, Lisa G.; Hoffman, Eric P.

2016-01-01

Abstract Objective. To identify muscle gene expression patterns that predict rituximab responses and assess the effects of rituximab on muscle gene expression in PM and DM. Methods. In an attempt to understand the molecular mechanism of response and non-response to rituximab therapy, we performed Affymetrix gene expression array analyses on muscle biopsy specimens taken before and after rituximab therapy from eight PM and two DM patients in the Rituximab in Myositis study. We also analysed selected muscle-infiltrating cell phenotypes in these biopsies by immunohistochemical staining. Partek and Ingenuity pathway analyses assessed the gene pathways and networks. Results. Myeloid type I IFN signature genes were expressed at higher levels at baseline in the skeletal muscle of rituximab responders than in non-responders, whereas classic non-myeloid IFN signature genes were expressed at higher levels in non-responders at baseline. Also, rituximab responders have a greater reduction of the myeloid and non-myeloid type I IFN signatures than non-responders. The decrease in the type I IFN signature following administration of rituximab may be associated with the decreases in muscle-infiltrating CD19 + B cells and CD68 + macrophages in responders. Conclusion. Our findings suggest that high levels of myeloid type I IFN gene expression in skeletal muscle predict responses to rituximab in PM/DM and that rituximab responders also have a greater decrease in the expression of these genes. These data add further evidence to recent studies defining the type I IFN signature as both a predictor of therapeutic responses and a biomarker of myositis disease activity. PMID:27215813

Low and middle altitude cusp particle signatures for general magnetopause reconnection rate variations. 1: Theory

NASA Technical Reports Server (NTRS)

Lockwood, M.; Smith, M. F.

1994-01-01

We present predictions of the signatures of magnetosheath particle precipitation (in the regions classified as open low-latitude boundary layer, cusp, mantle and polar cap) for periods when the interplanetary magnetic field has a southward component. These are made using the 'pulsating cusp' model of the effects of time-varying magnetic reconnection at the dayside magnetopause. Predictions are made for both low-altitude satellites in the topside ionosphere and for midaltitude spacecraft in the magnetosphere. Low-altitude cusp signatures, which show a continuous ion dispersion signature, reveal 'quasi-steady reconnection' (one limit of the pulsating cusp model), which persists for a period of at least 10 min. We estimate that 'quasi-steady' in this context corresponds to fluctuations in the reconnection rate of a factor of 2 or less. The other limit of the pulsating cusp model explains the instantaneous jumps in the precipitating ion spectrum that have been observed at low altitudes. Such jumps are produced by isolated pulses of reconnection: that is, they are separated by intervals when the reconnection rate is zero. These also generate convecting patches on the magnetopause in which the field lines thread the boundary via a rotational discontinuity separated by more extensive regions of tangential discontinuity. Predictions of the corresponding ion precipitation signatures seen by midaltitude spacecraft are presented. We resolve the apparent contradiction between estimates of the width of the injection region from midaltitude data and the concept of continuous entry of solar wind plasma along open field lines. In addition, we reevaluate the use of pitch angle-energy dispersion to estimate the injection distance.

The effect of unsteady blade loading on the aeroacoustics of a pusher propeller

NASA Astrophysics Data System (ADS)

Mauk, Clay S.; Farokhi, Saeed

1993-06-01

A theoretical/computational approach is developed to predict the change in near-field noise due to a momentum-deficit upstream of a propeller plane, specifically for a pylon wake in a pusher configuration. The acoustic pressure is computed using blade geometry and unsteady blade surface pressure history. The steady blade surface pressure is predicted using blade-momentum theory and two-dimensional airfoil characteristics. Unsteady blade pressures are derived from in-flight measurements. In-flight acoustic measurements are used for code validation purposes. Overall sound pressure levels (OSPL) are computed for an array of observer locations parallel to the propeller axis of rotation. In order to clearly realize the effect of the wake encounter on the radiated sound, the wake signature is eliminated from the unsteady blade pressures. By subtracting the OSPL computed with the smoothed data from that computed with the original unsteady data, the change in noise resulting from the wake encounter is deduced. In general, the noise was increased due to the propeller-wake chopping activity. For all flight conditions, the largest increase in radiated noise occurred for a highly loaded propeller. The results indicate that the propeller noise due to periodic wake encounter may possess a unique directivity pattern.

Comparison between measured and predicted turbulence frequency spectra in ITG and TEM regimes

NASA Astrophysics Data System (ADS)

Citrin, J.; Arnichand, H.; Bernardo, J.; Bourdelle, C.; Garbet, X.; Jenko, F.; Hacquin, S.; Pueschel, M. J.; Sabot, R.

2017-06-01

The observation of distinct peaks in tokamak core reflectometry measurements—named quasi-coherent-modes (QCMs)—are identified as a signature of trapped-electron-mode (TEM) turbulence (Arnichand et al 2016 Plasma Phys. Control. Fusion 58 014037). This phenomenon is investigated with detailed linear and nonlinear gyrokinetic simulations using the Gene code. A Tore-Supra density scan is studied, which traverses through a linear (LOC) to saturated (SOC) ohmic confinement transition. The LOC and SOC phases are both simulated separately. In the LOC phase, where QCMs are observed, TEMs are robustly predicted unstable in linear studies. In the later SOC phase, where QCMs are no longer observed, ion-temperature-gradient (ITG) modes are identified. In nonlinear simulations, in the ITG (SOC) phase, a broadband spectrum is seen. In the TEM (LOC) phase, a clear emergence of a peak at the TEM frequencies is seen. This is due to reduced nonlinear frequency broadening of the underlying linear modes in the TEM regime compared with the ITG regime. A synthetic diagnostic of the nonlinearly simulated frequency spectra reproduces the features observed in the reflectometry measurements. These results support the identification of core QCMs as an experimental marker for TEM turbulence.

An MEG signature corresponding to an axiomatic model of reward prediction error.

PubMed

Talmi, Deborah; Fuentemilla, Lluis; Litvak, Vladimir; Duzel, Emrah; Dolan, Raymond J

2012-01-02

Optimal decision-making is guided by evaluating the outcomes of previous decisions. Prediction errors are theoretical teaching signals which integrate two features of an outcome: its inherent value and prior expectation of its occurrence. To uncover the magnetic signature of prediction errors in the human brain we acquired magnetoencephalographic (MEG) data while participants performed a gambling task. Our primary objective was to use formal criteria, based upon an axiomatic model (Caplin and Dean, 2008a), to determine the presence and timing profile of MEG signals that express prediction errors. We report analyses at the sensor level, implemented in SPM8, time locked to outcome onset. We identified, for the first time, a MEG signature of prediction error, which emerged approximately 320 ms after an outcome and expressed as an interaction between outcome valence and probability. This signal followed earlier, separate signals for outcome valence and probability, which emerged approximately 200 ms after an outcome. Strikingly, the time course of the prediction error signal, as well as the early valence signal, resembled the Feedback-Related Negativity (FRN). In simultaneously acquired EEG data we obtained a robust FRN, but the win and loss signals that comprised this difference wave did not comply with the axiomatic model. Our findings motivate an explicit examination of the critical issue of timing embodied in computational models of prediction errors as seen in human electrophysiological data. Copyright © 2011 Elsevier Inc. All rights reserved.

pkCSM: Predicting Small-Molecule Pharmacokinetic and Toxicity Properties Using Graph-Based Signatures

PubMed Central

2015-01-01

Drug development has a high attrition rate, with poor pharmacokinetic and safety properties a significant hurdle. Computational approaches may help minimize these risks. We have developed a novel approach (pkCSM) which uses graph-based signatures to develop predictive models of central ADMET properties for drug development. pkCSM performs as well or better than current methods. A freely accessible web server (http://structure.bioc.cam.ac.uk/pkcsm), which retains no information submitted to it, provides an integrated platform to rapidly evaluate pharmacokinetic and toxicity properties. PMID:25860834

Genomic signatures characterize leukocyte infiltration in myositis muscles

PubMed Central

2012-01-01

Background Leukocyte infiltration plays an important role in the pathogenesis and progression of myositis, and is highly associated with disease severity. Currently, there is a lack of: efficacious therapies for myositis; understanding of the molecular features important for disease pathogenesis; and potential molecular biomarkers for characterizing inflammatory myopathies to aid in clinical development. Methods In this study, we developed a simple model and predicted that 1) leukocyte-specific transcripts (including both protein-coding transcripts and microRNAs) should be coherently overexpressed in myositis muscle and 2) the level of over-expression of these transcripts should be correlated with leukocyte infiltration. We applied this model to assess immune cell infiltration in myositis by examining mRNA and microRNA (miRNA) expression profiles in muscle biopsies from 31 myositis patients and 5 normal controls. Results Several gene signatures, including a leukocyte index, type 1 interferon (IFN), MHC class I, and immunoglobulin signature, were developed to characterize myositis patients at the molecular level. The leukocyte index, consisting of genes predominantly associated with immune function, displayed strong concordance with pathological assessment of immune cell infiltration. This leukocyte index was subsequently utilized to differentiate transcriptional changes due to leukocyte infiltration from other alterations in myositis muscle. Results from this differentiation revealed biologically relevant differences in the relationship between the type 1 IFN pathway, miR-146a, and leukocyte infiltration within various myositis subtypes. Conclusions Results indicate that a likely interaction between miR-146a expression and the type 1 IFN pathway is confounded by the level of leukocyte infiltration into muscle tissue. Although the role of miR-146a in myositis remains uncertain, our results highlight the potential benefit of deconvoluting the source of transcriptional changes in myositis muscle or other heterogeneous tissue samples. Taken together, the leukocyte index and other gene signatures developed in this study may be potential molecular biomarkers to help to further characterize inflammatory myopathies and aid in clinical development. These hypotheses need to be confirmed in separate and sufficiently powered clinical trials. PMID:23171592

Asymmetric distances for binary embeddings.

PubMed

Gordo, Albert; Perronnin, Florent; Gong, Yunchao; Lazebnik, Svetlana

2014-01-01

In large-scale query-by-example retrieval, embedding image signatures in a binary space offers two benefits: data compression and search efficiency. While most embedding algorithms binarize both query and database signatures, it has been noted that this is not strictly a requirement. Indeed, asymmetric schemes that binarize the database signatures but not the query still enjoy the same two benefits but may provide superior accuracy. In this work, we propose two general asymmetric distances that are applicable to a wide variety of embedding techniques including locality sensitive hashing (LSH), locality sensitive binary codes (LSBC), spectral hashing (SH), PCA embedding (PCAE), PCAE with random rotations (PCAE-RR), and PCAE with iterative quantization (PCAE-ITQ). We experiment on four public benchmarks containing up to 1M images and show that the proposed asymmetric distances consistently lead to large improvements over the symmetric Hamming distance for all binary embedding techniques.

Simplified sonic-boom prediction. [using aerodynamic configuration charts and calculators or slide rules

NASA Technical Reports Server (NTRS)

Carlson, H. W.

1978-01-01

Sonic boom overpressures and signature duration may be predicted for the entire affected ground area for a wide variety of supersonic airplane configurations and spacecraft operating at altitudes up to 76 km in level flight or in moderate climbing or descending flight paths. The outlined procedure relies to a great extent on the use of charts to provide generation and propagation factors for use in relatively simple expressions for signature calculation. Computational requirements can be met by hand-held scientific calculators, or even by slide rules. A variety of correlations of predicted and measured sonic-boom data for airplanes and spacecraft serve to demonstrate the applicability of the simplified method.

Genomic evidence for genes encoding leucine-rich repeat receptors linked to resistance against the eukaryotic extra- and intracellular Brassica napus pathogens Leptosphaeria maculans and Plasmodiophora brassicae.

PubMed

Stotz, Henrik U; Harvey, Pascoe J; Haddadi, Parham; Mashanova, Alla; Kukol, Andreas; Larkan, Nicholas J; Borhan, M Hossein; Fitt, Bruce D L

2018-01-01

Genes coding for nucleotide-binding leucine-rich repeat (LRR) receptors (NLRs) control resistance against intracellular (cell-penetrating) pathogens. However, evidence for a role of genes coding for proteins with LRR domains in resistance against extracellular (apoplastic) fungal pathogens is limited. Here, the distribution of genes coding for proteins with eLRR domains but lacking kinase domains was determined for the Brassica napus genome. Predictions of signal peptide and transmembrane regions divided these genes into 184 coding for receptor-like proteins (RLPs) and 121 coding for secreted proteins (SPs). Together with previously annotated NLRs, a total of 720 LRR genes were found. Leptosphaeria maculans-induced expression during a compatible interaction with cultivar Topas differed between RLP, SP and NLR gene families; NLR genes were induced relatively late, during the necrotrophic phase of pathogen colonization. Seven RLP, one SP and two NLR genes were found in Rlm1 and Rlm3/Rlm4/Rlm7/Rlm9 loci for resistance against L. maculans on chromosome A07 of B. napus. One NLR gene at the Rlm9 locus was positively selected, as was the RLP gene on chromosome A10 with LepR3 and Rlm2 alleles conferring resistance against L. maculans races with corresponding effectors AvrLm1 and AvrLm2, respectively. Known loci for resistance against L. maculans (extracellular hemi-biotrophic fungus), Sclerotinia sclerotiorum (necrotrophic fungus) and Plasmodiophora brassicae (intracellular, obligate biotrophic protist) were examined for presence of RLPs, SPs and NLRs in these regions. Whereas loci for resistance against P. brassicae were enriched for NLRs, no such signature was observed for the other pathogens. These findings demonstrate involvement of (i) NLR genes in resistance against the intracellular pathogen P. brassicae and a putative NLR gene in Rlm9-mediated resistance against the extracellular pathogen L. maculans.

Source Authentication for Code Dissemination Supporting Dynamic Packet Size in Wireless Sensor Networks.

PubMed

Kim, Daehee; Kim, Dongwan; An, Sunshin

2016-07-09

Code dissemination in wireless sensor networks (WSNs) is a procedure for distributing a new code image over the air in order to update programs. Due to the fact that WSNs are mostly deployed in unattended and hostile environments, secure code dissemination ensuring authenticity and integrity is essential. Recent works on dynamic packet size control in WSNs allow enhancing the energy efficiency of code dissemination by dynamically changing the packet size on the basis of link quality. However, the authentication tokens attached by the base station become useless in the next hop where the packet size can vary according to the link quality of the next hop. In this paper, we propose three source authentication schemes for code dissemination supporting dynamic packet size. Compared to traditional source authentication schemes such as μTESLA and digital signatures, our schemes provide secure source authentication under the environment, where the packet size changes in each hop, with smaller energy consumption.

Source Authentication for Code Dissemination Supporting Dynamic Packet Size in Wireless Sensor Networks †

PubMed Central

Kim, Daehee; Kim, Dongwan; An, Sunshin

2016-01-01

Code dissemination in wireless sensor networks (WSNs) is a procedure for distributing a new code image over the air in order to update programs. Due to the fact that WSNs are mostly deployed in unattended and hostile environments, secure code dissemination ensuring authenticity and integrity is essential. Recent works on dynamic packet size control in WSNs allow enhancing the energy efficiency of code dissemination by dynamically changing the packet size on the basis of link quality. However, the authentication tokens attached by the base station become useless in the next hop where the packet size can vary according to the link quality of the next hop. In this paper, we propose three source authentication schemes for code dissemination supporting dynamic packet size. Compared to traditional source authentication schemes such as μTESLA and digital signatures, our schemes provide secure source authentication under the environment, where the packet size changes in each hop, with smaller energy consumption. PMID:27409616

Simulation of Acoustic Noise Generated by an Airbreathing, Beam-Powered Launch Vehicle

NASA Astrophysics Data System (ADS)

Kennedy, W. C.; Van Laak, P.; Scarton, H. A.; Myrabo, L. N.

2005-04-01

A simple acoustic model is developed for predicting the noise signature vs. power level for advanced laser-propelled lightcraft — capable of single-stage flights into low Earth orbit. This model predicts the noise levels generated by a pulsed detonation engine (PDE) during the initial lift-off and acceleration phase, for two representative `tractor-beam' lightcraft designs: a 1-place `Mercury' vehicle (2.5-m diameter, 900-kg); and a larger 5-place `Apollo' vehicle (5-m diameter, 5555-kg) — both the subject of an earlier study. The use of digital techniques to simulate the expected PDE noise signature is discussed, and three examples of fly-by noise signatures are presented. The reduction, or complete elimination of perceptible noise from such engines, can be accomplished by shifting the pulse frequency into the supra-audible or sub-audible range.

Low-delay predictive audio coding for the HIVITS HDTV codec

NASA Astrophysics Data System (ADS)

McParland, A. K.; Gilchrist, N. H. C.

1995-01-01

The status of work relating to predictive audio coding, as part of the European project on High Quality Video Telephone and HD(TV) Systems (HIVITS), is reported. The predictive coding algorithm is developed, along with six-channel audio coding and decoding hardware. Demonstrations of the audio codec operating in conjunction with the video codec, are given.

Development of an automatic cow body condition scoring using body shape signature and Fourier descriptors.

PubMed

Bercovich, A; Edan, Y; Alchanatis, V; Moallem, U; Parmet, Y; Honig, H; Maltz, E; Antler, A; Halachmi, I

2013-01-01

Body condition evaluation is a common tool to assess energy reserves of dairy cows and to estimate their fatness or thinness. This study presents a computer-vision tool that automatically estimates cow's body condition score. Top-view images of 151 cows were collected on an Israeli research dairy farm using a digital still camera located at the entrance to the milking parlor. The cow's tailhead area and its contour were segmented and extracted automatically. Two types of features of the tailhead contour were extracted: (1) the angles and distances between 5 anatomical points; and (2) the cow signature, which is a 1-dimensional vector of the Euclidean distances from each point in the normalized tailhead contour to the shape center. Two methods were applied to describe the cow's signature and to reduce its dimension: (1) partial least squares regression, and (2) Fourier descriptors of the cow signature. Three prediction models were compared with manual scores of an expert. Results indicate that (1) it is possible to automatically extract and predict body condition from color images without any manual interference; and (2) Fourier descriptors of the cow's signature result in improved performance (R(2)=0.77). Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Overview of Recent Radiation Transport Code Comparisons for Space Applications

NASA Astrophysics Data System (ADS)

Townsend, Lawrence

Recent advances in radiation transport code development for space applications have resulted in various comparisons of code predictions for a variety of scenarios and codes. Comparisons among both Monte Carlo and deterministic codes have been made and published by vari-ous groups and collaborations, including comparisons involving, but not limited to HZETRN, HETC-HEDS, FLUKA, GEANT, PHITS, and MCNPX. In this work, an overview of recent code prediction inter-comparisons, including comparisons to available experimental data, is presented and discussed, with emphases on those areas of agreement and disagreement among the various code predictions and published data.

Probing the ToxCastTM Chemical Library for Predictive Signatures of Developmental Toxicity - Poster at Teratology Society Annual Meeting

EPA Science Inventory

EPA’s ToxCast™ project is profiling the in vitro bioactivity of chemical compounds to assess pathway-level and cell-based signatures that correlate with observed in vivo toxicity. We hypothesize that cell signaling pathways are primary targets for diverse environmental chemicals ...

Optimal Weight Assignment for a Chinese Signature File.

ERIC Educational Resources Information Center

Liang, Tyne; And Others

1996-01-01

Investigates the performance of a character-based Chinese text retrieval scheme in which monogram keys and bigram keys are encoded into document signatures. Tests and verifies the theoretical predictions of the optimal weight assignments and the minimal false hit rate in experiments using a real Chinese corpus for disyllabic queries of different…

Accurate Prediction of Motor Failures by Application of Multi CBM Tools: A Case Study

NASA Astrophysics Data System (ADS)

Dutta, Rana; Singh, Veerendra Pratap; Dwivedi, Jai Prakash

2018-02-01

Motor failures are very difficult to predict accurately with a single condition-monitoring tool as both electrical and the mechanical systems are closely related. Electrical problem, like phase unbalance, stator winding insulation failures can, at times, lead to vibration problem and at the same time mechanical failures like bearing failure, leads to rotor eccentricity. In this case study of a 550 kW blower motor it has been shown that a rotor bar crack was detected by current signature analysis and vibration monitoring confirmed the same. In later months in a similar motor vibration monitoring predicted bearing failure and current signature analysis confirmed the same. In both the cases, after dismantling the motor, the predictions were found to be accurate. In this paper we will be discussing the accurate predictions of motor failures through use of multi condition monitoring tools with two case studies.

Using a Stem Cell-Based Signature to Guide Therapeutic Selection in Cancer

PubMed Central

Shats, Igor; Gatza, Michael L.; Chang, Jeffrey T.; Mori, Seiichi; Wang, Jialiang; Rich, Jeremy; Nevins, Joseph R.

2010-01-01

Given the very substantial heterogeneity of most human cancers, it is likely that most cancer therapeutics will be active in only a small fraction of any population of patients. As such, the development of new therapeutics, coupled with methods to match a therapy with the individual patient, will be critical to achieving significant gains in disease outcome. One such opportunity is the use of expression signatures to identify key oncogenic phenotypes that can serve not only as biomarkers but also as a means of identifying therapeutic compounds that might specifically target these phenotypes. Given the potential importance of targeting tumors exhibiting a stem-like phenotype, we have developed an expression signature that reflects common biological aspects of various stem-like characteristics. The Consensus Stemness Ranking (CSR) signature is upregulated in cancer stem cell enriched samples, at advanced tumor stages and is associated with poor prognosis in multiple cancer types. Using two independent computational approaches we utilized the CSR signature to identify clinically useful compounds that could target the CSR phenotype. In vitro assays confirmed selectivity of several predicted compounds including topoisomerase inhibitors and resveratrol towards breast cancer cell lines that exhibit a high-CSR phenotype. Importantly, the CSR signature could predict clinical response of breast cancer patients to a neoadjuvant regimen that included a CSR-specific agent. Collectively, these results suggest therapeutic opportunities to target the CSR phenotype in a relevant cohort of cancer patients. PMID:21169407

miRNA signature associated with outcome of gastric cancer patients following chemotherapy

PubMed Central

2011-01-01

Background Identification of patients who likely will or will not benefit from cytotoxic chemotherapy through the use of biomarkers could greatly improve clinical management by better defining appropriate treatment options for patients. microRNAs may be potentially useful biomarkers that help guide individualized therapy for cancer because microRNA expression is dysregulated in cancer. In order to identify miRNA signatures for gastric cancer and for predicting clinical resistance to cisplatin/fluorouracil (CF) chemotherapy, a comprehensive miRNA microarray analysis was performed using endoscopic biopsy samples. Methods Biopsy samples were collected prior to chemotherapy from 90 gastric cancer patients treated with CF and from 34 healthy volunteers. At the time of disease progression, post-treatment samples were additionally collected from 8 clinical responders. miRNA expression was determined using a custom-designed Agilent microarray. In order to identify a miRNA signature for chemotherapy resistance, we correlated miRNA expression levels with the time to progression (TTP) of disease after CF therapy. Results A miRNA signature distinguishing gastric cancer from normal stomach epithelium was identified. 30 miRNAs were significantly inversely correlated with TTP whereas 28 miRNAs were significantly positively correlated with TTP of 82 cancer patients (P<0.05). Prominent among the upregulated miRNAs associated with chemosensitivity were miRNAs known to regulate apoptosis, including let-7g, miR-342, miR-16, miR-181, miR-1, and miR-34. When this 58-miRNA predictor was applied to a separate set of pre- and post-treatment tumor samples from the 8 clinical responders, all of the 8 pre-treatment samples were correctly predicted as low-risk, whereas samples from the post-treatment tumors that developed chemoresistance were predicted to be in the high-risk category by the 58 miRNA signature, suggesting that selection for the expression of these miRNAs occurred as chemoresistance arose. Conclusions We have identified 1) a miRNA expression signature that distinguishes gastric cancer from normal stomach epithelium from healthy volunteers, and 2) a chemoreresistance miRNA expression signature that is correlated with TTP after CF therapy. The chemoresistance miRNA expression signature includes several miRNAs previously shown to regulate apoptosis in vitro, and warrants further validation. PMID:22112324

S100A9 and EGFR gene signatures predict disease progression in muscle invasive bladder cancer patients after chemotherapy.

PubMed

Kim, W T; Kim, J; Yan, C; Jeong, P; Choi, S Y; Lee, O J; Chae, Y B; Yun, S J; Lee, S C; Kim, W J

2014-05-01

In our previous gene expression profile analysis, IL1B, S100A8, S100A9, and EGFR were shown to be important mediators of muscle invasive bladder cancer (MIBC) progression. The aim of the present study was to investigate the ability of these gene signatures to predict disease progression after chemotherapy in patients with locally recurrent or metastatic MIBC. Patients with locally advanced MIBC who received chemotherapy were enrolled. The expression signatures of four genes were measured and carried out further functional analysis to confirm our findings. Two of the four genes, S100A9 and EGFR, were determined to significantly influence disease progression (P = 0.023, 0.045, respectively). Based on a receiver operating characteristic curve, a cut-off value for disease progression was determined. Patients with the good-prognostic signature group had a significantly longer time to progression and cancer-specific survival time than those with the poor-prognostic signature group (P < 0.001, 0.042, respectively). In the multivariate Cox regression analysis, gene signature was the only factor that significantly influenced disease progression [hazard ratio: 4.726, confidence interval: 1.623-13.763, P = 0.004]. In immunohistochemical analysis, S100A9 and EGFR positivity were associated with disease progression after chemotherapy. Protein expression of S100A9/EGFR showed modest correlation with gene expression of S100A9/EGFR (r = 0.395, P = 0.014 and r = 0.453, P = 0.004). Our functional analysis provided the evidence demonstrating that expression of S100A9 and EGFR closely associated chemoresistance, and that inhibition of S100A9 and EGFR may sensitize bladder tumor cells to the cisplatin-based chemotherapy. The S100A9/EGFR level is a novel prognostic marker to predict the chemoresponsiveness of patients with locally recurrent or metastatic MIBC.

Bit selection using field drilling data and mathematical investigation

NASA Astrophysics Data System (ADS)

Momeni, M. S.; Ridha, S.; Hosseini, S. J.; Meyghani, B.; Emamian, S. S.

2018-03-01

A drilling process will not be complete without the usage of a drill bit. Therefore, bit selection is considered to be an important task in drilling optimization process. To select a bit is considered as an important issue in planning and designing a well. This is simply because the cost of drilling bit in total cost is quite high. Thus, to perform this task, aback propagation ANN Model is developed. This is done by training the model using several wells and it is done by the usage of drilling bit records from offset wells. In this project, two models are developed by the usage of the ANN. One is to find predicted IADC bit code and one is to find Predicted ROP. Stage 1 was to find the IADC bit code by using all the given filed data. The output is the Targeted IADC bit code. Stage 2 was to find the Predicted ROP values using the gained IADC bit code in Stage 1. Next is Stage 3 where the Predicted ROP value is used back again in the data set to gain Predicted IADC bit code value. The output is the Predicted IADC bit code. Thus, at the end, there are two models that give the Predicted ROP values and Predicted IADC bit code values.

Neural representations of the concepts in simple sentences: Concept activation prediction and context effects.

PubMed

Just, Marcel Adam; Wang, Jing; Cherkassky, Vladimir L

2017-08-15

Although it has been possible to identify individual concepts from a concept's brain activation pattern, there have been significant obstacles to identifying a proposition from its fMRI signature. Here we demonstrate the ability to decode individual prototype sentences from readers' brain activation patterns, by using theory-driven regions of interest and semantic properties. It is possible to predict the fMRI brain activation patterns evoked by propositions and words which are entirely new to the model with reliably above-chance rank accuracy. The two core components implemented in the model that reflect the theory were the choice of intermediate semantic features and the brain regions associated with the neurosemantic dimensions. This approach also predicts the neural representation of object nouns across participants, studies, and sentence contexts. Moreover, we find that the neural representation of an agent-verb-object proto-sentence is more accurately characterized by the neural signatures of its components as they occur in a similar context than by the neural signatures of these components as they occur in isolation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Binding Affinity prediction with Property Encoded Shape Distribution signatures

PubMed Central

Das, Sourav; Krein, Michael P.

2010-01-01

We report the use of the molecular signatures known as “Property-Encoded Shape Distributions” (PESD) together with standard Support Vector Machine (SVM) techniques to produce validated models that can predict the binding affinity of a large number of protein ligand complexes. This “PESD-SVM” method uses PESD signatures that encode molecular shapes and property distributions on protein and ligand surfaces as features to build SVM models that require no subjective feature selection. A simple protocol was employed for tuning the SVM models during their development, and the results were compared to SFCscore – a regression-based method that was previously shown to perform better than 14 other scoring functions. Although the PESD-SVM method is based on only two surface property maps, the overall results were comparable. For most complexes with a dominant enthalpic contribution to binding (ΔH/-TΔS > 3), a good correlation between true and predicted affinities was observed. Entropy and solvent were not considered in the present approach and further improvement in accuracy would require accounting for these components rigorously. PMID:20095526

Signaling protein signature predicts clinical outcome of non-small-cell lung cancer.

PubMed

Jin, Bao-Feng; Yang, Fan; Ying, Xiao-Min; Gong, Lin; Hu, Shuo-Feng; Zhao, Qing; Liao, Yi-Da; Chen, Ke-Zhong; Li, Teng; Tai, Yan-Hong; Cao, Yuan; Li, Xiao; Huang, Yan; Zhan, Xiao-Yan; Qin, Xuan-He; Wu, Jin; Chen, Shuai; Guo, Sai-Sai; Zhang, Yu-Cheng; Chen, Jing; Shen, Dan-Hua; Sun, Kun-Kun; Chen, Lu; Li, Wei-Hua; Li, Ai-Ling; Wang, Na; Xia, Qing; Wang, Jun; Zhou, Tao

2018-03-06

Non-small-cell lung cancer (NSCLC) is characterized by abnormalities of numerous signaling proteins that play pivotal roles in cancer development and progression. Many of these proteins have been reported to be correlated with clinical outcomes of NSCLC. However, none of them could provide adequate accuracy of prognosis prediction in clinical application. A total of 384 resected NSCLC specimens from two hospitals in Beijing (BJ) and Chongqing (CQ) were collected. Using immunohistochemistry (IHC) staining on stored formalin-fixed paraffin-embedded (FFPE) surgical samples, we examined the expression levels of 75 critical proteins on BJ samples. Random forest algorithm (RFA) and support vector machines (SVM) computation were applied to identify protein signatures on 2/3 randomly assigned BJ samples. The identified signatures were tested on the remaining BJ samples, and were further validated with CQ independent cohort. A 6-protein signature for adenocarcinoma (ADC) and a 5-protein signature for squamous cell carcinoma (SCC) were identified from training sets and tested in testing sets. In independent validation with CQ cohort, patients can also be divided into high- and low-risk groups with significantly different median overall survivals by Kaplan-Meier analysis, both in ADC (31 months vs. 87 months, HR 2.81; P <  0.001) and SCC patients (27 months vs. not reached, HR 9.97; P <  0.001). Cox regression analysis showed that both signatures are independent prognostic indicators and outperformed TNM staging (ADC: adjusted HR 3.07 vs. 2.43, SCC: adjusted HR 7.84 vs. 2.24). Particularly, we found that only the ADC patients in high-risk group significantly benefited from adjuvant chemotherapy (P = 0.018). Both ADC and SCC protein signatures could effectively stratify the prognosis of NSCLC patients, and may support patient selection for adjuvant chemotherapy.

Autophagy-related prognostic signature for breast cancer.

PubMed

Gu, Yunyan; Li, Pengfei; Peng, Fuduan; Zhang, Mengmeng; Zhang, Yuanyuan; Liang, Haihai; Zhao, Wenyuan; Qi, Lishuang; Wang, Hongwei; Wang, Chenguang; Guo, Zheng

2016-03-01

Autophagy is a process that degrades intracellular constituents, such as long-lived or damaged proteins and organelles, to buffer metabolic stress under starvation conditions. Deregulation of autophagy is involved in the progression of cancer. However, the predictive value of autophagy for breast cancer prognosis remains unclear. First, based on gene expression profiling, we found that autophagy genes were implicated in breast cancer. Then, using the Cox proportional hazard regression model, we detected autophagy prognostic signature for breast cancer in a training dataset. We identified a set of eight autophagy genes (BCL2, BIRC5, EIF4EBP1, ERO1L, FOS, GAPDH, ITPR1 and VEGFA) that were significantly associated with overall survival in breast cancer. The eight autophagy genes were assigned as a autophagy-related prognostic signature for breast cancer. Based on the autophagy-related signature, the training dataset GSE21653 could be classified into high-risk and low-risk subgroups with significantly different survival times (HR = 2.72, 95% CI = (1.91, 3.87); P = 1.37 × 10(-5)). Inactivation of autophagy was associated with shortened survival of breast cancer patients. The prognostic value of the autophagy-related signature was confirmed in the testing dataset GSE3494 (HR = 2.12, 95% CI = (1.48, 3.03); P = 1.65 × 10(-3)) and GSE7390 (HR = 1.76, 95% CI = (1.22, 2.54); P = 9.95 × 10(-4)). Further analysis revealed that the prognostic value of the autophagy signature was independent of known clinical prognostic factors, including age, tumor size, grade, estrogen receptor status, progesterone receptor status, ERBB2 status, lymph node status and TP53 mutation status. Finally, we demonstrated that the autophagy signature could also predict distant metastasis-free survival for breast cancer. © 2015 Wiley Periodicals, Inc.

Neutron-encoded Signatures Enable Product Ion Annotation From Tandem Mass Spectra*

PubMed Central

Richards, Alicia L.; Vincent, Catherine E.; Guthals, Adrian; Rose, Christopher M.; Westphall, Michael S.; Bandeira, Nuno; Coon, Joshua J.

2013-01-01

We report the use of neutron-encoded (NeuCode) stable isotope labeling of amino acids in cell culture for the purpose of C-terminal product ion annotation. Two NeuCode labeling isotopologues of lysine, 13C615N2 and 2H8, which differ by 36 mDa, were metabolically embedded in a sample proteome, and the resultant labeled proteins were combined, digested, and analyzed via liquid chromatography and mass spectrometry. With MS/MS scan resolving powers of ∼50,000 or higher, product ions containing the C terminus (i.e. lysine) appear as a doublet spaced by exactly 36 mDa, whereas N-terminal fragments exist as a single m/z peak. Through theory and experiment, we demonstrate that over 90% of all y-type product ions have detectable doublets. We report on an algorithm that can extract these neutron signatures with high sensitivity and specificity. In other words, of 15,503 y-type product ion peaks, the y-type ion identification algorithm correctly identified 14,552 (93.2%) based on detection of the NeuCode doublet; 6.8% were misclassified (i.e. other ion types that were assigned as y-type products). Searching NeuCode labeled yeast with PepNovo+ resulted in a 34% increase in correct de novo identifications relative to searching through MS/MS only. We use this tool to simplify spectra prior to database searching, to sort unmatched tandem mass spectra for spectral richness, for correlation of co-fragmented ions to their parent precursor, and for de novo sequence identification. PMID:24043425

Feedback-related negativity codes outcome valence, but not outcome expectancy, during reversal learning.

PubMed

von Borries, A K L; Verkes, R J; Bulten, B H; Cools, R; de Bruijn, E R A

2013-12-01

Optimal behavior depends on the ability to assess the predictive value of events and to adjust behavior accordingly. Outcome processing can be studied by using its electrophysiological signatures--that is, the feedback-related negativity (FRN) and the P300. A prominent reinforcement-learning model predicts an FRN on negative prediction errors, as well as implying a role for the FRN in learning and the adaptation of behavior. However, these predictions have recently been challenged. Notably, studies so far have used tasks in which the outcomes have been contingent on the response. In these paradigms, the need to adapt behavioral responses is present only for negative, not for positive feedback. The goal of the present study was to investigate the effects of positive as well as negative violations of expectancy on FRN amplitudes, without the usual confound of behavioral adjustments. A reversal-learning task was employed in which outcome value and outcome expectancy were orthogonalized; that is, both positive and negative outcomes were equally unexpected. The results revealed a double dissociation, with effects of valence but not expectancy on the FRN and, conversely, effects of expectancy but not valence on the P300. While FRN amplitudes were largest for negative-outcome trials, irrespective of outcome expectancy, P300 amplitudes were largest for unexpected-outcome trials, irrespective of outcome valence. These FRN effects were interpreted to reflect an evaluation along a good-bad dimension, rather than reflecting a negative prediction error or a role in behavioral adaptation. By contrast, the P300 reflects the updating of information relevant for behavior in a changing context.

Cryptography Would Reveal Alterations In Photographs

NASA Technical Reports Server (NTRS)

Friedman, Gary L.

1995-01-01

Public-key decryption method proposed to guarantee authenticity of photographic images represented in form of digital files. In method, digital camera generates original data from image in standard public format; also produces coded signature to verify standard-format image data. Scheme also helps protect against other forms of lying, such as attaching false captions.

26 CFR 48.6412-1 - Floor stocks credit or refund.

Code of Federal Regulations, 2010 CFR

2010-04-01

...; and (D) The quantity of articles held by the dealer as floor stocks on the inventory date. (3) Actual... Revenue Code of 1954 with respect to the articles in my inventory on _____. (Name) By (Signature of... refund authorized by section 6412 for manufacturers excise taxes paid in respect of certain articles held...

The conservation and signatures of lincRNAs in Marek’s disease of chicken

USDA-ARS?s Scientific Manuscript database

Long intergenic non-coding RNAs (lincRNAs) associated with a number of cancers and other diseases have been identified in mammals, but they are still formidable to be comprehensively identified and characterized. Marek’s disease (MD) is a T cell lymphoma of chickens induced by Marek’s disease virus ...

The conservation and signatures of lincRNAs in Marek’s disease of chicken

USDA-ARS?s Scientific Manuscript database

Long intergenic non-coding RNAs (lincRNAs) associated with a number of cancers and other diseases have been identified in mammals, but they are still formidable to be comprehensively identified and characterized in chicken. Marek’s disease (MD) is a T cell lymphoma of chickens induced by Marek’s dis...

Establishing Malware Attribution and Binary Provenance Using Multicompilation Techniques

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

Ramshaw, M. J.

2017-07-28

Malware is a serious problem for computer systems and costs businesses and customers billions of dollars a year in addition to compromising their private information. Detecting malware is particularly difficult because malware source code can be compiled in many different ways and generate many different digital signatures, which causes problems for most anti-malware programs that rely on static signature detection. Our project uses a convolutional neural network to identify malware programs but these require large amounts of data to be effective. Towards that end, we gather thousands of source code files from publicly available programming contest sites and compile themmore » with several different compilers and flags. Building upon current research, we then transform these binary files into image representations and use them to train a long-term recurrent convolutional neural network that will eventually be used to identify how a malware binary was compiled. This information will include the compiler, version of the compiler and the options used in compilation, information which can be critical in determining where a malware program came from and even who authored it.« less

Optical Variability Signatures from Massive Black Hole Binaries

NASA Astrophysics Data System (ADS)

Kasliwal, Vishal P.; Frank, Koby Alexander; Lidz, Adam

2017-01-01

The hierarchical merging of dark matter halos and their associated galaxies should lead to a population of supermassive black hole binaries (MBHBs). We consider plausible optical variability signatures from MBHBs at sub-parsec separations and search for these using data from the Catalina Real-Time Transient Survey (CRTS). Specifically, we model the impact of relativistic Doppler beaming on the accretion disk emission from the less massive, secondary black hole. We explore whether this Doppler modulation may be separated from other sources of stochastic variability in the accretion flow around the MBHBs, which we describe as a damped random walk (DRW). In the simple case of a circular orbit, relativistic beaming leads to a series of broad peaks — located at multiples of the orbital frequency — in the fluctuation power spectrum. We extend our analysis to the case of elliptical orbits and discuss the effect of beaming on the flux power spectrum and auto-correlation function using simulations. We present a code to model an observed light curve as a stochastic DRW-type time series modulated by relativistic beaming and apply the code to CRTS data.

Integrated genomic analysis of recurrence-associated small non-coding RNAs in oesophageal cancer.

PubMed

Jang, Hee-Jin; Lee, Hyun-Sung; Burt, Bryan M; Lee, Geon Kook; Yoon, Kyong-Ah; Park, Yun-Yong; Sohn, Bo Hwa; Kim, Sang Bae; Kim, Moon Soo; Lee, Jong Mog; Joo, Jungnam; Kim, Sang Cheol; Yun, Ju Sik; Na, Kook Joo; Choi, Yoon-La; Park, Jong-Lyul; Kim, Seon-Young; Lee, Yong Sun; Han, Leng; Liang, Han; Mak, Duncan; Burks, Jared K; Zo, Jae Ill; Sugarbaker, David J; Shim, Young Mog; Lee, Ju-Seog

2017-02-01

Oesophageal squamous cell carcinoma (ESCC) is a heterogeneous disease with variable outcomes that are challenging to predict. A better understanding of the biology of ESCC recurrence is needed to improve patient care. Our goal was to identify small non-coding RNAs (sncRNAs) that could predict the likelihood of recurrence after surgical resection and to uncover potential molecular mechanisms that dictate clinical heterogeneity. We developed a robust prediction model for recurrence based on the analysis of the expression profile data of sncRNAs from 108 fresh frozen ESCC specimens as a discovery set and assessment of the associations between sncRNAs and recurrence-free survival (RFS). We also evaluated the mechanistic and therapeutic implications of sncRNA obtained through integrated analysis from multiple datasets. We developed a risk assessment score (RAS) for recurrence with three sncRNAs (microRNA (miR)-223, miR-1269a and nc886) whose expression was significantly associated with RFS in the discovery cohort (n=108). RAS was validated in an independent cohort of 512 patients. In multivariable analysis, RAS was an independent predictor of recurrence (HR, 2.27; 95% CI, 1.26 to 4.09; p=0.007). This signature implies the expression of ΔNp63 and multiple alterations of driver genes like PIK3CA. We suggested therapeutic potentials of immune checkpoint inhibitors in low-risk patients, and Polo-like kinase inhibitors, mammalian target of rapamycin (mTOR) inhibitors, and histone deacetylase inhibitors in high-risk patients. We developed an easy-to-use prognostic model with three sncRNAs as robust prognostic markers for postoperative recurrence of ESCC. We anticipate that such a stratified and systematic, tumour-specific biological approach will potentially contribute to significant improvement in ESCC treatment. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Evaluation of plasma proteomic data for Alzheimer disease state classification and for the prediction of progression from mild cognitive impairment to Alzheimer disease.

PubMed

Llano, Daniel A; Devanarayan, Viswanath; Simon, Adam J

2013-01-01

Previous studies that have examined the potential for plasma markers to serve as biomarkers for Alzheimer disease (AD) have studied single analytes and focused on the amyloid-β and τ isoforms and have failed to yield conclusive results. In this study, we performed a multivariate analysis of 146 plasma analytes (the Human DiscoveryMAP v 1.0 from Rules-Based Medicine) in 527 subjects with AD, mild cognitive impairment (MCI), or cognitively normal elderly subjects from the Alzheimer's Disease Neuroimaging Initiative database. We identified 4 different proteomic signatures, each using 5 to 14 analytes, that differentiate AD from control patients with sensitivity and specificity ranging from 74% to 85%. Five analytes were common to all 4 signatures: apolipoprotein A-II, apolipoprotein E, serum glutamic oxaloacetic transaminase, α-1-microglobulin, and brain natriuretic peptide. None of the signatures adequately predicted progression from MCI to AD over a 12- and 24-month period. A new panel of analytes, optimized to predict MCI to AD conversion, was able to provide 55% to 60% predictive accuracy. These data suggest that a simple panel of plasma analytes may provide an adjunctive tool to differentiate AD from controls, may provide mechanistic insights to the etiology of AD, but cannot adequately predict MCI to AD conversion.

KEA-71 Smart Current Signature Sensor (SCSS)

NASA Technical Reports Server (NTRS)

Perotti, Jose M.

2010-01-01

This slide presentation reviews the development and uses of the Smart Current Signature Sensor (SCSS), also known as the Valve Health Monitor (VHM) system. SCSS provides a way to not only monitor real-time the valve's operation in a non invasive manner, but also to monitor its health (Fault Detection and Isolation) and identify potential faults and/or degradation in the near future (Prediction/Prognosis). This technology approach is not only applicable for solenoid valves, and it could be extrapolated to other electrical components with repeatable electrical current signatures such as motors.

EPAs ToxCast Research Program: Developing Predictive Bioactivity Signatures for Chemicals

EPA Science Inventory

The international community needs better predictive tools for assessing the hazards and risks of chemicals. It is technically feasible to collect bioactivity data on virtually all chemicals of potential concern ToxCast is providing a proof of concept for obtaining predictive, b...

Muscle myeloid type I interferon gene expression may predict therapeutic responses to rituximab in myositis patients.

PubMed

Nagaraju, Kanneboyina; Ghimbovschi, Svetlana; Rayavarapu, Sree; Phadke, Aditi; Rider, Lisa G; Hoffman, Eric P; Miller, Frederick W

2016-09-01

To identify muscle gene expression patterns that predict rituximab responses and assess the effects of rituximab on muscle gene expression in PM and DM. In an attempt to understand the molecular mechanism of response and non-response to rituximab therapy, we performed Affymetrix gene expression array analyses on muscle biopsy specimens taken before and after rituximab therapy from eight PM and two DM patients in the Rituximab in Myositis study. We also analysed selected muscle-infiltrating cell phenotypes in these biopsies by immunohistochemical staining. Partek and Ingenuity pathway analyses assessed the gene pathways and networks. Myeloid type I IFN signature genes were expressed at higher levels at baseline in the skeletal muscle of rituximab responders than in non-responders, whereas classic non-myeloid IFN signature genes were expressed at higher levels in non-responders at baseline. Also, rituximab responders have a greater reduction of the myeloid and non-myeloid type I IFN signatures than non-responders. The decrease in the type I IFN signature following administration of rituximab may be associated with the decreases in muscle-infiltrating CD19(+) B cells and CD68(+) macrophages in responders. Our findings suggest that high levels of myeloid type I IFN gene expression in skeletal muscle predict responses to rituximab in PM/DM and that rituximab responders also have a greater decrease in the expression of these genes. These data add further evidence to recent studies defining the type I IFN signature as both a predictor of therapeutic responses and a biomarker of myositis disease activity. Published by Oxford University Press on behalf British Society for Rheumatology 2016. This work is written by US Government employees and is in the public domain in the US.

The molecular basis of breast cancer pathological phenotypes.

PubMed

Heng, Yujing J; Lester, Susan C; Tse, Gary Mk; Factor, Rachel E; Allison, Kimberly H; Collins, Laura C; Chen, Yunn-Yi; Jensen, Kristin C; Johnson, Nicole B; Jeong, Jong Cheol; Punjabi, Rahi; Shin, Sandra J; Singh, Kamaljeet; Krings, Gregor; Eberhard, David A; Tan, Puay Hoon; Korski, Konstanty; Waldman, Frederic M; Gutman, David A; Sanders, Melinda; Reis-Filho, Jorge S; Flanagan, Sydney R; Gendoo, Deena Ma; Chen, Gregory M; Haibe-Kains, Benjamin; Ciriello, Giovanni; Hoadley, Katherine A; Perou, Charles M; Beck, Andrew H

2017-02-01

The histopathological evaluation of morphological features in breast tumours provides prognostic information to guide therapy. Adjunct molecular analyses provide further diagnostic, prognostic and predictive information. However, there is limited knowledge of the molecular basis of morphological phenotypes in invasive breast cancer. This study integrated genomic, transcriptomic and protein data to provide a comprehensive molecular profiling of morphological features in breast cancer. Fifteen pathologists assessed 850 invasive breast cancer cases from The Cancer Genome Atlas (TCGA). Morphological features were significantly associated with genomic alteration, DNA methylation subtype, PAM50 and microRNA subtypes, proliferation scores, gene expression and/or reverse-phase protein assay subtype. Marked nuclear pleomorphism, necrosis, inflammation and a high mitotic count were associated with the basal-like subtype, and had a similar molecular basis. Omics-based signatures were constructed to predict morphological features. The association of morphology transcriptome signatures with overall survival in oestrogen receptor (ER)-positive and ER-negative breast cancer was first assessed by use of the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset; signatures that remained prognostic in the METABRIC multivariate analysis were further evaluated in five additional datasets. The transcriptomic signature of poorly differentiated epithelial tubules was prognostic in ER-positive breast cancer. No signature was prognostic in ER-negative breast cancer. This study provided new insights into the molecular basis of breast cancer morphological phenotypes. The integration of morphological with molecular data has the potential to refine breast cancer classification, predict response to therapy, enhance our understanding of breast cancer biology, and improve clinical management. This work is publicly accessible at www.dx.ai/tcga_breast. Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Comparison of Code Predictions to Test Measurements for Two Orifice Compensated Hydrostatic Bearings at High Reynolds Numbers

NASA Technical Reports Server (NTRS)

Keba, John E.

1996-01-01

Rotordynamic coefficients obtained from testing two different hydrostatic bearings are compared to values predicted by two different computer programs. The first set of test data is from a relatively long (L/D=1) orifice compensated hydrostatic bearing tested in water by Texas A&M University (TAMU Bearing No.9). The second bearing is a shorter (L/D=.37) bearing and was tested in a lower viscosity fluid by Rocketdyne Division of Rockwell (Rocketdyne 'Generic' Bearing) at similar rotating speeds and pressures. Computed predictions of bearing rotordynamic coefficients were obtained from the cylindrical seal code 'ICYL', one of the industrial seal codes developed for NASA-LeRC by Mechanical Technology Inc., and from the hydrodynamic bearing code 'HYDROPAD'. The comparison highlights the difference the bearing has on the accuracy of the predictions. The TAMU Bearing No. 9 test data is closely matched by the predictions obtained for the HYDROPAD code (except for added mass terms) whereas significant differences exist between the data from the Rocketdyne 'Generic' bearing the code predictions. The results suggest that some aspects of the fluid behavior in the shorter, higher Reynolds Number 'Generic' bearing may not be modeled accurately in the codes. The ICYL code predictions for flowrate and direct stiffness approximately equal those of HYDROPAD. Significant differences in cross-coupled stiffness and the damping terms were obtained relative to HYDROPAD and both sets of test data. Several observations are included concerning application of the ICYL code.

``Illuminating'' electron diffusion regions of collisionless magnetic reconnection using electron agyrotropy

NASA Astrophysics Data System (ADS)

Scudder, Jack; Daughton, William

2008-06-01

Agyrotropy is a scalar measure of the departure of the pressure tensor from cylindrical symmetry about the local magnetic field direction. Ordinarily electrons are well modeled as gyrotropic with very small agyrotropy. Intensified layers of electron agyrotropy are demonstrated to highlight the thin electron gyroradius scale boundary regions adjoining separatrices, X and O lines of full particle simulations of collisionless magnetic reconnection. Examples are presented to show these effects in antiparallel and guide field geometries, pair plasmas, and simulations at a variety of mass ratios, including a hydrogen plasma. Agyrotropy has been determined from the PIC pressure tensor using a new, fast algorithm developed to correct discreteness contributions to the apparent agyrotropy. As a local scalar diagnostic, agyrotropy is shown to be potentially useful with single spacecraft data to identify the crossing or proximity of electron scale current layers, thus providing a kinetic level diagnosis of a given layer's ability to be a possible site of the collisionless reconnection process. Such kinetic tools are certainly complimentary to the other macroscopic signatures of reconnection. Because of the extreme circumstances required for electron agyrotropy, detection of these signatures with framing macroscopic signatures might prove useful for the discovery of new reconnection sites in nature and 3-D codes of collisionless reconnection. The agyrotropy in the 2-D PIC codes reflect long-lived bulges on the distribution function that appear to be organized by the direction and size of slowly evolving perpendicular electric fields in these layers and are not consistent with gyrophase bunching.

Mechanizing chile peppers: Challenges and advances in transitioning harvest of New Mexico's signature crop

USDA-ARS?s Scientific Manuscript database

New Mexican-type chile (Capsicum annuum L.), often referred to as 'Anaheim', is the signature crop of New Mexico. Both the red and green (fully sized, but physiologically immature) crops are integral to the state's culture and economy. Lack of a predictable labor supply and higher input costs have p...

A dehydration-inducible gene in the truffle Tuber borchii identifies a novel group of dehydrins

PubMed Central

Abba', Simona; Ghignone, Stefano; Bonfante, Paola

2006-01-01

Background The expressed sequence tag M6G10 was originally isolated from a screening for differentially expressed transcripts during the reproductive stage of the white truffle Tuber borchii. mRNA levels for M6G10 increased dramatically during fruiting body maturation compared to the vegetative mycelial stage. Results Bioinformatics tools, phylogenetic analysis and expression studies were used to support the hypothesis that this sequence, named TbDHN1, is the first dehydrin (DHN)-like coding gene isolated in fungi. Homologs of this gene, all defined as "coding for hypothetical proteins" in public databases, were exclusively found in ascomycetous fungi and in plants. Although complete (or almost complete) fungal genomes and EST collections of some Basidiomycota and Glomeromycota are already available, DHN-like proteins appear to be represented only in Ascomycota. A new and previously uncharacterized conserved signature pattern was identified and proposed to Uniprot database as the main distinguishing feature of this new group of DHNs. Expression studies provide experimental evidence of a transcript induction of TbDHN1 during cellular dehydration. Conclusion Expression pattern and sequence similarities to known plant DHNs indicate that TbDHN1 is the first characterized DHN-like protein in fungi. The high similarity of TbDHN1 with homolog coding sequences implies the existence of a novel fungal/plant group of LEA Class II proteins characterized by a previously undescribed signature pattern. PMID:16512918

High-Lift Propeller Noise Prediction for a Distributed Electric Propulsion Flight Demonstrator

NASA Technical Reports Server (NTRS)

Nark, Douglas M.; Buning, Pieter G.; Jones, William T.; Derlaga, Joseph M.

2017-01-01

Over the past several years, the use of electric propulsion technologies within aircraft design has received increased attention. The characteristics of electric propulsion systems open up new areas of the aircraft design space, such as the use of distributed electric propulsion (DEP). In this approach, electric motors are placed in many different locations to achieve increased efficiency through integration of the propulsion system with the airframe. Under a project called Scalable Convergent Electric Propulsion Technology Operations Research (SCEPTOR), NASA is designing a flight demonstrator aircraft that employs many "high-lift propellers" distributed upstream of the wing leading edge and two cruise propellers (one at each wingtip). As the high-lift propellers are operational at low flight speeds (take-off/approach flight conditions), the impact of the DEP configuration on the aircraft noise signature is also an important design consideration. This paper describes efforts toward the development of a mulit-fidelity aerodynamic and acoustic methodology for DEP high-lift propeller aeroacoustic modeling. Specifically, the PAS, OVERFLOW 2, and FUN3D codes are used to predict the aerodynamic performance of a baseline high-lift propeller blade set. Blade surface pressure results from the aerodynamic predictions are then used with PSU-WOPWOP and the F1A module of the NASA second generation Aircraft NOise Prediction Program to predict the isolated high-lift propeller noise source. Comparisons of predictions indicate that general trends related to angle of attack effects at the blade passage frequency are captured well with the various codes. Results for higher harmonics of the blade passage frequency appear consistent for the CFD based methods. Conversely, evidence of the need for a study of the effects of increased azimuthal grid resolution on the PAS based results is indicated and will be pursued in future work. Overall, the results indicate that the computational approach is acceptable for fundamental assessment of low-noise high-lift propeller designs. The extent to which the various approaches may be used in a complementary manner will be further established as measured data becomes available for validation. Ultimately, it is anticipated that this combined approach may be used to provide realistic incident source fields for acoustic shielding/scattering studies on various aircraft configurations.

Novel immunohistochemistry-based signatures to predict metastatic site of triple-negative breast cancers.

PubMed

Klimov, Sergey; Rida, Padmashree Cg; Aleskandarany, Mohammed A; Green, Andrew R; Ellis, Ian O; Janssen, Emiel Am; Rakha, Emad A; Aneja, Ritu

2017-09-05

Although distant metastasis (DM) in breast cancer (BC) is the most lethal form of recurrence and the most common underlying cause of cancer related deaths, the outcome following the development of DM is related to the site of metastasis. Triple negative BC (TNBC) is an aggressive form of BC characterised by early recurrences and high mortality. Athough multiple variables can be used to predict the risk of metastasis, few markers can predict the specific site of metastasis. This study aimed at identifying a biomarker signature to predict particular sites of DM in TNBC. A clinically annotated series of 322 TNBC were immunohistochemically stained with 133 biomarkers relevant to BC, to develop multibiomarker models for predicting metastasis to the bone, liver, lung and brain. Patients who experienced metastasis to each site were compared with those who did not, by gradually filtering the biomarker set via a two-tailed t-test and Cox univariate analyses. Biomarker combinations were finally ranked based on statistical significance, and evaluated in multivariable analyses. Our final models were able to stratify TNBC patients into high risk groups that showed over 5, 6, 7 and 8 times higher risk of developing metastasis to the bone, liver, lung and brain, respectively, than low-risk subgroups. These models for predicting site-specific metastasis retained significance following adjustment for tumour size, patient age and chemotherapy status. Our novel IHC-based biomarkers signatures, when assessed in primary TNBC tumours, enable prediction of specific sites of metastasis, and potentially unravel biomarkers previously unknown in site tropism.

Infrared signature modelling of a rocket jet plume - comparison with flight measurements

NASA Astrophysics Data System (ADS)

Rialland, V.; Guy, A.; Gueyffier, D.; Perez, P.; Roblin, A.; Smithson, T.

2016-01-01

The infrared signature modelling of rocket plumes is a challenging problem involving rocket geometry, propellant composition, combustion modelling, trajectory calculations, fluid mechanics, atmosphere modelling, calculation of gas and particles radiative properties and of radiative transfer through the atmosphere. This paper presents ONERA simulation tools chained together to achieve infrared signature prediction, and the comparison of the estimated and measured signatures of an in-flight rocket plume. We consider the case of a solid rocket motor with aluminized propellant, the Black Brant sounding rocket. The calculation case reproduces the conditions of an experimental rocket launch, performed at White Sands in 1997, for which we obtained high quality infrared signature data sets from DRDC Valcartier. The jet plume is calculated using an in-house CFD software called CEDRE. The plume infrared signature is then computed on the spectral interval 1900-5000 cm-1 with a step of 5 cm-1. The models and their hypotheses are presented and discussed. Then the resulting plume properties, radiance and spectra are detailed. Finally, the estimated infrared signature is compared with the spectral imaging measurements. The discrepancies are analyzed and discussed.

Integrated MicroRNA and mRNA Signatures Associated with Survival in Triple Negative Breast Cancer

PubMed Central

Lovat, Francesca; Carasi, Stefania; Pulvirenti, Alfredo; Ferro, Alfredo; Alder, Hansjuerg; He, Gang; Vecchione, Andrea; Croce, Carlo M.; Shapiro, Charles L.; Huebner, Kay

2013-01-01

Triple negative breast cancer (TNBC) is a heterogeneous disease at the molecular, pathologic and clinical levels. To stratify TNBCs, we determined microRNA (miRNA) expression profiles, as well as expression profiles of a cancer-focused mRNA panel, in tumor, adjacent non-tumor (normal) and lymph node metastatic lesion (mets) tissues, from 173 women with TNBCs; we linked specific miRNA signatures to patient survival and used miRNA/mRNA anti-correlations to identify clinically and genetically different TNBC subclasses. We also assessed miRNA signatures as potential regulators of TNBC subclass-specific gene expression networks defined by expression of canonical signal pathways. Tissue specific miRNAs and mRNAs were identified for normal vs tumor vs mets comparisons. miRNA signatures correlated with prognosis were identified and predicted anti-correlated targets within the mRNA profile were defined. Two miRNA signatures (miR-16, 155, 125b, 374a and miR-16, 125b, 374a, 374b, 421, 655, 497) predictive of overall survival (P = 0.05) and distant-disease free survival (P = 0.009), respectively, were identified for patients 50 yrs of age or younger. By multivariate analysis the risk signatures were independent predictors for overall survival and distant-disease free survival. mRNA expression profiling, using the cancer-focused mRNA panel, resulted in clustering of TNBCs into 4 molecular subclasses with different expression signatures anti-correlated with the prognostic miRNAs. Our findings suggest that miRNAs play a key role in triple negative breast cancer through their ability to regulate fundamental pathways such as: cellular growth and proliferation, cellular movement and migration, Extra Cellular Matrix degradation. The results define miRNA expression signatures that characterize and contribute to the phenotypic diversity of TNBC and its metastasis. PMID:23405235

Integrated microRNA and mRNA signatures associated with survival in triple negative breast cancer.

PubMed

Cascione, Luciano; Gasparini, Pierluigi; Lovat, Francesca; Carasi, Stefania; Pulvirenti, Alfredo; Ferro, Alfredo; Alder, Hansjuerg; He, Gang; Vecchione, Andrea; Croce, Carlo M; Shapiro, Charles L; Huebner, Kay

2013-01-01

Triple negative breast cancer (TNBC) is a heterogeneous disease at the molecular, pathologic and clinical levels. To stratify TNBCs, we determined microRNA (miRNA) expression profiles, as well as expression profiles of a cancer-focused mRNA panel, in tumor, adjacent non-tumor (normal) and lymph node metastatic lesion (mets) tissues, from 173 women with TNBCs; we linked specific miRNA signatures to patient survival and used miRNA/mRNA anti-correlations to identify clinically and genetically different TNBC subclasses. We also assessed miRNA signatures as potential regulators of TNBC subclass-specific gene expression networks defined by expression of canonical signal pathways.Tissue specific miRNAs and mRNAs were identified for normal vs tumor vs mets comparisons. miRNA signatures correlated with prognosis were identified and predicted anti-correlated targets within the mRNA profile were defined. Two miRNA signatures (miR-16, 155, 125b, 374a and miR-16, 125b, 374a, 374b, 421, 655, 497) predictive of overall survival (P = 0.05) and distant-disease free survival (P = 0.009), respectively, were identified for patients 50 yrs of age or younger. By multivariate analysis the risk signatures were independent predictors for overall survival and distant-disease free survival. mRNA expression profiling, using the cancer-focused mRNA panel, resulted in clustering of TNBCs into 4 molecular subclasses with different expression signatures anti-correlated with the prognostic miRNAs. Our findings suggest that miRNAs play a key role in triple negative breast cancer through their ability to regulate fundamental pathways such as: cellular growth and proliferation, cellular movement and migration, Extra Cellular Matrix degradation. The results define miRNA expression signatures that characterize and contribute to the phenotypic diversity of TNBC and its metastasis.

Signatures of Subacute Potentially Catastrophic Illness in the ICU: Model Development and Validation.

PubMed

Moss, Travis J; Lake, Douglas E; Calland, J Forrest; Enfield, Kyle B; Delos, John B; Fairchild, Karen D; Moorman, J Randall

2016-09-01

Patients in ICUs are susceptible to subacute potentially catastrophic illnesses such as respiratory failure, sepsis, and hemorrhage that present as severe derangements of vital signs. More subtle physiologic signatures may be present before clinical deterioration, when treatment might be more effective. We performed multivariate statistical analyses of bedside physiologic monitoring data to identify such early subclinical signatures of incipient life-threatening illness. We report a study of model development and validation of a retrospective observational cohort using resampling (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis type 1b internal validation) and a study of model validation using separate data (type 2b internal/external validation). University of Virginia Health System (Charlottesville), a tertiary-care, academic medical center. Critically ill patients consecutively admitted between January 2009 and June 2015 to either the neonatal, surgical/trauma/burn, or medical ICUs with available physiologic monitoring data. None. We analyzed 146 patient-years of vital sign and electrocardiography waveform time series from the bedside monitors of 9,232 ICU admissions. Calculations from 30-minute windows of the physiologic monitoring data were made every 15 minutes. Clinicians identified 1,206 episodes of respiratory failure leading to urgent unplanned intubation, sepsis, or hemorrhage leading to multi-unit transfusions from systematic individual chart reviews. Multivariate models to predict events up to 24 hours prior had internally validated C-statistics of 0.61-0.88. In adults, physiologic signatures of respiratory failure and hemorrhage were distinct from each other but externally consistent across ICUs. Sepsis, on the other hand, demonstrated less distinct and inconsistent signatures. Physiologic signatures of all neonatal illnesses were similar. Subacute potentially catastrophic illnesses in three diverse ICU populations have physiologic signatures that are detectable in the hours preceding clinical detection and intervention. Detection of such signatures can draw attention to patients at highest risk, potentially enabling earlier intervention and better outcomes.

Prediction of plant lncRNA by ensemble machine learning classifiers.

PubMed

Simopoulos, Caitlin M A; Weretilnyk, Elizabeth A; Golding, G Brian

2018-05-02

In plants, long non-protein coding RNAs are believed to have essential roles in development and stress responses. However, relative to advances on discerning biological roles for long non-protein coding RNAs in animal systems, this RNA class in plants is largely understudied. With comparatively few validated plant long non-coding RNAs, research on this potentially critical class of RNA is hindered by a lack of appropriate prediction tools and databases. Supervised learning models trained on data sets of mostly non-validated, non-coding transcripts have been previously used to identify this enigmatic RNA class with applications largely focused on animal systems. Our approach uses a training set comprised only of empirically validated long non-protein coding RNAs from plant, animal, and viral sources to predict and rank candidate long non-protein coding gene products for future functional validation. Individual stochastic gradient boosting and random forest classifiers trained on only empirically validated long non-protein coding RNAs were constructed. In order to use the strengths of multiple classifiers, we combined multiple models into a single stacking meta-learner. This ensemble approach benefits from the diversity of several learners to effectively identify putative plant long non-coding RNAs from transcript sequence features. When the predicted genes identified by the ensemble classifier were compared to those listed in GreeNC, an established plant long non-coding RNA database, overlap for predicted genes from Arabidopsis thaliana, Oryza sativa and Eutrema salsugineum ranged from 51 to 83% with the highest agreement in Eutrema salsugineum. Most of the highest ranking predictions from Arabidopsis thaliana were annotated as potential natural antisense genes, pseudogenes, transposable elements, or simply computationally predicted hypothetical protein. Due to the nature of this tool, the model can be updated as new long non-protein coding transcripts are identified and functionally verified. This ensemble classifier is an accurate tool that can be used to rank long non-protein coding RNA predictions for use in conjunction with gene expression studies. Selection of plant transcripts with a high potential for regulatory roles as long non-protein coding RNAs will advance research in the elucidation of long non-protein coding RNA function.

Efficient temporal and interlayer parameter prediction for weighted prediction in scalable high efficiency video coding

NASA Astrophysics Data System (ADS)

Tsang, Sik-Ho; Chan, Yui-Lam; Siu, Wan-Chi

2017-01-01

Weighted prediction (WP) is an efficient video coding tool that was introduced since the establishment of the H.264/AVC video coding standard, for compensating the temporal illumination change in motion estimation and compensation. WP parameters, including a multiplicative weight and an additive offset for each reference frame, are required to be estimated and transmitted to the decoder by slice header. These parameters cause extra bits in the coded video bitstream. High efficiency video coding (HEVC) provides WP parameter prediction to reduce the overhead. Therefore, WP parameter prediction is crucial to research works or applications, which are related to WP. Prior art has been suggested to further improve the WP parameter prediction by implicit prediction of image characteristics and derivation of parameters. By exploiting both temporal and interlayer redundancies, we propose three WP parameter prediction algorithms, enhanced implicit WP parameter, enhanced direct WP parameter derivation, and interlayer WP parameter, to further improve the coding efficiency of HEVC. Results show that our proposed algorithms can achieve up to 5.83% and 5.23% bitrate reduction compared to the conventional scalable HEVC in the base layer for SNR scalability and 2× spatial scalability, respectively.

Adaptive evolution of the matrix extracellular phosphoglycoprotein in mammals

PubMed Central

2011-01-01

Background Matrix extracellular phosphoglycoprotein (MEPE) belongs to a family of small integrin-binding ligand N-linked glycoproteins (SIBLINGs) that play a key role in skeleton development, particularly in mineralization, phosphate regulation and osteogenesis. MEPE associated disorders cause various physiological effects, such as loss of bone mass, tumors and disruption of renal function (hypophosphatemia). The study of this developmental gene from an evolutionary perspective could provide valuable insights on the adaptive diversification of morphological phenotypes in vertebrates. Results Here we studied the adaptive evolution of the MEPE gene in 26 Eutherian mammals and three birds. The comparative genomic analyses revealed a high degree of evolutionary conservation of some coding and non-coding regions of the MEPE gene across mammals indicating a possible regulatory or functional role likely related with mineralization and/or phosphate regulation. However, the majority of the coding region had a fast evolutionary rate, particularly within the largest exon (1467 bp). Rodentia and Scandentia had distinct substitution rates with an increased accumulation of both synonymous and non-synonymous mutations compared with other mammalian lineages. Characteristics of the gene (e.g. biochemical, evolutionary rate, and intronic conservation) differed greatly among lineages of the eight mammalian orders. We identified 20 sites with significant positive selection signatures (codon and protein level) outside the main regulatory motifs (dentonin and ASARM) suggestive of an adaptive role. Conversely, we find three sites under selection in the signal peptide and one in the ASARM motif that were supported by at least one selection model. The MEPE protein tends to accumulate amino acids promoting disorder and potential phosphorylation targets. Conclusion MEPE shows a high number of selection signatures, revealing the crucial role of positive selection in the evolution of this SIBLING member. The selection signatures were found mainly outside the functional motifs, reinforcing the idea that other regions outside the dentonin and the ASARM might be crucial for the function of the protein and future studies should be undertaken to understand its importance. PMID:22103247

Signatures of criticality arise from random subsampling in simple population models.

PubMed

Nonnenmacher, Marcel; Behrens, Christian; Berens, Philipp; Bethge, Matthias; Macke, Jakob H

2017-10-01

The rise of large-scale recordings of neuronal activity has fueled the hope to gain new insights into the collective activity of neural ensembles. How can one link the statistics of neural population activity to underlying principles and theories? One attempt to interpret such data builds upon analogies to the behaviour of collective systems in statistical physics. Divergence of the specific heat-a measure of population statistics derived from thermodynamics-has been used to suggest that neural populations are optimized to operate at a "critical point". However, these findings have been challenged by theoretical studies which have shown that common inputs can lead to diverging specific heat. Here, we connect "signatures of criticality", and in particular the divergence of specific heat, back to statistics of neural population activity commonly studied in neural coding: firing rates and pairwise correlations. We show that the specific heat diverges whenever the average correlation strength does not depend on population size. This is necessarily true when data with correlations is randomly subsampled during the analysis process, irrespective of the detailed structure or origin of correlations. We also show how the characteristic shape of specific heat capacity curves depends on firing rates and correlations, using both analytically tractable models and numerical simulations of a canonical feed-forward population model. To analyze these simulations, we develop efficient methods for characterizing large-scale neural population activity with maximum entropy models. We find that, consistent with experimental findings, increases in firing rates and correlation directly lead to more pronounced signatures. Thus, previous reports of thermodynamical criticality in neural populations based on the analysis of specific heat can be explained by average firing rates and correlations, and are not indicative of an optimized coding strategy. We conclude that a reliable interpretation of statistical tests for theories of neural coding is possible only in reference to relevant ground-truth models.

DRA/NASA/ONERA Collaboration on Icing Research. Part 2; Prediction of Airfoil Ice Accretion

NASA Technical Reports Server (NTRS)

Wright, William B.; Gent, R. W.; Guffond, Didier

1997-01-01

This report presents results from a joint study by DRA, NASA, and ONERA for the purpose of comparing, improving, and validating the aircraft icing computer codes developed by each agency. These codes are of three kinds: (1) water droplet trajectory prediction, (2) ice accretion modeling, and (3) transient electrothermal deicer analysis. In this joint study, the agencies compared their code predictions with each other and with experimental results. These comparison exercises were published in three technical reports, each with joint authorship. DRA published and had first authorship of Part 1 - Droplet Trajectory Calculations, NASA of Part 2 - Ice Accretion Prediction, and ONERA of Part 3 - Electrothermal Deicer Analysis. The results cover work done during the period from August 1986 to late 1991. As a result, all of the information in this report is dated. Where necessary, current information is provided to show the direction of current research. In this present report on ice accretion, each agency predicted ice shapes on two dimensional airfoils under icing conditions for which experimental ice shapes were available. In general, all three codes did a reasonable job of predicting the measured ice shapes. For any given experimental condition, one of the three codes predicted the general ice features (i.e., shape, impingement limits, mass of ice) somewhat better than did the other two. However, no single code consistently did better than the other two over the full range of conditions examined, which included rime, mixed, and glaze ice conditions. In several of the cases, DRA showed that the user's knowledge of icing can significantly improve the accuracy of the code prediction. Rime ice predictions were reasonably accurate and consistent among the codes, because droplets freeze on impact and the freezing model is simple. Glaze ice predictions were less accurate and less consistent among the codes, because the freezing model is more complex and is critically dependent upon unsubstantiated heat transfer and surface roughness models. Thus, heat transfer prediction methods used in the codes became the subject for a separate study in this report to compare predicted heat transfer coefficients with a limited experimental database of heat transfer coefficients for cylinders with simulated glaze and rime ice shapes. The codes did a good job of predicting heat transfer coefficients near the stagnation region of the ice shapes. But in the region of the ice horns, all three codes predicted heat transfer coefficients considerably higher than the measured values. An important conclusion of this study is that further research is needed to understand the finer detail of of the glaze ice accretion process and to develop improved glaze ice accretion models.

Modeling of Light Reflection from Human Skin

NASA Astrophysics Data System (ADS)

Delgado, J. A.; Cornejo, A.; Rivas-Silva, J. F.; Rodríguez, E. E.

2006-09-01

In this work a two-layer model is used to simulate the spectral reflectance of adult human skin. We report and discuss diffuse reflectance spectra of this model for three values of the volume fraction of melanosomes fme, namely a) lightly pigmented skin fme = 4%, b) moderately pigmented skin fme = 14% and c) heavily pigmented skin fme = 30% at a volume fraction of blood fbl = 0.2%. We also considered the modeling of reflectance spectra for two values of fbl (0.2% and 1%) with fme = 4%. Both simulations were done in the 400-700 nm spectral range using the Monte Carlo simulation code MCML in standard C. Results showed that the principal signatures of human skin reflectance spectrum are obtained with this model and that it could be of valuable use to made predictions of diffuse reflectance of human skin for different values of the parameters related to skin characterization. These parameters can be associated to distinct medical conditions, such as erythema, jaundice, etc.

The Spirodela polyrhiza genome reveals insights into its neotenous reduction fast growth and aquatic lifestyle

PubMed Central

Wang, W.; Haberer, G.; Gundlach, H.; Gläßer, C.; Nussbaumer, T.; Luo, M.C.; Lomsadze, A.; Borodovsky, M.; Kerstetter, R.A.; Shanklin, J.; Byrant, D.W.; Mockler, T.C.; Appenroth, K.J.; Grimwood, J.; Jenkins, J.; Chow, J.; Choi, C.; Adam, C.; Cao, X.-H.; Fuchs, J.; Schubert, I.; Rokhsar, D.; Schmutz, J.; Michael, T.P.; Mayer, K.F.X.; Messing, J

2014-01-01

The subfamily of the Lemnoideae belongs to a different order than other monocotyledonous species that have been sequenced and comprises aquatic plants that grow rapidly on the water surface. Here we select Spirodela polyrhiza for whole-genome sequencing. We show that Spirodela has a genome with no signs of recent retrotranspositions but signatures of two ancient whole-genome duplications, possibly 95 million years ago (mya), older than those in Arabidopsis and rice. Its genome has only 19,623 predicted protein-coding genes, which is 28% less than the dicotyledonous Arabidopsis thaliana and 50% less than monocotyledonous rice. We propose that at least in part, the neotenous reduction of these aquatic plants is based on readjusted copy numbers of promoters and repressors of the juvenile-to-adult transition. The Spirodela genome, along with its unique biology and physiology, will stimulate new insights into environmental adaptation, ecology, evolution and plant development, and will be instrumental for future bioenergy applications. PMID:24548928

Hard X-ray Detectability of Small Impulsive Heating Events in the Solar Corona

NASA Astrophysics Data System (ADS)

Glesener, L.; Klimchuk, J. A.; Bradshaw, S. J.; Marsh, A.; Krucker, S.; Christe, S.

2015-12-01

Impulsive heating events ("nanoflares") are a candidate to supply the solar corona with its ~2 MK temperature. These transient events can be studied using extreme ultraviolet and soft X-ray observations, among others. However, the impulsive events may occur in tenuous loops on small enough timescales that the heating is essentially not observed due to ionization timescales, and only the cooling phase is observed. Bremsstrahlung hard X-rays could serve as a more direct and prompt indicator of transient heating events. A hard X-ray spacecraft based on the direct-focusing technology pioneered by the Focusing Optics X-ray Solar Imager (FOXSI) sounding rocket could search for these direct signatures. In this work, we use the hydrodynamical EBTEL code to simulate differential emission measures produced by individual heating events and by ensembles of such events. We then directly predict hard X-ray spectra and consider their observability by a future spaceborne FOXSI, and also by the RHESSI and NuSTAR spacecraft.

Post-analysis report on Chesapeake Bay data processing. [spectral analysis and recognition computer signature extension

NASA Technical Reports Server (NTRS)

Thomson, F.

1972-01-01

The additional processing performed on data collected over the Rhode River Test Site and Forestry Site in November 1970 is reported. The techniques and procedures used to obtain the processed results are described. Thermal data collected over three approximately parallel lines of the site were contoured, and the results color coded, for the purpose of delineating important scene constituents and to identify trees attacked by pine bark beetles. Contouring work and histogram preparation are reviewed and the important conclusions from the spectral analysis and recognition computer (SPARC) signature extension work are summarized. The SPARC setup and processing records are presented and recommendations are made for future data collection over the site.

The Design of Integrated Information System for High Voltage Metering Lab

NASA Astrophysics Data System (ADS)

Ma, Yan; Yang, Yi; Xu, Guangke; Gu, Chao; Zou, Lida; Yang, Feng

2018-01-01

With the development of smart grid, intelligent and informatization management of high-voltage metering lab become increasingly urgent. In the paper we design an integrated information system, which automates the whole transactions from accepting instruments, make experiments, generating report, report signature to instrument claims. Through creating database for all the calibrated instruments, using two-dimensional code, integrating report templates in advance, establishing bookmarks and online transmission of electronical signatures, our manual procedures reduce largely. These techniques simplify the complex process of account management and report transmission. After more than a year of operation, our work efficiency improves about forty percent averagely, and its accuracy rate and data reliability are much higher as well.

Flowfield Comparisons from Three Navier-Stokes Solvers for an Axisymmetric Separate Flow Jet

NASA Technical Reports Server (NTRS)

Koch, L. Danielle; Bridges, James; Khavaran, Abbas

2002-01-01

To meet new noise reduction goals, many concepts to enhance mixing in the exhaust jets of turbofan engines are being studied. Accurate steady state flowfield predictions from state-of-the-art computational fluid dynamics (CFD) solvers are needed as input to the latest noise prediction codes. The main intent of this paper was to ascertain that similar Navier-Stokes solvers run at different sites would yield comparable results for an axisymmetric two-stream nozzle case. Predictions from the WIND and the NPARC codes are compared to previously reported experimental data and results from the CRAFT Navier-Stokes solver. Similar k-epsilon turbulence models were employed in each solver, and identical computational grids were used. Agreement between experimental data and predictions from each code was generally good for mean values. All three codes underpredict the maximum value of turbulent kinetic energy. The predicted locations of the maximum turbulent kinetic energy were farther downstream than seen in the data. A grid study was conducted using the WIND code, and comments about convergence criteria and grid requirements for CFD solutions to be used as input for noise prediction computations are given. Additionally, noise predictions from the MGBK code, using the CFD results from the CRAFT code, NPARC, and WIND as input are compared to data.

Coding tools investigation for next generation video coding based on HEVC

NASA Astrophysics Data System (ADS)

Chen, Jianle; Chen, Ying; Karczewicz, Marta; Li, Xiang; Liu, Hongbin; Zhang, Li; Zhao, Xin

2015-09-01

The new state-of-the-art video coding standard, H.265/HEVC, has been finalized in 2013 and it achieves roughly 50% bit rate saving compared to its predecessor, H.264/MPEG-4 AVC. This paper provides the evidence that there is still potential for further coding efficiency improvements. A brief overview of HEVC is firstly given in the paper. Then, our improvements on each main module of HEVC are presented. For instance, the recursive quadtree block structure is extended to support larger coding unit and transform unit. The motion information prediction scheme is improved by advanced temporal motion vector prediction, which inherits the motion information of each small block within a large block from a temporal reference picture. Cross component prediction with linear prediction model improves intra prediction and overlapped block motion compensation improves the efficiency of inter prediction. Furthermore, coding of both intra and inter prediction residual is improved by adaptive multiple transform technique. Finally, in addition to deblocking filter and SAO, adaptive loop filter is applied to further enhance the reconstructed picture quality. This paper describes above-mentioned techniques in detail and evaluates their coding performance benefits based on the common test condition during HEVC development. The simulation results show that significant performance improvement over HEVC standard can be achieved, especially for the high resolution video materials.

Development and verification of NRC`s single-rod fuel performance codes FRAPCON-3 AND FRAPTRAN

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

Beyer, C.E.; Cunningham, M.E.; Lanning, D.D.

1998-03-01

The FRAPCON and FRAP-T code series, developed in the 1970s and early 1980s, are used by the US Nuclear Regulatory Commission (NRC) to predict fuel performance during steady-state and transient power conditions, respectively. Both code series are now being updated by Pacific Northwest National Laboratory to improve their predictive capabilities at high burnup levels. The newest versions of the codes are called FRAPCON-3 and FRAPTRAN. The updates to fuel property and behavior models are focusing on providing best estimate predictions under steady-state and fast transient power conditions up to extended fuel burnups (> 55 GWd/MTU). Both codes will be assessedmore » against a data base independent of the data base used for code benchmarking and an estimate of code predictive uncertainties will be made based on comparisons to the benchmark and independent data bases.« less

Classifying lower grade glioma cases according to whole genome gene expression.

PubMed

Chen, Baoshi; Liang, Tingyu; Yang, Pei; Wang, Haoyuan; Liu, Yanwei; Yang, Fan; You, Gan

2016-11-08

To identify a gene-based signature as a novel prognostic model in lower grade gliomas. A gene signature developed from HOXA7, SLC2A4RG and MN1 could segregate patients into low and high risk score groups with different overall survival (OS), and was validated in TCGA RNA-seq and GSE16011 mRNA array datasets. Receiver operating characteristic (ROC) was performed to show that the three-gene signature was more sensitive and specific than histology, grade, age, IDH1 mutation and 1p/19q co-deletion. Gene Set Enrichment Analysis (GSEA) and GO analysis showed high-risk samples were associated with tumor associated macrophages (TAMs) and highly invasive phenotypes. Moreover, HOXA7-siRNA inhibited migration and invasion in vitro, and downregulated MMP9 at the protein level in U251 glioma cells. A cohort of 164 glioma specimens from the Chinese Glioma Genome Atlas (CGGA) array database were assessed as the training group. TCGA RNA-seq and GSE16011 mRNA array datasets were used for validation. Regression analyses and linear risk score assessment were performed for the identification of the three-gene signature comprising HOXA7, SLC2A4RG and MN1. We established a three-gene signature for lower grade gliomas, which could independently predict overall survival (OS) of lower grade glioma patients with higher sensitivity and specificity compared with other clinical characteristics. These findings indicate that the three-gene signature is a new prognostic model that could provide improved OS prediction and accurate therapies for lower grade glioma patients.

Influence of flowfield and vehicle parameters on engineering aerothermal methods

NASA Technical Reports Server (NTRS)

Wurster, Kathryn E.; Zoby, E. Vincent; Thompson, Richard A.

1989-01-01

The reliability and flexibility of three engineering codes used in the aerosphace industry (AEROHEAT, INCHES, and MINIVER) were investigated by comparing the results of these codes with Reentry F flight data and ground-test heat-transfer data for a range of cone angles, and with the predictions obtained using the detailed VSL3D code; the engineering solutions were also compared. In particular, the impact of several vehicle and flow-field parameters on the heat transfer and the capability of the engineering codes to predict these results were determined. It was found that entropy, pressure gradient, nose bluntness, gas chemistry, and angle of attack all affect heating levels. A comparison of the results of the three engineering codes with Reentry F flight data and with the predictions obtained of the VSL3D code showed a very good agreement in the regions of the applicability of the codes. It is emphasized that the parameters used in this study can significantly influence the actual heating levels and the prediction capability of a code.

The Cortical Organization of Speech Processing: Feedback Control and Predictive Coding the Context of a Dual-Stream Model

ERIC Educational Resources Information Center

Hickok, Gregory

2012-01-01

Speech recognition is an active process that involves some form of predictive coding. This statement is relatively uncontroversial. What is less clear is the source of the prediction. The dual-stream model of speech processing suggests that there are two possible sources of predictive coding in speech perception: the motor speech system and the…

A high temperature fatigue life prediction computer code based on the total strain version of StrainRange Partitioning (SRP)

NASA Technical Reports Server (NTRS)

Mcgaw, Michael A.; Saltsman, James F.

1993-01-01

A recently developed high-temperature fatigue life prediction computer code is presented and an example of its usage given. The code discussed is based on the Total Strain version of Strainrange Partitioning (TS-SRP). Included in this code are procedures for characterizing the creep-fatigue durability behavior of an alloy according to TS-SRP guidelines and predicting cyclic life for complex cycle types for both isothermal and thermomechanical conditions. A reasonably extensive materials properties database is included with the code.

Stochastic Plume Simulations for the Fukushima Accident and the Deep Water Horizon Oil Spill

NASA Astrophysics Data System (ADS)

Coelho, E.; Peggion, G.; Rowley, C.; Hogan, P.

2012-04-01

The Fukushima Dai-ichi power plant suffered damage leading to radioactive contamination of coastal waters. Major issues in characterizing the extent of the affected waters were a poor knowledge of the radiation released to the coastal waters and the rather complex coastal dynamics of the region, not deterministically captured by the available prediction systems. Equivalently, during the Gulf of Mexico Deep Water Horizon oil platform accident in April 2010, significant amounts of oil and gas were released from the ocean floor. For this case, issues in mapping and predicting the extent of the affected waters in real-time were a poor knowledge of the actual amounts of oil reaching the surface and the fact that coastal dynamics over the region were not deterministically captured by the available prediction systems. To assess the ocean regions and times that were most likely affected by these accidents while capturing the above sources of uncertainty, ensembles of the Navy Coastal Ocean Model (NCOM) were configured over the two regions (NE Japan and Northern Gulf of Mexico). For the Fukushima case tracers were released on each ensemble member; their locations at each instant provided reference positions of water volumes where the signature of water released from the plant could be found. For the Deep Water Horizon oil spill case each ensemble member was coupled with a diffusion-advection solution to estimate possible scenarios of oil concentrations using perturbed estimates of the released amounts as the source terms at the surface. Stochastic plumes were then defined using a Risk Assessment Code (RAC) analysis that associates a number from 1 to 5 to each grid point, determined by the likelihood of having tracer particle within short ranges (for the Fukushima case), hence defining the high risk areas and those recommended for monitoring. For the Oil Spill case the RAC codes were determined by the likelihood of reaching oil concentrations as defined in the Bonn Agreement Oil Appearance Code. The likelihoods were taken in both cases from probability distribution functions derived from the ensemble runs. Results were compared with a control-deterministic solution and checked against available reports to assess their skill in capturing the actual observed plumes and other in-situ data, as well as their relevance for planning surveys and reconnaissance flights for both cases.

TransCONFIRM: Identification of a Genetic Signature of Response to Fulvestrant in Advanced Hormone Receptor-Positive Breast Cancer.

PubMed

Jeselsohn, Rinath; Barry, William T; Migliaccio, Ilenia; Biagioni, Chiara; Zhao, Jin; De Tribolet-Hardy, Jonas; Guarducci, Cristina; Bonechi, Martina; Laing, Naomi; Winer, Eric P; Brown, Myles; Leo, Angelo Di; Malorni, Luca

2016-12-01

Fulvestrant is an estrogen receptor (ER) antagonist and an approved treatment for metastatic estrogen receptor-positive (ER + ) breast cancer. With the exception of ER levels, there are no established predictive biomarkers of response to single-agent fulvestrant. We attempted to identify a gene signature of response to fulvestrant in advanced breast cancer. Primary tumor samples from 134 patients enrolled in the phase III CONFIRM study of patients with metastatic ER + breast cancer comparing treatment with either 250 mg or 500 mg fulvestrant were collected for genome-wide transcriptomic analysis. Gene expression profiling was performed using Affymetrix microarrays. An exploratory analysis was performed to identify biologic pathways and new signatures associated with response to fulvestrant. Pathway analysis demonstrated that increased EGF pathway and FOXA1 transcriptional signaling is associated with decreased response to fulvestrant. Using a multivariate Cox model, we identified a novel set of 37 genes with an expression that is independently associated with progression-free survival (PFS). TFAP2C, a known regulator of ER activity, was ranked second in this gene set, and high expression was associated with a decreased response to fulvestrant. The negative predictive value of TFAP2C expression at the protein level was confirmed by IHC. We identified biologic pathways and a novel gene signature in primary ER + breast cancers that predicts for response to treatment in the CONFIRM study. These results suggest potential new therapeutic targets and warrant further validation as predictive biomarkers of fulvestrant treatment in metastatic breast cancer. Clin Cancer Res; 22(23); 5755-64. ©2016 AACR. ©2016 American Association for Cancer Research.

RIDES: Robust Intrusion Detection System for IP-Based Ubiquitous Sensor Networks

PubMed Central

Amin, Syed Obaid; Siddiqui, Muhammad Shoaib; Hong, Choong Seon; Lee, Sungwon

2009-01-01

The IP-based Ubiquitous Sensor Network (IP-USN) is an effort to build the “Internet of things”. By utilizing IP for low power networks, we can benefit from existing well established tools and technologies of IP networks. Along with many other unresolved issues, securing IP-USN is of great concern for researchers so that future market satisfaction and demands can be met. Without proper security measures, both reactive and proactive, it is hard to envisage an IP-USN realm. In this paper we present a design of an IDS (Intrusion Detection System) called RIDES (Robust Intrusion DEtection System) for IP-USN. RIDES is a hybrid intrusion detection system, which incorporates both Signature and Anomaly based intrusion detection components. For signature based intrusion detection this paper only discusses the implementation of distributed pattern matching algorithm with the help of signature-code, a dynamically created attack-signature identifier. Other aspects, such as creation of rules are not discussed. On the other hand, for anomaly based detection we propose a scoring classifier based on the SPC (Statistical Process Control) technique called CUSUM charts. We also investigate the settings and their effects on the performance of related parameters for both of the components. PMID:22412321

RIDES: Robust Intrusion Detection System for IP-Based Ubiquitous Sensor Networks.

PubMed

Amin, Syed Obaid; Siddiqui, Muhammad Shoaib; Hong, Choong Seon; Lee, Sungwon

2009-01-01

The IP-based Ubiquitous Sensor Network (IP-USN) is an effort to build the "Internet of things". By utilizing IP for low power networks, we can benefit from existing well established tools and technologies of IP networks. Along with many other unresolved issues, securing IP-USN is of great concern for researchers so that future market satisfaction and demands can be met. Without proper security measures, both reactive and proactive, it is hard to envisage an IP-USN realm. In this paper we present a design of an IDS (Intrusion Detection System) called RIDES (Robust Intrusion DEtection System) for IP-USN. RIDES is a hybrid intrusion detection system, which incorporates both Signature and Anomaly based intrusion detection components. For signature based intrusion detection this paper only discusses the implementation of distributed pattern matching algorithm with the help of signature-code, a dynamically created attack-signature identifier. Other aspects, such as creation of rules are not discussed. On the other hand, for anomaly based detection we propose a scoring classifier based on the SPC (Statistical Process Control) technique called CUSUM charts. We also investigate the settings and their effects on the performance of related parameters for both of the components.

A simulation study of fast neutron interrogation for standoff detection of improvised explosive devices

NASA Astrophysics Data System (ADS)

Heider, S. A.; Dunn, W. L.

2015-11-01

The signature-based radiation-scanning technique utilizes radiation detector responses, called "signatures," and compares these to "templates" in order to differentiate targets that contain certain materials, such as explosives or drugs, from those that do not. Our investigations are aimed at the detection of nitrogen-rich explosives contained in improvised explosive devices. We use the term "clutter" to refer to any non-explosive materials with which the interrogating radiation may interact between source and detector. To deal with the many target types and clutter configurations that may be encountered in the field, the use of "artificial templates" is proposed. The MCNP code was used to simulate 14.1 MeV neutron source beams incident on one type of target containing various clutter and sample materials. Signatures due to inelastic-scatter and prompt-capture gamma rays from hydrogen, carbon, nitrogen, and oxygen and two scattered neutron signatures were considered. Targets containing explosive materials in the presence of clutter were able to be identified from targets that contained only non-explosive ("inert") materials. This study demonstrates that a finite number of artificial templates is sufficient for IED detection with fairly good sensitivity and specificity.

Statistical Analysis of CFD Solutions from the Third AIAA Drag Prediction Workshop

NASA Technical Reports Server (NTRS)

Morrison, Joseph H.; Hemsch, Michael J.

2007-01-01

The first AIAA Drag Prediction Workshop, held in June 2001, evaluated the results from an extensive N-version test of a collection of Reynolds-Averaged Navier-Stokes CFD codes. The code-to-code scatter was more than an order of magnitude larger than desired for design and experimental validation of cruise conditions for a subsonic transport configuration. The second AIAA Drag Prediction Workshop, held in June 2003, emphasized the determination of installed pylon-nacelle drag increments and grid refinement studies. The code-to-code scatter was significantly reduced compared to the first DPW, but still larger than desired. However, grid refinement studies showed no significant improvement in code-to-code scatter with increasing grid refinement. The third Drag Prediction Workshop focused on the determination of installed side-of-body fairing drag increments and grid refinement studies for clean attached flow on wing alone configurations and for separated flow on the DLR-F6 subsonic transport model. This work evaluated the effect of grid refinement on the code-to-code scatter for the clean attached flow test cases and the separated flow test cases.

EPA's ToxCast Program for Predicting Hazard and Prioritizing the Toxicity Testing of Environmental Chemicals

EPA Science Inventory

An alternative is to perform a set of relatively inexpensive and rapid high throughput screening (HTS) assays, derive signatures predictive of effects or modes of chemical toxicity from the HTS data, then use these predictions to prioritize chemicals for more detailed analysis. T...

Developing a Predictive Capability for Bioluminescence Signatures

DTIC Science & Technology

2012-09-30

dinoflagellates, common unicellular plankton that are also known to form red tides. Dinoflagellate bioluminescence is stimulated by flow stress of...bioluminescence signature of a moving object depends on the bioluminescence potential of the organisms (related to their species abundance), the...WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval Surface Warfare Center Panama City, FL 32407 8. PERFORMING ORGANIZATION

Developing a Predictive Capability for Bioluminescence Signatures

DTIC Science & Technology

2012-09-30

sources of bioluminescence are dinoflagellates, common unicellular plankton that are also known to form red tides. Dinoflagellate bioluminescence is...to locate their prey. The bioluminescence signature of a moving object depends on the bioluminescence potential of the organisms (related to...characteristics of the source organisms and the measurement of their bioluminescence by ocean Report Documentation Page Form ApprovedOMB No. 0704-0188 Public

Developing a Predictive Capability for Bioluminescence Signatures

DTIC Science & Technology

2010-01-01

sources of bioluminescence are dinoflagellates, common unicellular plankton that are also known to form red tides. Dinoflagellate bioluminescence is...wakes to locate their prey. The bioluminescence signature of a moving object depends on the bioluminescence potential of the organisms (related...PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) University of California, San Diego,Scripps Institution of Oceanography,La Jolla,CA,92093-0202 8

Microarray analysis of miRNA expression profiles following whole body irradiation in a mouse model.

PubMed

Aryankalayil, Molykutty J; Chopra, Sunita; Makinde, Adeola; Eke, Iris; Levin, Joel; Shankavaram, Uma; MacMillan, Laurel; Vanpouille-Box, Claire; Demaria, Sandra; Coleman, C Norman

2018-06-19

Accidental exposure to life-threatening radiation in a nuclear event is a major concern; there is an enormous need for identifying biomarkers for radiation biodosimetry to triage populations and treat critically exposed individuals. To identify dose-differentiating miRNA signatures from whole blood samples of whole body irradiated mice. Mice were whole body irradiated with X-rays (2 Gy-15 Gy); blood was collected at various time-points post-exposure; total RNA was isolated; miRNA microarrays were performed; miRNAs differentially expressed in irradiated vs. unirradiated controls were identified; feature extraction and classification models were applied to predict dose-differentiating miRNA signature. We observed a time and dose responsive alteration in the expression levels of miRNAs. Maximum number of miRNAs were altered at 24-h and 48-h time-points post-irradiation. A 23-miRNA signature was identified using feature selection algorithms and classifier models. An inverse correlation in the expression level changes of miR-17 members, and their targets were observed in whole body irradiated mice and non-human primates. Whole blood-based miRNA expression signatures might be used for predicting radiation exposures in a mass casualty nuclear incident.

Mirage: a visible signature evaluation tool

NASA Astrophysics Data System (ADS)

Culpepper, Joanne B.; Meehan, Alaster J.; Shao, Q. T.; Richards, Noel

2017-10-01

This paper presents the Mirage visible signature evaluation tool, designed to provide a visible signature evaluation capability that will appropriately reflect the effect of scene content on the detectability of targets, providing a capability to assess visible signatures in the context of the environment. Mirage is based on a parametric evaluation of input images, assessing the value of a range of image metrics and combining them using the boosted decision tree machine learning method to produce target detectability estimates. It has been developed using experimental data from photosimulation experiments, where human observers search for vehicle targets in a variety of digital images. The images used for tool development are synthetic (computer generated) images, showing vehicles in many different scenes and exhibiting a wide variation in scene content. A preliminary validation has been performed using k-fold cross validation, where 90% of the image data set was used for training and 10% of the image data set was used for testing. The results of the k-fold validation from 200 independent tests show a prediction accuracy between Mirage predictions of detection probability and observed probability of detection of r(262) = 0:63, p < 0:0001 (Pearson correlation) and a MAE = 0:21 (mean absolute error).

ToxCast: Developing Predictive Signatures of Chemically Induced Toxicity (S)

EPA Science Inventory

ToxCast, the United States Environmental Protection Agency’s chemical prioritization research program, is developing methods for utilizing computational chemistry, bioactivity profiling and toxicogenomic data to predict potential for toxicity and prioritize limited testing resour...

Identifying gnostic predictors of the vaccine response.

PubMed

Haining, W Nicholas; Pulendran, Bali

2012-06-01

Molecular predictors of the response to vaccination could transform vaccine development. They would allow larger numbers of vaccine candidates to be rapidly screened, shortening the development time for new vaccines. Gene-expression based predictors of vaccine response have shown early promise. However, a limitation of gene-expression based predictors is that they often fail to reveal the mechanistic basis of their ability to classify response. Linking predictive signatures to the function of their component genes would advance basic understanding of vaccine immunity and also improve the robustness of vaccine prediction. New analytic tools now allow more biological meaning to be extracted from predictive signatures. Functional genomic approaches to perturb gene expression in mammalian cells permit the function of predictive genes to be surveyed in highly parallel experiments. The challenge for vaccinologists is therefore to use these tools to embed mechanistic insights into predictors of vaccine response. Copyright © 2012 Elsevier Ltd. All rights reserved.

Statistical Analysis of the AIAA Drag Prediction Workshop CFD Solutions

NASA Technical Reports Server (NTRS)

Morrison, Joseph H.; Hemsch, Michael J.

2007-01-01

The first AIAA Drag Prediction Workshop (DPW), held in June 2001, evaluated the results from an extensive N-version test of a collection of Reynolds-Averaged Navier-Stokes CFD codes. The code-to-code scatter was more than an order of magnitude larger than desired for design and experimental validation of cruise conditions for a subsonic transport configuration. The second AIAA Drag Prediction Workshop, held in June 2003, emphasized the determination of installed pylon-nacelle drag increments and grid refinement studies. The code-to-code scatter was significantly reduced compared to the first DPW, but still larger than desired. However, grid refinement studies showed no significant improvement in code-to-code scatter with increasing grid refinement. The third AIAA Drag Prediction Workshop, held in June 2006, focused on the determination of installed side-of-body fairing drag increments and grid refinement studies for clean attached flow on wing alone configurations and for separated flow on the DLR-F6 subsonic transport model. This report compares the transonic cruise prediction results of the second and third workshops using statistical analysis.

Solution of the lossy nonlinear Tricomi equation with application to sonic boom focusing

NASA Astrophysics Data System (ADS)

Salamone, Joseph A., III

Sonic boom focusing theory has been augmented with new terms that account for mean flow effects in the direction of propagation and also for atmospheric absorption/dispersion due to molecular relaxation due to oxygen and nitrogen. The newly derived model equation was numerically implemented using a computer code. The computer code was numerically validated using a spectral solution for nonlinear propagation of a sinusoid through a lossy homogeneous medium. An additional numerical check was performed to verify the linear diffraction component of the code calculations. The computer code was experimentally validated using measured sonic boom focusing data from the NASA sponsored Superboom Caustic and Analysis Measurement Program (SCAMP) flight test. The computer code was in good agreement with both the numerical and experimental validation. The newly developed code was applied to examine the focusing of a NASA low-boom demonstration vehicle concept. The resulting pressure field was calculated for several supersonic climb profiles. The shaping efforts designed into the signatures were still somewhat evident despite the effects of sonic boom focusing.

Inter-view prediction of intra mode decision for high-efficiency video coding-based multiview video coding

NASA Astrophysics Data System (ADS)

da Silva, Thaísa Leal; Agostini, Luciano Volcan; da Silva Cruz, Luis A.

2014-05-01

Intra prediction is a very important tool in current video coding standards. High-efficiency video coding (HEVC) intra prediction presents relevant gains in encoding efficiency when compared to previous standards, but with a very important increase in the computational complexity since 33 directional angular modes must be evaluated. Motivated by this high complexity, this article presents a complexity reduction algorithm developed to reduce the HEVC intra mode decision complexity targeting multiview videos. The proposed algorithm presents an efficient fast intra prediction compliant with singleview and multiview video encoding. This fast solution defines a reduced subset of intra directions according to the video texture and it exploits the relationship between prediction units (PUs) of neighbor depth levels of the coding tree. This fast intra coding procedure is used to develop an inter-view prediction method, which exploits the relationship between the intra mode directions of adjacent views to further accelerate the intra prediction process in multiview video encoding applications. When compared to HEVC simulcast, our method achieves a complexity reduction of up to 47.77%, at the cost of an average BD-PSNR loss of 0.08 dB.

SNP discovery in candidate adaptive genes using exon capture in a free-ranging alpine ungulate

Treesearch

Gretchen H. Roffler; Stephen J. Amish; Seth Smith; Ted Cosart; Marty Kardos; Michael K. Schwartz; Gordon Luikart

2016-01-01

Identification of genes underlying genomic signatures of natural selection is key to understanding adaptation to local conditions. We used targeted resequencing to identify SNP markers in 5321 candidate adaptive genes associated with known immunological, metabolic and growth functions in ovids and other ungulates. We selectively targeted 8161 exons in protein-coding...

Directory of Organizational Technical Report Acronym Codes (DOTRAC)

DTIC Science & Technology

1994-07-01

TM - Technical memo report........................................................... TMR- Technical news bulletin...BETHESDA 418182 MD DTRC- TM -12 DAVID TAYLOR RESEARCH CENTER BETHESDA 418631 MD SHIP SYSTEMS INTEGRATION DEPT DTRC- TM -14 DAVID TAYLOR RESEARCH CENTER...BETHESDA 419277 MD SHIP ELECTROMAGNETIC SIGNATURES DEPT DTRC- TM -15 DAVID TAYLOR RESEARCH CENTER BETHESDA 418173 MD SHIP HYDROMECHANICS DEPT DTRC- TM -16 DAVID

Prize of the best thesis 2015: Study of debris discs through state-of-the-art numerical modelling

NASA Astrophysics Data System (ADS)

Kral, Q.; Thébault, P.

2015-12-01

This proceeding summarises the thesis entitled ``Study of debris discs with a new generation numerical model'' by Quentin Kral, for which he obtained the prize of the best thesis in 2015. The thesis brought major contributions to the field of debris disc modelling. The main achievement is to have created, almost ex-nihilo, the first truly self-consistent numerical model able to simultaneously follow the coupled collisional and dynamical evolutions of debris discs. Such a code has been thought as being the ``Holy Grail'' of disc modellers for the past decade, and while several codes with partial dynamics/collisions coupling have been presented, the code developed in this thesis, called ``LIDT-DD'' is the first to achieve a full coupling. The LIDT-DD model, which is the first of a new-generation of fully self-consistent debris disc models is able to handle both planetesimals and dust and create new fragments after each collision. The main idea of LIDT-DD development was to merge into one code two approaches that were so far used separately in disc modelling, that is, an N-body algorithm to investigate the dynamics, and a statistical scheme to explore the collisional evolution. This complex scheme is not straightforward to develop as there are major difficulties to overcome: 1) collisions in debris discs are highly destructive and produce clouds of small fragments after each single impact, 2) the smallest (and most numerous) of these fragments have a strongly size-dependent dynamics because of the radiation pressure, and 3) the dust usually observed in discs is precisely these smallest grains. These extreme constraints had so far prevented all previous attempts at developing self-consistent disc models to succeed. The thesis contains many examples of the use of LIDT-DD that are not yet published but the case of the collision between two asteroid-like bodies is studied in detail. In particular, LIDT-DD is able to predict the different stages that should be observed after such massive collisions that happen mainly in the latest stages of planetary formation. Some giant impact signatures and observability predictions for VLT/SPHERE and JWST/MIRI are given. JWST should be able to detect many of such impacts and would enable to see on-going planetary formation in dozens of planetary systems.

Transonic Drag Prediction on a DLR-F6 Transport Configuration Using Unstructured Grid Solvers

NASA Technical Reports Server (NTRS)

Lee-Rausch, E. M.; Frink, N. T.; Mavriplis, D. J.; Rausch, R. D.; Milholen, W. E.

2004-01-01

A second international AIAA Drag Prediction Workshop (DPW-II) was organized and held in Orlando Florida on June 21-22, 2003. The primary purpose was to inves- tigate the code-to-code uncertainty. address the sensitivity of the drag prediction to grid size and quantify the uncertainty in predicting nacelle/pylon drag increments at a transonic cruise condition. This paper presents an in-depth analysis of the DPW-II computational results from three state-of-the-art unstructured grid Navier-Stokes flow solvers exercised on similar families of tetrahedral grids. The flow solvers are USM3D - a tetrahedral cell-centered upwind solver. FUN3D - a tetrahedral node-centered upwind solver, and NSU3D - a general element node-centered central-differenced solver. For the wingbody, the total drag predicted for a constant-lift transonic cruise condition showed a decrease in code-to-code variation with grid refinement as expected. For the same flight condition, the wing/body/nacelle/pylon total drag and the nacelle/pylon drag increment predicted showed an increase in code-to-code variation with grid refinement. Although the range in total drag for the wingbody fine grids was only 5 counts, a code-to-code comparison of surface pressures and surface restricted streamlines indicated that the three solvers were not all converging to the same flow solutions- different shock locations and separation patterns were evident. Similarly, the wing/body/nacelle/pylon solutions did not appear to be converging to the same flow solutions. Overall, grid refinement did not consistently improve the correlation with experimental data for either the wingbody or the wing/body/nacelle pylon configuration. Although the absolute values of total drag predicted by two of the solvers for the medium and fine grids did not compare well with the experiment, the incremental drag predictions were within plus or minus 3 counts of the experimental data. The correlation with experimental incremental drag was not significantly changed by specifying transition. Although the sources of code-to-code variation in force and moment predictions for the three unstructured grid codes have not yet been identified, the current study reinforces the necessity of applying multiple codes to the same application to assess uncertainty.

High-fat diet reprograms the epigenome of rat spermatozoa and transgenerationally affects metabolism of the offspring

PubMed Central

de Castro Barbosa, Thais; Ingerslev, Lars R.; Alm, Petter S.; Versteyhe, Soetkin; Massart, Julie; Rasmussen, Morten; Donkin, Ida; Sjögren, Rasmus; Mudry, Jonathan M.; Vetterli, Laurène; Gupta, Shashank; Krook, Anna; Zierath, Juleen R.; Barrès, Romain

2015-01-01

Objectives Chronic and high consumption of fat constitutes an environmental stress that leads to metabolic diseases. We hypothesized that high-fat diet (HFD) transgenerationally remodels the epigenome of spermatozoa and metabolism of the offspring. Methods F0-male rats fed either HFD or chow diet for 12 weeks were mated with chow-fed dams to generate F1 and F2 offspring. Motile spermatozoa were isolated from F0 and F1 breeders to determine DNA methylation and small non-coding RNA (sncRNA) expression pattern by deep sequencing. Results Newborn offspring of HFD-fed fathers had reduced body weight and pancreatic beta-cell mass. Adult female, but not male, offspring of HFD-fed fathers were glucose intolerant and resistant to HFD-induced weight gain. This phenotype was perpetuated in the F2 progeny, indicating transgenerational epigenetic inheritance. The epigenome of spermatozoa from HFD-fed F0 and their F1 male offspring showed common DNA methylation and small non-coding RNA expression signatures. Altered expression of sperm miRNA let-7c was passed down to metabolic tissues of the offspring, inducing a transcriptomic shift of the let-7c predicted targets. Conclusion Our results provide insight into mechanisms by which HFD transgenerationally reprograms the epigenome of sperm cells, thereby affecting metabolic tissues of offspring throughout two generations. PMID:26977389

Radiation signatures from a locally energized flaring loop

NASA Technical Reports Server (NTRS)

Emslie, A. G.; Vlahos, L.

1980-01-01

The radiation signatures from a locally energized solar flare loop based on the physical properties of the energy release mechanisms were consistent with hard X-ray, microwave, and EUV observations for plausible source parameters. It was found that a suprathermal tail of high energy electrons is produced by the primary energy release, and that the number of energetic charged particles ejected into the interplanetary medium in the model is consistent with observations. The radiation signature model predicts that the intrinsic polarization of the hard X-ray burst should increase over the photon energy range of 20 to 100 keV.

Development of a computer technique for the prediction of transport aircraft flight profile sonic boom signatures. M.S. Thesis

NASA Technical Reports Server (NTRS)

Coen, Peter G.

1991-01-01

A new computer technique for the analysis of transport aircraft sonic boom signature characteristics was developed. This new technique, based on linear theory methods, combines the previously separate equivalent area and F function development with a signature propagation method using a single geometry description. The new technique was implemented in a stand-alone computer program and was incorporated into an aircraft performance analysis program. Through these implementations, both configuration designers and performance analysts are given new capabilities to rapidly analyze an aircraft's sonic boom characteristics throughout the flight envelope.

A multigene predictor of metastatic outcome in early stage hormone receptor-negative and triple-negative breast cancer

PubMed Central

2010-01-01

Introduction Various multigene predictors of breast cancer clinical outcome have been commercialized, but proved to be prognostic only for hormone receptor (HR) subsets overexpressing estrogen or progesterone receptors. Hormone receptor negative (HRneg) breast cancers, particularly those lacking HER2/ErbB2 overexpression and known as triple-negative (Tneg) cases, are heterogeneous and generally aggressive breast cancer subsets in need of prognostic subclassification, since most early stage HRneg and Tneg breast cancer patients are cured with conservative treatment yet invariably receive aggressive adjuvant chemotherapy. Methods An unbiased search for genes predictive of distant metastatic relapse was undertaken using a training cohort of 199 node-negative, adjuvant treatment naïve HRneg (including 154 Tneg) breast cancer cases curated from three public microarray datasets. Prognostic gene candidates were subsequently validated using a different cohort of 75 node-negative, adjuvant naïve HRneg cases curated from three additional datasets. The HRneg/Tneg gene signature was prognostically compared with eight other previously reported gene signatures, and evaluated for cancer network associations by two commercial pathway analysis programs. Results A novel set of 14 prognostic gene candidates was identified as outcome predictors: CXCL13, CLIC5, RGS4, RPS28, RFX7, EXOC7, HAPLN1, ZNF3, SSX3, HRBL, PRRG3, ABO, PRTN3, MATN1. A composite HRneg/Tneg gene signature index proved more accurate than any individual candidate gene or other reported multigene predictors in identifying cases likely to remain free of metastatic relapse. Significant positive correlations between the HRneg/Tneg index and three independent immune-related signatures (STAT1, IFN, and IR) were observed, as were consistent negative associations between the three immune-related signatures and five other proliferation module-containing signatures (MS-14, ONCO-RS, GGI, CSR/wound and NKI-70). Network analysis identified 8 genes within the HRneg/Tneg signature as being functionally linked to immune/inflammatory chemokine regulation. Conclusions A multigene HRneg/Tneg signature linked to immune/inflammatory cytokine regulation was identified from pooled expression microarray data and shown to be superior to other reported gene signatures in predicting the metastatic outcome of early stage and conservatively managed HRneg and Tneg breast cancer. Further validation of this prognostic signature may lead to new therapeutic insights and spare many newly diagnosed breast cancer patients the need for aggressive adjuvant chemotherapy. PMID:20946665

Simplifying BRDF input data for optical signature modeling

NASA Astrophysics Data System (ADS)

Hallberg, Tomas; Pohl, Anna; Fagerström, Jan

2017-05-01

Scene simulations of optical signature properties using signature codes normally requires input of various parameterized measurement data of surfaces and coatings in order to achieve realistic scene object features. Some of the most important parameters are used in the model of the Bidirectional Reflectance Distribution Function (BRDF) and are normally determined by surface reflectance and scattering measurements. Reflectance measurements of the spectral Directional Hemispherical Reflectance (DHR) at various incident angles can normally be performed in most spectroscopy labs, while measuring the BRDF is more complicated or may not be available at all in many optical labs. We will present a method in order to achieve the necessary BRDF data directly from DHR measurements for modeling software using the Sandford-Robertson BRDF model. The accuracy of the method is tested by modeling a test surface by comparing results from using estimated and measured BRDF data as input to the model. These results show that using this method gives no significant loss in modeling accuracy.

Four-gene Pan-African Blood Signature Predicts Progression to Tuberculosis.

PubMed

Suliman, Sara; Thompson, Ethan; Sutherland, Jayne; Weiner Rd, January; Ota, Martin O C; Shankar, Smitha; Penn-Nicholson, Adam; Thiel, Bonnie; Erasmus, Mzwandile; Maertzdorf, Jeroen; Duffy, Fergal J; Hill, Philip C; Hughes, E Jane; Stanley, Kim; Downing, Katrina; Fisher, Michelle L; Valvo, Joe; Parida, Shreemanta K; van der Spuy, Gian; Tromp, Gerard; Adetifa, Ifedayo M O; Donkor, Simon; Howe, Rawleigh; Mayanja-Kizza, Harriet; Boom, W Henry; Dockrell, Hazel; Ottenhoff, Tom H M; Hatherill, Mark; Aderem, Alan; Hanekom, Willem A; Scriba, Thomas J; Kaufmann, Stefan He; Zak, Daniel E; Walzl, Gerhard

2018-04-06

Contacts of tuberculosis (TB) patients constitute an important target population for preventative measures as they are at high risk of infection with Mycobacterium tuberculosis and progression to disease. We investigated biosignatures with predictive ability for incident tuberculosis. In a case-control study nested within the Grand Challenges 6-74 longitudinal HIV-negative African cohort of exposed household contacts, we employed RNA sequencing, polymerase chain reaction (PCR) and the Pair Ratio algorithm in a training/test set approach. Overall, 79 progressors, who developed tuberculosis between 3 and 24 months following exposure, and 328 matched non-progressors, who remained healthy during 24 months of follow-up, were investigated. A four-transcript signature (RISK4), derived from samples in a South African and Gambian training set, predicted progression up to two years before onset of disease in blinded test set samples from South Africa, The Gambia and Ethiopia with little population-associated variability and also validated on an external cohort of South African adolescents with latent Mycobacterium tuberculosis infection. By contrast, published diagnostic or prognostic tuberculosis signatures predicted on samples from some but not all 3 countries, indicating site-specific variability. Post-hoc meta-analysis identified a single gene pair, C1QC/TRAV27, that would consistently predict TB progression in household contacts from multiple African sites but not in infected adolescents without known recent exposure events. Collectively, we developed a simple whole blood-based PCR test to predict tuberculosis in household contacts from diverse African populations, with potential for implementation in national TB contact investigation programs.

Transforming RNA-Seq data to improve the performance of prognostic gene signatures.

PubMed

Zwiener, Isabella; Frisch, Barbara; Binder, Harald

2014-01-01

Gene expression measurements have successfully been used for building prognostic signatures, i.e for identifying a short list of important genes that can predict patient outcome. Mostly microarray measurements have been considered, and there is little advice available for building multivariable risk prediction models from RNA-Seq data. We specifically consider penalized regression techniques, such as the lasso and componentwise boosting, which can simultaneously consider all measurements and provide both, multivariable regression models for prediction and automated variable selection. However, they might be affected by the typical skewness, mean-variance-dependency or extreme values of RNA-Seq covariates and therefore could benefit from transformations of the latter. In an analytical part, we highlight preferential selection of covariates with large variances, which is problematic due to the mean-variance dependency of RNA-Seq data. In a simulation study, we compare different transformations of RNA-Seq data for potentially improving detection of important genes. Specifically, we consider standardization, the log transformation, a variance-stabilizing transformation, the Box-Cox transformation, and rank-based transformations. In addition, the prediction performance for real data from patients with kidney cancer and acute myeloid leukemia is considered. We show that signature size, identification performance, and prediction performance critically depend on the choice of a suitable transformation. Rank-based transformations perform well in all scenarios and can even outperform complex variance-stabilizing approaches. Generally, the results illustrate that the distribution and potential transformations of RNA-Seq data need to be considered as a critical step when building risk prediction models by penalized regression techniques.

Transforming RNA-Seq Data to Improve the Performance of Prognostic Gene Signatures

PubMed Central

Zwiener, Isabella; Frisch, Barbara; Binder, Harald

2014-01-01

Gene expression measurements have successfully been used for building prognostic signatures, i.e for identifying a short list of important genes that can predict patient outcome. Mostly microarray measurements have been considered, and there is little advice available for building multivariable risk prediction models from RNA-Seq data. We specifically consider penalized regression techniques, such as the lasso and componentwise boosting, which can simultaneously consider all measurements and provide both, multivariable regression models for prediction and automated variable selection. However, they might be affected by the typical skewness, mean-variance-dependency or extreme values of RNA-Seq covariates and therefore could benefit from transformations of the latter. In an analytical part, we highlight preferential selection of covariates with large variances, which is problematic due to the mean-variance dependency of RNA-Seq data. In a simulation study, we compare different transformations of RNA-Seq data for potentially improving detection of important genes. Specifically, we consider standardization, the log transformation, a variance-stabilizing transformation, the Box-Cox transformation, and rank-based transformations. In addition, the prediction performance for real data from patients with kidney cancer and acute myeloid leukemia is considered. We show that signature size, identification performance, and prediction performance critically depend on the choice of a suitable transformation. Rank-based transformations perform well in all scenarios and can even outperform complex variance-stabilizing approaches. Generally, the results illustrate that the distribution and potential transformations of RNA-Seq data need to be considered as a critical step when building risk prediction models by penalized regression techniques. PMID:24416353

A radiosensitivity gene signature and PD-L1 status predict clinical outcome of patients with invasive breast carcinoma in The Cancer Genome Atlas (TCGA) dataset.

PubMed

Jang, Bum-Sup; Kim, In Ah

2017-09-01

We investigated the link between the radiosensitivity gene signature and programmed cell death ligand 1 (PD-L1) status and clinical outcome in order to identify a group of patients that would possibly receive clinical benefit of radiotherapy (RT) combined with anti-PD1/PD-L1 therapy. We validated the identified gene signature related to radiosensitivity and analyzed the PD-L1 status of invasive breast cancer in The Cancer Genome Atlas (TCGA) dataset. To validate the gene signature, 1045 patients were selected and divided into two clusters using a consensus clustering algorithm based on their radiosensitive (RS) or radioresistant (RR) designation according to their prognosis. Patients were also stratified as PD-L1-high or PD-L1-low based on the median value of CD274 mRNA expression level as surrogates of PD-L1. Patents assigned to the RS group had decreased risk of recurrence-free survival (RFS) rate than patients in the RR group by univariate analysis (HR 0.45, 95% CI 0.25-0.81, p=0.008) only when treated with RT. The RS group was independently associated with the PD-L1-high group, and CD274 mRNA expression was significantly higher in the RS group (p<0.001) than the RR group. In the PD-L1-high group, the RS group was associated with better RFS compared to the RR group (HR 0.37, 95% CI 0.16-0.87, p=0.022) in multivariate analysis. The level of PD-L1 expression may represent the immunogenicity of tumors, and thus, we speculated that the PD-L1-high group had more immunogenic tumors, which could be more sensitive to radiation-induced immunologic cell death. We first evaluated the predictive value of the radiosensitivity gene signature and described a relationship with this radiosensitivity gene signature and PD-L1. The radiosensitivity gene signature and PD-L1 status were important factors for prediction of the clinical outcome of RT in patients with invasive breast cancer and may be used for selecting patients who will benefit from RT combined with anti-PD1/PDL1 therapy. Copyright © 2017 Elsevier B.V. All rights reserved.

From High-Throughput Microarray-Based Screening to Clinical Application: The Development of a Second Generation Multigene Test for Breast Cancer Prognosis

PubMed Central

Brase, Jan C.; Kronenwett, Ralf; Petry, Christoph; Denkert, Carsten; Schmidt, Marcus

2013-01-01

Several multigene tests have been developed for breast cancer patients to predict the individual risk of recurrence. Most of the first generation tests rely on proliferation-associated genes and are commonly carried out in central reference laboratories. Here, we describe the development of a second generation multigene assay, the EndoPredict test, a prognostic multigene expression test for estrogen receptor (ER) positive, human epidermal growth factor receptor (HER2) negative (ER+/HER2−) breast cancer patients. The EndoPredict gene signature was initially established in a large high-throughput microarray-based screening study. The key steps for biomarker identification are discussed in detail, in comparison to the establishment of other multigene signatures. After biomarker selection, genes and algorithms were transferred to a diagnostic platform (reverse transcription quantitative PCR (RT-qPCR)) to allow for assaying formalin-fixed, paraffin-embedded (FFPE) samples. A comprehensive analytical validation was performed and a prospective proficiency testing study with seven pathological laboratories finally proved that EndoPredict can be reliably used in the decentralized setting. Three independent large clinical validation studies (n = 2,257) demonstrated that EndoPredict offers independent prognostic information beyond current clinicopathological parameters and clinical guidelines. The review article summarizes several important steps that should be considered for the development process of a second generation multigene test and offers a means for transferring a microarray signature from the research laboratory to clinical practice. PMID:27605191

A 9-protein biomarker molecular signature for predicting histologic type in endometrial carcinoma by immunohistochemistry.

PubMed

Santacana, Maria; Maiques, Oscar; Valls, Joan; Gatius, Sònia; Abó, Ana Isabel; López-García, María Ángeles; Mota, Alba; Reventós, Jaume; Moreno-Bueno, Gema; Palacios, Jose; Bartosch, Carla; Dolcet, Xavier; Matias-Guiu, Xavier

2014-12-01

Histologic typing may be difficult in a subset of endometrial carcinoma (EC) cases. In these cases, interobserver agreement improves when immunohistochemistry (IHC) is used. A series of endometrioid type (EEC) grades 1, 2, and 3 and serous type (SC) were immunostained for p53, p16, estrogen receptor, PTEN, IMP2, IMP3, HER2, cyclin B2 and E1, HMGA2, FolR1, MSLN, Claudins 3 and 4, and NRF2. Nine biomarkers showed significant differences with thresholds in IHC value scale between both types (p53 ≥ 20, IMP2 ≥ 115, IMP3 ≥ 2, cyclin E1 ≥ 220, HMGA2 ≥ 30, FolR1 ≥ 50, p16 ≥ 170, nuclear PTEN ≥ 2 and estrogen receptor ≤ 50; P < .005). This combination led to increased discrimination when considering cases satisfying 0 to 5 conditions predicted as EEC and those satisfying 6 to 9 conditions predicted as SC. This signature correctly predicted all 48 EEC grade 1-2 cases and 18 SC cases, but 3 SC cases were wrongly predicted as EEC. Sensitivity was 86% (95% confidence interval [CI], 64%-97%), and specificity was 100% (95% CI, 89%-100%). The classifier correctly predicted all 28 EEC grade 3 cases but only identified the EEC and SC components in 4 of 9 mixed EEC-SC. An independent validation series (29 EEC grades 1-2, 28 EEC grade 3, and 31 SC) showed 100% sensitivity (95% CI, 84%-100%) and 83% specificity (95% CI, 64%-94%). We propose an internally and externally validated 9-protein biomarker signature to predict the histologic type of EC (EEC or SC) by IHC. The results also suggest that mixed EEC-SC is molecularly ambiguous. Copyright © 2014 Elsevier Inc. All rights reserved.

Dynamic thermal signature prediction for real-time scene generation

NASA Astrophysics Data System (ADS)

Christie, Chad L.; Gouthas, Efthimios (Themie); Williams, Owen M.; Swierkowski, Leszek

2013-05-01

At DSTO, a real-time scene generation framework, VIRSuite, has been developed in recent years, within which trials data are predominantly used for modelling the radiometric properties of the simulated objects. Since in many cases the data are insufficient, a physics-based simulator capable of predicting the infrared signatures of objects and their backgrounds has been developed as a new VIRSuite module. It includes transient heat conduction within the materials, and boundary conditions that take into account the heat fluxes due to solar radiation, wind convection and radiative transfer. In this paper, an overview is presented, covering both the steady-state and transient performance.

Observational Signatures of Magnetic Reconnection

NASA Technical Reports Server (NTRS)

Savage, Sabrina

2014-01-01

Magnetic reconnection is often referred to as the primary source of energy release during solar flares. Directly observing reconnection occurring in the solar atmosphere, however, is not trivial considering that the scale size of the diffusion region is magnitudes smaller than the observational capabilities of current instrumentation, and coronal magnetic field measurements are not currently sufficient to capture the process. Therefore, predicting and studying observationally feasible signatures of the precursors and consequences of reconnection is necessary for guiding and verifying the simulations that dominate our understanding. I will present a set of such observations, particularly in connection with long-duration solar events, and compare them with recent simulations and theoretical predictions.

An optical model for the microwave properties of sea ice

NASA Technical Reports Server (NTRS)

Gloersen, P.; Larabee, J. K.

1981-01-01

The complex refractive index of sea ice is modeled and used to predict the microwave signatures of various sea ice types. Results are shown to correspond well with the observed values of the complex index inferred from dielectic constant and dielectric loss measurements performed in the field, and with observed microwave signatures of sea ice. The success of this modeling procedure vis a vis modeling of the dielectric properties of sea ice constituents used earlier by several others is explained. Multiple layer radiative transfer calculations are used to predict the microwave properties of first-year sea ice with and without snow, and multiyear sea ice.

Molecular Pathways: Extracting Medical Knowledge from High Throughput Genomic Data

PubMed Central

Goldstein, Theodore; Paull, Evan O.; Ellis, Matthew J.; Stuart, Joshua M.

2013-01-01

High-throughput genomic data that measures RNA expression, DNA copy number, mutation status and protein levels provide us with insights into the molecular pathway structure of cancer. Genomic lesions (amplifications, deletions, mutations) and epigenetic modifications disrupt biochemical cellular pathways. While the number of possible lesions is vast, different genomic alterations may result in concordant expression and pathway activities, producing common tumor subtypes that share similar phenotypic outcomes. How can these data be translated into medical knowledge that provides prognostic and predictive information? First generation mRNA expression signatures such as Genomic Health's Oncotype DX already provide prognostic information, but do not provide therapeutic guidance beyond the current standard of care – which is often inadequate in high-risk patients. Rather than building molecular signatures based on gene expression levels, evidence is growing that signatures based on higher-level quantities such as from genetic pathways may provide important prognostic and diagnostic cues. We provide examples of how activities for molecular entities can be predicted from pathway analysis and how the composite of all such activities, referred to here as the “activitome,” help connect genomic events to clinical factors in order to predict the drivers of poor outcome. PMID:23430023

Advanced turboprop noise prediction: Development of a code at NASA Langley based on recent theoretical results

NASA Technical Reports Server (NTRS)

Farassat, F.; Dunn, M. H.; Padula, S. L.

1986-01-01

The development of a high speed propeller noise prediction code at Langley Research Center is described. The code utilizes two recent acoustic formulations in the time domain for subsonic and supersonic sources. The structure and capabilities of the code are discussed. Grid size study for accuracy and speed of execution on a computer is also presented. The code is tested against an earlier Langley code. Considerable increase in accuracy and speed of execution are observed. Some examples of noise prediction of a high speed propeller for which acoustic test data are available are given. A brisk derivation of formulations used is given in an appendix.

PhiSiGns: an online tool to identify signature genes in phages and design PCR primers for examining phage diversity.

PubMed

Dwivedi, Bhakti; Schmieder, Robert; Goldsmith, Dawn B; Edwards, Robert A; Breitbart, Mya

2012-03-04

Phages (viruses that infect bacteria) have gained significant attention because of their abundance, diversity and important ecological roles. However, the lack of a universal gene shared by all phages presents a challenge for phage identification and characterization, especially in environmental samples where it is difficult to culture phage-host systems. Homologous conserved genes (or "signature genes") present in groups of closely-related phages can be used to explore phage diversity and define evolutionary relationships amongst these phages. Bioinformatic approaches are needed to identify candidate signature genes and design PCR primers to amplify those genes from environmental samples; however, there is currently no existing computational tool that biologists can use for this purpose. Here we present PhiSiGns, a web-based and standalone application that performs a pairwise comparison of each gene present in user-selected phage genomes, identifies signature genes, generates alignments of these genes, and designs potential PCR primer pairs. PhiSiGns is available at (http://www.phantome.org/phisigns/; http://phisigns.sourceforge.net/) with a link to the source code. Here we describe the specifications of PhiSiGns and demonstrate its application with a case study. PhiSiGns provides phage biologists with a user-friendly tool to identify signature genes and design PCR primers to amplify related genes from uncultured phages in environmental samples. This bioinformatics tool will facilitate the development of novel signature genes for use as molecular markers in studies of phage diversity, phylogeny, and evolution.

PhiSiGns: an online tool to identify signature genes in phages and design PCR primers for examining phage diversity

PubMed Central

2012-01-01

Background Phages (viruses that infect bacteria) have gained significant attention because of their abundance, diversity and important ecological roles. However, the lack of a universal gene shared by all phages presents a challenge for phage identification and characterization, especially in environmental samples where it is difficult to culture phage-host systems. Homologous conserved genes (or "signature genes") present in groups of closely-related phages can be used to explore phage diversity and define evolutionary relationships amongst these phages. Bioinformatic approaches are needed to identify candidate signature genes and design PCR primers to amplify those genes from environmental samples; however, there is currently no existing computational tool that biologists can use for this purpose. Results Here we present PhiSiGns, a web-based and standalone application that performs a pairwise comparison of each gene present in user-selected phage genomes, identifies signature genes, generates alignments of these genes, and designs potential PCR primer pairs. PhiSiGns is available at (http://www.phantome.org/phisigns/; http://phisigns.sourceforge.net/) with a link to the source code. Here we describe the specifications of PhiSiGns and demonstrate its application with a case study. Conclusions PhiSiGns provides phage biologists with a user-friendly tool to identify signature genes and design PCR primers to amplify related genes from uncultured phages in environmental samples. This bioinformatics tool will facilitate the development of novel signature genes for use as molecular markers in studies of phage diversity, phylogeny, and evolution. PMID:22385976

Use of Attribute Driven Incremental Discretization and Logic Learning Machine to build a prognostic classifier for neuroblastoma patients.

PubMed

Cangelosi, Davide; Muselli, Marco; Parodi, Stefano; Blengio, Fabiola; Becherini, Pamela; Versteeg, Rogier; Conte, Massimo; Varesio, Luigi

2014-01-01

Cancer patient's outcome is written, in part, in the gene expression profile of the tumor. We previously identified a 62-probe sets signature (NB-hypo) to identify tissue hypoxia in neuroblastoma tumors and showed that NB-hypo stratified neuroblastoma patients in good and poor outcome 1. It was important to develop a prognostic classifier to cluster patients into risk groups benefiting of defined therapeutic approaches. Novel classification and data discretization approaches can be instrumental for the generation of accurate predictors and robust tools for clinical decision support. We explored the application to gene expression data of Rulex, a novel software suite including the Attribute Driven Incremental Discretization technique for transforming continuous variables into simplified discrete ones and the Logic Learning Machine model for intelligible rule generation. We applied Rulex components to the problem of predicting the outcome of neuroblastoma patients on the bases of 62 probe sets NB-hypo gene expression signature. The resulting classifier consisted in 9 rules utilizing mainly two conditions of the relative expression of 11 probe sets. These rules were very effective predictors, as shown in an independent validation set, demonstrating the validity of the LLM algorithm applied to microarray data and patients' classification. The LLM performed as efficiently as Prediction Analysis of Microarray and Support Vector Machine, and outperformed other learning algorithms such as C4.5. Rulex carried out a feature selection by selecting a new signature (NB-hypo-II) of 11 probe sets that turned out to be the most relevant in predicting outcome among the 62 of the NB-hypo signature. Rules are easily interpretable as they involve only few conditions. Our findings provided evidence that the application of Rulex to the expression values of NB-hypo signature created a set of accurate, high quality, consistent and interpretable rules for the prediction of neuroblastoma patients' outcome. We identified the Rulex weighted classification as a flexible tool that can support clinical decisions. For these reasons, we consider Rulex to be a useful tool for cancer classification from microarray gene expression data.

Simulating Cosmic Reionization and Its Observable Consequences

NASA Astrophysics Data System (ADS)

Shapiro, Paul

2017-01-01

I summarize recent progress in modelling the epoch of reionization by large- scale simulations of cosmic structure formation, radiative transfer and their interplay, which trace the ionization fronts that swept across the IGM, to predict observable signatures. Reionization by starlight from early galaxies affected their evolution, impacting reionization, itself, and imprinting the galaxies with a memory of reionization. Star formation suppression, e.g., may explain the observed underabundance of Local Group dwarfs relative to N-body predictions for Cold Dark Matter. I describe CoDa (''Cosmic Dawn''), the first fully-coupled radiation-hydrodynamical simulation of reionization and galaxy formation in the Local Universe, in a volume large enough to model reionization globally but with enough resolving power to follow all the atomic-cooling galactic halos in that volume. A 90 Mpc box was simulated from a constrained realization of primordial fluctuations, chosen to reproduce present-day features of the Local Group, including the Milky Way and M31, and the local universe beyond, including the Virgo cluster. The new RAMSES-CUDATON hybrid CPU-GPU code took 11 days to perform this simulation on the Titan supercomputer at Oak Ridge National Laboratory, with 4096-cubed N-body particles for the dark matter and 4096-cubed cells for the atomic gas and ionizing radiation.

Top-down modulation in the infant brain: Learning-induced expectations rapidly affect the sensory cortex at 6 months.

PubMed

Emberson, Lauren L; Richards, John E; Aslin, Richard N

2015-08-04

Recent theoretical work emphasizes the role of expectation in neural processing, shifting the focus from feed-forward cortical hierarchies to models that include extensive feedback (e.g., predictive coding). Empirical support for expectation-related feedback is compelling but restricted to adult humans and nonhuman animals. Given the considerable differences in neural organization, connectivity, and efficiency between infant and adult brains, it is a crucial yet open question whether expectation-related feedback is an inherent property of the cortex (i.e., operational early in development) or whether expectation-related feedback develops with extensive experience and neural maturation. To determine whether infants' expectations about future sensory input modulate their sensory cortices without the confounds of stimulus novelty or repetition suppression, we used a cross-modal (audiovisual) omission paradigm and used functional near-infrared spectroscopy (fNIRS) to record hemodynamic responses in the infant cortex. We show that the occipital cortex of 6-month-old infants exhibits the signature of expectation-based feedback. Crucially, we found that this region does not respond to auditory stimuli if they are not predictive of a visual event. Overall, these findings suggest that the young infant's brain is already capable of some rudimentary form of expectation-based feedback.

CELFE/NASTRAN Code for the Analysis of Structures Subjected to High Velocity Impact

NASA Technical Reports Server (NTRS)

Chamis, C. C.

1978-01-01

CELFE (Coupled Eulerian Lagrangian Finite Element)/NASTRAN Code three-dimensional finite element code has the capability for analyzing of structures subjected to high velocity impact. The local response is predicted by CELFE and, for large problems, the far-field impact response is predicted by NASTRAN. The coupling of the CELFE code with NASTRAN (CELFE/NASTRAN code) and the application of the code to selected three-dimensional high velocity impact problems are described.

Indexing sensory plasticity: Evidence for distinct Predictive Coding and Hebbian learning mechanisms in the cerebral cortex.

PubMed

Spriggs, M J; Sumner, R L; McMillan, R L; Moran, R J; Kirk, I J; Muthukumaraswamy, S D

2018-04-30

The Roving Mismatch Negativity (MMN), and Visual LTP paradigms are widely used as independent measures of sensory plasticity. However, the paradigms are built upon fundamentally different (and seemingly opposing) models of perceptual learning; namely, Predictive Coding (MMN) and Hebbian plasticity (LTP). The aim of the current study was to compare the generative mechanisms of the MMN and visual LTP, therefore assessing whether Predictive Coding and Hebbian mechanisms co-occur in the brain. Forty participants were presented with both paradigms during EEG recording. Consistent with Predictive Coding and Hebbian predictions, Dynamic Causal Modelling revealed that the generation of the MMN modulates forward and backward connections in the underlying network, while visual LTP only modulates forward connections. These results suggest that both Predictive Coding and Hebbian mechanisms are utilized by the brain under different task demands. This therefore indicates that both tasks provide unique insight into plasticity mechanisms, which has important implications for future studies of aberrant plasticity in clinical populations. Copyright © 2018 Elsevier Inc. All rights reserved.

Correlation approach to identify coding regions in DNA sequences

NASA Technical Reports Server (NTRS)

Ossadnik, S. M.; Buldyrev, S. V.; Goldberger, A. L.; Havlin, S.; Mantegna, R. N.; Peng, C. K.; Simons, M.; Stanley, H. E.

1994-01-01

Recently, it was observed that noncoding regions of DNA sequences possess long-range power-law correlations, whereas coding regions typically display only short-range correlations. We develop an algorithm based on this finding that enables investigators to perform a statistical analysis on long DNA sequences to locate possible coding regions. The algorithm is particularly successful in predicting the location of lengthy coding regions. For example, for the complete genome of yeast chromosome III (315,344 nucleotides), at least 82% of the predictions correspond to putative coding regions; the algorithm correctly identified all coding regions larger than 3000 nucleotides, 92% of coding regions between 2000 and 3000 nucleotides long, and 79% of coding regions between 1000 and 2000 nucleotides. The predictive ability of this new algorithm supports the claim that there is a fundamental difference in the correlation property between coding and noncoding sequences. This algorithm, which is not species-dependent, can be implemented with other techniques for rapidly and accurately locating relatively long coding regions in genomic sequences.

Developing a Predictive Capability for Bioluminescence Signatures

DTIC Science & Technology

2011-09-30

sources of bioluminescence are dinoflagellates, common unicellular plankton that are also known to form red tides. Dinoflagellate bioluminescence is...wakes to locate their prey. The bioluminescence signature of a moving object depends on the bioluminescence potential of the organisms (related to...AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) University of California, San

Calibration and comparison of the NASA Lewis free-piston Stirling engine model predictions with RE-1000 test data

NASA Technical Reports Server (NTRS)

Geng, Steven M.

1987-01-01

A free-piston Stirling engine performance code is being upgraded and validated at the NASA Lewis Research Center under an interagency agreement between the Department of Energy's Oak Ridge National Laboratory and NASA Lewis. Many modifications were made to the free-piston code in an attempt to decrease the calibration effort. A procedure was developed that made the code calibration process more systematic. Engine-specific calibration parameters are often used to bring predictions and experimental data into better agreement. The code was calibrated to a matrix of six experimental data points. Predictions of the calibrated free-piston code are compared with RE-1000 free-piston Stirling engine sensitivity test data taken at NASA Lewis. Reasonable agreement was obtained between the code prediction and the experimental data over a wide range of engine operating conditions.

Calibration and comparison of the NASA Lewis free-piston Stirling engine model predictions with RE-1000 test data

NASA Technical Reports Server (NTRS)

Geng, Steven M.

1987-01-01

A free-piston Stirling engine performance code is being upgraded and validated at the NASA Lewis Research Center under an interagency agreement between the Department of Energy's Oak Ridge National Laboratory and NASA Lewis. Many modifications were made to the free-piston code in an attempt to decrease the calibration effort. A procedure was developed that made the code calibration process more systematic. Engine-specific calibration parameters are often used to bring predictions and experimental data into better agreement. The code was calibrated to a matrix of six experimental data points. Predictions of the calibrated free-piston code are compared with RE-1000 free-piston Stirling engine sensitivity test data taken at NASA Lewis. Resonable agreement was obtained between the code predictions and the experimental data over a wide range of engine operating conditions.

Integrating multiple molecular sources into a clinical risk prediction signature by extracting complementary information.

PubMed

Hieke, Stefanie; Benner, Axel; Schlenl, Richard F; Schumacher, Martin; Bullinger, Lars; Binder, Harald

2016-08-30

High-throughput technology allows for genome-wide measurements at different molecular levels for the same patient, e.g. single nucleotide polymorphisms (SNPs) and gene expression. Correspondingly, it might be beneficial to also integrate complementary information from different molecular levels when building multivariable risk prediction models for a clinical endpoint, such as treatment response or survival. Unfortunately, such a high-dimensional modeling task will often be complicated by a limited overlap of molecular measurements at different levels between patients, i.e. measurements from all molecular levels are available only for a smaller proportion of patients. We propose a sequential strategy for building clinical risk prediction models that integrate genome-wide measurements from two molecular levels in a complementary way. To deal with partial overlap, we develop an imputation approach that allows us to use all available data. This approach is investigated in two acute myeloid leukemia applications combining gene expression with either SNP or DNA methylation data. After obtaining a sparse risk prediction signature e.g. from SNP data, an automatically selected set of prognostic SNPs, by componentwise likelihood-based boosting, imputation is performed for the corresponding linear predictor by a linking model that incorporates e.g. gene expression measurements. The imputed linear predictor is then used for adjustment when building a prognostic signature from the gene expression data. For evaluation, we consider stability, as quantified by inclusion frequencies across resampling data sets. Despite an extremely small overlap in the application example with gene expression and SNPs, several genes are seen to be more stably identified when taking the (imputed) linear predictor from the SNP data into account. In the application with gene expression and DNA methylation, prediction performance with respect to survival also indicates that the proposed approach might work well. We consider imputation of linear predictor values to be a feasible and sensible approach for dealing with partial overlap in complementary integrative analysis of molecular measurements at different levels. More generally, these results indicate that a complementary strategy for integrating different molecular levels can result in more stable risk prediction signatures, potentially providing a more reliable insight into the underlying biology.

Analysis of Nozzle Jet Plume Effects on Sonic Boom Signature

NASA Technical Reports Server (NTRS)

Bui, Trong

2010-01-01

An axisymmetric full Navier-Stokes computational fluid dynamics (CFD) study was conducted to examine nozzle exhaust jet plume effects on the sonic boom signature of a supersonic aircraft. A simplified axisymmetric nozzle geometry, representative of the nozzle on the NASA Dryden NF-15B Lift and Nozzle Change Effects on Tail Shock (LaNCETS) research airplane, was considered. The highly underexpanded nozzle flow is found to provide significantly more reduction in the tail shock strength in the sonic boom N-wave pressure signature than perfectly expanded and overexpanded nozzle flows. A tail shock train in the sonic boom signature, similar to what was observed in the LaNCETS flight data, is observed for the highly underexpanded nozzle flow. The CFD results provide a detailed description of the nozzle flow physics involved in the LaNCETS nozzle at different nozzle expansion conditions and help in interpreting LaNCETS flight data as well as in the eventual CFD analysis of a full LaNCETS aircraft. The current study also provided important information on proper modeling of the LaNCETS aircraft nozzle. The primary objective of the current CFD research effort was to support the LaNCETS flight research data analysis effort by studying the detailed nozzle exhaust jet plume s imperfect expansion effects on the sonic boom signature of a supersonic aircraft. Figure 1 illustrates the primary flow physics present in the interaction between the exhaust jet plume shock and the sonic boom coming off of an axisymmetric body in supersonic flight. The steeper tail shock from highly expanded jet plume reduces the dip of the sonic boom N-wave signature. A structured finite-volume compressible full Navier-Stokes CFD code was used in the current study. This approach is not limited by the simplifying assumptions inherent in previous sonic boom analysis efforts. Also, this study was the first known jet plume sonic boom CFD study in which the full viscous nozzle flow field was modeled, without coupling to a sonic boom propagation analysis code, from the stagnation chamber of the nozzle to the far field external flow, taking into account all nonisentropic effects in the shocks, boundary layers, and free shear layers, and their interactions at distances up to 30 times the nozzle exit diameter from the jet centerline. A CFD solution is shown in Figure 2. The flow field is very complicated and multi-dimensional, with shock-shock and shockplume interactions. At the time of this reporting, a full three-dimensional CFD study was being conducted to evaluate the effects of nozzle vectoring on the aircraft tail shock strength.

A high resolution atlas of gene expression in the domestic sheep (Ovis aries)

PubMed Central

Farquhar, Iseabail L.; Young, Rachel; Lefevre, Lucas; Pridans, Clare; Tsang, Hiu G.; Afrasiabi, Cyrus; Watson, Mick; Whitelaw, C. Bruce; Freeman, Tom C.; Archibald, Alan L.; Hume, David A.

2017-01-01

Sheep are a key source of meat, milk and fibre for the global livestock sector, and an important biomedical model. Global analysis of gene expression across multiple tissues has aided genome annotation and supported functional annotation of mammalian genes. We present a large-scale RNA-Seq dataset representing all the major organ systems from adult sheep and from several juvenile, neonatal and prenatal developmental time points. The Ovis aries reference genome (Oar v3.1) includes 27,504 genes (20,921 protein coding), of which 25,350 (19,921 protein coding) had detectable expression in at least one tissue in the sheep gene expression atlas dataset. Network-based cluster analysis of this dataset grouped genes according to their expression pattern. The principle of ‘guilt by association’ was used to infer the function of uncharacterised genes from their co-expression with genes of known function. We describe the overall transcriptional signatures present in the sheep gene expression atlas and assign those signatures, where possible, to specific cell populations or pathways. The findings are related to innate immunity by focusing on clusters with an immune signature, and to the advantages of cross-breeding by examining the patterns of genes exhibiting the greatest expression differences between purebred and crossbred animals. This high-resolution gene expression atlas for sheep is, to our knowledge, the largest transcriptomic dataset from any livestock species to date. It provides a resource to improve the annotation of the current reference genome for sheep, presenting a model transcriptome for ruminants and insight into gene, cell and tissue function at multiple developmental stages. PMID:28915238

A high resolution atlas of gene expression in the domestic sheep (Ovis aries).

PubMed

Clark, Emily L; Bush, Stephen J; McCulloch, Mary E B; Farquhar, Iseabail L; Young, Rachel; Lefevre, Lucas; Pridans, Clare; Tsang, Hiu G; Wu, Chunlei; Afrasiabi, Cyrus; Watson, Mick; Whitelaw, C Bruce; Freeman, Tom C; Summers, Kim M; Archibald, Alan L; Hume, David A

2017-09-01

Sheep are a key source of meat, milk and fibre for the global livestock sector, and an important biomedical model. Global analysis of gene expression across multiple tissues has aided genome annotation and supported functional annotation of mammalian genes. We present a large-scale RNA-Seq dataset representing all the major organ systems from adult sheep and from several juvenile, neonatal and prenatal developmental time points. The Ovis aries reference genome (Oar v3.1) includes 27,504 genes (20,921 protein coding), of which 25,350 (19,921 protein coding) had detectable expression in at least one tissue in the sheep gene expression atlas dataset. Network-based cluster analysis of this dataset grouped genes according to their expression pattern. The principle of 'guilt by association' was used to infer the function of uncharacterised genes from their co-expression with genes of known function. We describe the overall transcriptional signatures present in the sheep gene expression atlas and assign those signatures, where possible, to specific cell populations or pathways. The findings are related to innate immunity by focusing on clusters with an immune signature, and to the advantages of cross-breeding by examining the patterns of genes exhibiting the greatest expression differences between purebred and crossbred animals. This high-resolution gene expression atlas for sheep is, to our knowledge, the largest transcriptomic dataset from any livestock species to date. It provides a resource to improve the annotation of the current reference genome for sheep, presenting a model transcriptome for ruminants and insight into gene, cell and tissue function at multiple developmental stages.

Multiwaveband simulation-based signature analysis of camouflaged human dismounts in cluttered environments with TAIThermIR and MuSES

NASA Astrophysics Data System (ADS)

Packard, Corey D.; Klein, Mark D.; Viola, Timothy S.; Hepokoski, Mark A.

2016-10-01

The ability to predict electro-optical (EO) signatures of diverse targets against cluttered backgrounds is paramount for signature evaluation and/or management. Knowledge of target and background signatures is essential for a variety of defense-related applications. While there is no substitute for measured target and background signatures to determine contrast and detection probability, the capability to simulate any mission scenario with desired environmental conditions is a tremendous asset for defense agencies. In this paper, a systematic process for the thermal and visible-through-infrared simulation of camouflaged human dismounts in cluttered outdoor environments is presented. This process, utilizing the thermal and EO/IR radiance simulation tool TAIThermIR (and MuSES), provides a repeatable and accurate approach for analyzing contrast, signature and detectability of humans in multiple wavebands. The engineering workflow required to combine natural weather boundary conditions and the human thermoregulatory module developed by ThermoAnalytics is summarized. The procedure includes human geometry creation, human segmental physiology description and transient physical temperature prediction using environmental boundary conditions and active thermoregulation. Radiance renderings, which use Sandford-Robertson BRDF optical surface property descriptions and are coupled with MODTRAN for the calculation of atmospheric effects, are demonstrated. Sensor effects such as optical blurring and photon noise can be optionally included, increasing the accuracy of detection probability outputs that accompany each rendering. This virtual evaluation procedure has been extensively validated and provides a flexible evaluation process that minimizes the difficulties inherent in human-subject field testing. Defense applications such as detection probability assessment, camouflage pattern evaluation, conspicuity tests and automatic target recognition are discussed.

Predictive codes of familiarity and context during the perceptual learning of facial identities

NASA Astrophysics Data System (ADS)

Apps, Matthew A. J.; Tsakiris, Manos

2013-11-01

Face recognition is a key component of successful social behaviour. However, the computational processes that underpin perceptual learning and recognition as faces transition from unfamiliar to familiar are poorly understood. In predictive coding, learning occurs through prediction errors that update stimulus familiarity, but recognition is a function of both stimulus and contextual familiarity. Here we show that behavioural responses on a two-option face recognition task can be predicted by the level of contextual and facial familiarity in a computational model derived from predictive-coding principles. Using fMRI, we show that activity in the superior temporal sulcus varies with the contextual familiarity in the model, whereas activity in the fusiform face area covaries with the prediction error parameter that updated facial familiarity. Our results characterize the key computations underpinning the perceptual learning of faces, highlighting that the functional properties of face-processing areas conform to the principles of predictive coding.

Prediction task guided representation learning of medical codes in EHR.

PubMed

Cui, Liwen; Xie, Xiaolei; Shen, Zuojun

2018-06-18

There have been rapidly growing applications using machine learning models for predictive analytics in Electronic Health Records (EHR) to improve the quality of hospital services and the efficiency of healthcare resource utilization. A fundamental and crucial step in developing such models is to convert medical codes in EHR to feature vectors. These medical codes are used to represent diagnoses or procedures. Their vector representations have a tremendous impact on the performance of machine learning models. Recently, some researchers have utilized representation learning methods from Natural Language Processing (NLP) to learn vector representations of medical codes. However, most previous approaches are unsupervised, i.e. the generation of medical code vectors is independent from prediction tasks. Thus, the obtained feature vectors may be inappropriate for a specific prediction task. Moreover, unsupervised methods often require a lot of samples to obtain reliable results, but most practical problems have very limited patient samples. In this paper, we develop a new method called Prediction Task Guided Health Record Aggregation (PTGHRA), which aggregates health records guided by prediction tasks, to construct training corpus for various representation learning models. Compared with unsupervised approaches, representation learning models integrated with PTGHRA yield a significant improvement in predictive capability of generated medical code vectors, especially for limited training samples. Copyright © 2018. Published by Elsevier Inc.

Helical flow in RFX-mod tokamak plasmas

NASA Astrophysics Data System (ADS)

Piron, L.; Zaniol, B.; Bonfiglio, D.; Carraro, L.; Kirk, A.; Marrelli, L.; Martin, R.; Piron, C.; Piovesan, P.; Zuin, M.

2017-05-01

This work presents the first evidence of helical flow in RFX-mod q(a)  <  2 tokamak plasmas. The flow pattern is characterized by the presence of convective cells with m  =  1 and n  =  1 periodicity in the poloidal and toroidal directions, respectively. A similar helical flow deformation has been observed in the same device when operated as a reversed field pinch (RFP). In RFP plasmas, the flow dynamic is tailored by the innermost resonant m  =  1, n  =  7 tearing mode, which sustains the magnetic field configuration through the dynamo mechanism (Bonomo et al 2011 Nucl. Fusion 51 123007). By contrast, in the tokamak experiments presented here, it is strongly correlated with the m  =  1, n  =  1 MHD activity. A helical deformation of the flow pattern, associated with the deformation of the magnetic flux surfaces, is predicted by several codes, such as Specyl (Bonfiglio et al 2005 Phys. Rev. Lett. 94 145001), PIXIE3D (Chacón et al 2008 Phys. Plasmas 15 056103), NIMROD (King et al 2012 Phys. Plasmas 19 055905) and M3D-C1 (Jardin et al 2015 Phys. Rev. Lett. 115 215001). Among them, the 3D fully non-linear PIXIE3D has been used to calculate synthetic flow measurements, using a 2D flow modelling code. Inputs to the code are the PIXIE3D flow maps, the ion emission profiles as calculated by a 1D collisional radiative impurity transport code (Carraro et al 2000 Plasma Phys. Control. Fusion 42 731) and a synthetic diagnostic with the same geometry installed in RFX-mod. Good agreement between the synthetic and the experimental flow behaviour has been obtained, confirming that the flow oscillations observed with the associated convective cells are a signature of helical flow.

A biological network-based regularized artificial neural network model for robust phenotype prediction from gene expression data.

PubMed

Kang, Tianyu; Ding, Wei; Zhang, Luoyan; Ziemek, Daniel; Zarringhalam, Kourosh

2017-12-19

Stratification of patient subpopulations that respond favorably to treatment or experience and adverse reaction is an essential step toward development of new personalized therapies and diagnostics. It is currently feasible to generate omic-scale biological measurements for all patients in a study, providing an opportunity for machine learning models to identify molecular markers for disease diagnosis and progression. However, the high variability of genetic background in human populations hampers the reproducibility of omic-scale markers. In this paper, we develop a biological network-based regularized artificial neural network model for prediction of phenotype from transcriptomic measurements in clinical trials. To improve model sparsity and the overall reproducibility of the model, we incorporate regularization for simultaneous shrinkage of gene sets based on active upstream regulatory mechanisms into the model. We benchmark our method against various regression, support vector machines and artificial neural network models and demonstrate the ability of our method in predicting the clinical outcomes using clinical trial data on acute rejection in kidney transplantation and response to Infliximab in ulcerative colitis. We show that integration of prior biological knowledge into the classification as developed in this paper, significantly improves the robustness and generalizability of predictions to independent datasets. We provide a Java code of our algorithm along with a parsed version of the STRING DB database. In summary, we present a method for prediction of clinical phenotypes using baseline genome-wide expression data that makes use of prior biological knowledge on gene-regulatory interactions in order to increase robustness and reproducibility of omic-scale markers. The integrated group-wise regularization methods increases the interpretability of biological signatures and gives stable performance estimates across independent test sets.

Preliminary Computational Study for Future Tests in the NASA Ames 9 foot' x 7 foot Wind Tunnel

NASA Technical Reports Server (NTRS)

Pearl, Jason M.; Carter, Melissa B.; Elmiligui, Alaa A.; WInski, Courtney S.; Nayani, Sudheer N.

2016-01-01

The NASA Advanced Air Vehicles Program, Commercial Supersonics Technology Project seeks to advance tools and techniques to make over-land supersonic flight feasible. In this study, preliminary computational results are presented for future tests in the NASA Ames 9 foot x 7 foot supersonic wind tunnel to be conducted in early 2016. Shock-plume interactions and their effect on pressure signature are examined for six model geometries. Near- field pressure signatures are assessed using the CFD code USM3D to model the proposed test geometries in free-air. Additionally, results obtained using the commercial grid generation software Pointwise Reigistered Trademark are compared to results using VGRID, the NASA Langley Research Center in-house mesh generation program.

Performance Analysis of Blind Subspace-Based Signature Estimation Algorithms for DS-CDMA Systems with Unknown Correlated Noise

NASA Astrophysics Data System (ADS)

Zarifi, Keyvan; Gershman, Alex B.

2006-12-01

We analyze the performance of two popular blind subspace-based signature waveform estimation techniques proposed by Wang and Poor and Buzzi and Poor for direct-sequence code division multiple-access (DS-CDMA) systems with unknown correlated noise. Using the first-order perturbation theory, analytical expressions for the mean-square error (MSE) of these algorithms are derived. We also obtain simple high SNR approximations of the MSE expressions which explicitly clarify how the performance of these techniques depends on the environmental parameters and how it is related to that of the conventional techniques that are based on the standard white noise assumption. Numerical examples further verify the consistency of the obtained analytical results with simulation results.

Process consistency in models: The importance of system signatures, expert knowledge, and process complexity

NASA Astrophysics Data System (ADS)

Hrachowitz, M.; Fovet, O.; Ruiz, L.; Euser, T.; Gharari, S.; Nijzink, R.; Freer, J.; Savenije, H. H. G.; Gascuel-Odoux, C.

2014-09-01

Hydrological models frequently suffer from limited predictive power despite adequate calibration performances. This can indicate insufficient representations of the underlying processes. Thus, ways are sought to increase model consistency while satisfying the contrasting priorities of increased model complexity and limited equifinality. In this study, the value of a systematic use of hydrological signatures and expert knowledge for increasing model consistency was tested. It was found that a simple conceptual model, constrained by four calibration objective functions, was able to adequately reproduce the hydrograph in the calibration period. The model, however, could not reproduce a suite of hydrological signatures, indicating a lack of model consistency. Subsequently, testing 11 models, model complexity was increased in a stepwise way and counter-balanced by "prior constraints," inferred from expert knowledge to ensure a model which behaves well with respect to the modeler's perception of the system. We showed that, in spite of unchanged calibration performance, the most complex model setup exhibited increased performance in the independent test period and skill to better reproduce all tested signatures, indicating a better system representation. The results suggest that a model may be inadequate despite good performance with respect to multiple calibration objectives and that increasing model complexity, if counter-balanced by prior constraints, can significantly increase predictive performance of a model and its skill to reproduce hydrological signatures. The results strongly illustrate the need to balance automated model calibration with a more expert-knowledge-driven strategy of constraining models.

A novel prognostic six-CpG signature in glioblastomas.

PubMed

Yin, An-An; Lu, Nan; Etcheverry, Amandine; Aubry, Marc; Barnholtz-Sloan, Jill; Zhang, Lu-Hua; Mosser, Jean; Zhang, Wei; Zhang, Xiang; Liu, Yu-He; He, Ya-Long

2018-03-01

We aimed to identify a clinically useful biomarker using DNA methylation-based information to optimize individual treatment of patients with glioblastoma (GBM). A six-CpG panel was identified by incorporating genome-wide DNA methylation data and clinical information of three distinct discovery sets and was combined using a risk-score model. Different validation sets of GBMs and lower-grade gliomas and different statistical methods were implemented for prognostic evaluation. An integrative analysis of multidimensional TCGA data was performed to molecularly characterize different risk tumors. The six-CpG risk-score signature robustly predicted overall survival (OS) in all discovery and validation cohorts and in a treatment-independent manner. It also predicted progression-free survival (PFS) in available patients. The multimarker epigenetic signature was demonstrated as an independent prognosticator and had better performance than known molecular indicators such as glioma-CpG island methylator phenotype (G-CIMP) and proneural subtype. The defined risk subgroups were molecularly distinct; high-risk tumors were biologically more aggressive with concordant activation of proangiogenic signaling at multimolecular levels. Accordingly, we observed better OS benefits of bevacizumab-contained therapy to high-risk patients in independent sets, supporting its implication in guiding usage of antiangiogenic therapy. Finally, the six-CpG signature refined the risk classification based on G-CIMP and MGMT methylation status. The novel six-CpG signature is a robust and independent prognostic indicator for GBMs and is of promising value to improve personalized management. © 2018 John Wiley & Sons Ltd.

A 15-gene signature for prediction of colon cancer recurrence and prognosis based on SVM.

PubMed

Xu, Guangru; Zhang, Minghui; Zhu, Hongxing; Xu, Jinhua

2017-03-10

To screen the gene signature for distinguishing patients with high risks from those with low-risks for colon cancer recurrence and predicting their prognosis. Five microarray datasets of colon cancer samples were collected from Gene Expression Omnibus database and one was obtained from The Cancer Genome Atlas (TCGA). After preprocessing, data in GSE17537 were analyzed using the Linear Models for Microarray data (LIMMA) method to identify the differentially expressed genes (DEGs). The DEGs further underwent PPI network-based neighborhood scoring and support vector machine (SVM) analyses to screen the feature genes associated with recurrence and prognosis, which were then validated by four datasets GSE38832, GSE17538, GSE28814 and TCGA using SVM and Cox regression analyses. A total of 1207 genes were identified as DEGs between recurrence and no-recurrence samples, including 726 downregulated and 481 upregulated genes. Using SVM analysis and five gene expression profile data confirmation, a 15-gene signature (HES5, ZNF417, GLRA2, OR8D2, HOXA7, FABP6, MUSK, HTR6, GRIP2, KLRK1, VEGFA, AKAP12, RHEB, NCRNA00152 and PMEPA1) were identified as a predictor of recurrence risk and prognosis for colon cancer patients. Our identified 15-gene signature may be useful to classify colon cancer patients with different prognosis and some genes in this signature may represent new therapeutic targets. Copyright © 2016. Published by Elsevier B.V.

Massive collisions in debris disks: possible application to the beta Pic disc

NASA Astrophysics Data System (ADS)

Kral, Q.; Thébault, P.; Augereau, J.-C.; Boccaletti, A.; Charnoz, S.

2014-09-01

The new LIDT-DD code has been used to study massive collisions in debris discs. This new hybrid model is a fully self-consistent code coupling dynamics and collisions to study debris discs (Kral et al. 2013). It models the full complexity of debris discs' physics such as high velocity collisions, radiation-pressure affected orbits, wide range of grains' dynamical behaviour, etc. LIDT-DD can be used on many possible applications. Our first test case concerns the violent breakup of a massive planetesimal such as the ones happening during the late stages of planetary formation or with the biggest bodies in debris belts. We investigate the duration, magnitude and spatial structure of the signature left by such a violent event, as well as its observational detectability. We find that the breakup of a Ceres-sized body creates an asymmetric dust disc that is homogenized, by the coupled action of collisions and dynamics. The luminosity excess in the breakup's aftermath should be detectable by mid-IR photometry, from a 30 pc distance. As for the asymmetric structures, we derive synthetic images for the SPHERE/VLT and MIRI/JWST instruments, showing that they should be clearly visible and resolved from a 10 pc distance. We explain the observational signature of such impacts and give scaling laws to extrapolate our results to different configurations. These first results confirm that our code can be used to study the massive collision scenario to explain some asymmetries in the Beta-Pic disc.

Advanced Subsonic Technology (AST) Area of Interest (AOI) 6: Develop and Validate Aeroelastic Codes for Turbomachinery

NASA Technical Reports Server (NTRS)

Gardner, Kevin D.; Liu, Jong-Shang; Murthy, Durbha V.; Kruse, Marlin J.; James, Darrell

1999-01-01

AlliedSignal Engines, in cooperation with NASA GRC (National Aeronautics and Space Administration Glenn Research Center), completed an evaluation of recently-developed aeroelastic computer codes using test cases from the AlliedSignal Engines fan blisk and turbine databases. Test data included strain gage, performance, and steady-state pressure information obtained for conditions where synchronous or flutter vibratory conditions were found to occur. Aeroelastic codes evaluated included quasi 3-D UNSFLO (MIT Developed/AE Modified, Quasi 3-D Aeroelastic Computer Code), 2-D FREPS (NASA-Developed Forced Response Prediction System Aeroelastic Computer Code), and 3-D TURBO-AE (NASA/Mississippi State University Developed 3-D Aeroelastic Computer Code). Unsteady pressure predictions for the turbine test case were used to evaluate the forced response prediction capabilities of each of the three aeroelastic codes. Additionally, one of the fan flutter cases was evaluated using TURBO-AE. The UNSFLO and FREPS evaluation predictions showed good agreement with the experimental test data trends, but quantitative improvements are needed. UNSFLO over-predicted turbine blade response reductions, while FREPS under-predicted them. The inviscid TURBO-AE turbine analysis predicted no discernible blade response reduction, indicating the necessity of including viscous effects for this test case. For the TURBO-AE fan blisk test case, significant effort was expended getting the viscous version of the code to give converged steady flow solutions for the transonic flow conditions. Once converged, the steady solutions provided an excellent match with test data and the calibrated DAWES (AlliedSignal 3-D Viscous Steady Flow CFD Solver). However, efforts expended establishing quality steady-state solutions prevented exercising the unsteady portion of the TURBO-AE code during the present program. AlliedSignal recommends that unsteady pressure measurement data be obtained for both test cases examined for use in aeroelastic code validation.

CANDO and the infinite drug discovery frontier

PubMed Central

Minie, Mark; Chopra, Gaurav; Sethi, Geetika; Horst, Jeremy; White, George; Roy, Ambrish; Hatti, Kaushik; Samudrala, Ram

2014-01-01

The Computational Analysis of Novel Drug Opportunities (CANDO) platform (http://protinfo.org/cando) uses similarity of compound–proteome interaction signatures to infer homology of compound/drug behavior. We constructed interaction signatures for 3733 human ingestible compounds covering 48,278 protein structures mapping to 2030 indications based on basic science methodologies to predict and analyze protein structure, function, and interactions developed by us and others. Our signature comparison and ranking approach yielded benchmarking accuracies of 12–25% for 1439 indications with at least two approved compounds. We prospectively validated 49/82 ‘high value’ predictions from nine studies covering seven indications, with comparable or better activity to existing drugs, which serve as novel repurposed therapeutics. Our approach may be generalized to compounds beyond those approved by the FDA, and can also consider mutations in protein structures to enable personalization. Our platform provides a holistic multiscale modeling framework of complex atomic, molecular, and physiological systems with broader applications in medicine and engineering. PMID:24980786

Theoretical Characterizaiton of Visual Signatures (Muzzle Flash)

NASA Astrophysics Data System (ADS)

Kashinski, D. O.; Scales, A. N.; Vanderley, D. L.; Chase, G. M.; di Nallo, O. E.; Byrd, E. F. C.

2014-05-01

We are investigating the accuracy of theoretical models used to predict the visible, ultraviolet and infrared spectra of product materials ejected from the muzzle of currently fielded systems. Recent advances in solid propellants has made the management of muzzle signature (flash) a principle issue in weapons development across the calibers. A priori prediction of the electromagnetic spectra of formulations will allow researchers to tailor blends that yield desired signatures and determine spectrographic detection ranges. We are currently employing quantum chemistry methods at various levels of sophistication to optimize molecular geometries, compute vibrational frequencies, and determine the optical spectra of specific gas-phase molecules and radicals of interest. Electronic excitations are being computed using Time Dependent Density Functional Theory (TD-DFT). A comparison of computational results to experimental values found in the literature is used to assess the affect of basis set and functional choice on calculation accuracy. The current status of this work will be presented at the conference. Work supported by the ARL, and USMA.

Theoretical Characterization of Visual Signatures and Calculation of Approximate Global Harmonic Frequency Scaling Factors

NASA Astrophysics Data System (ADS)

Kashinski, D. O.; Nelson, R. G.; Chase, G. M.; di Nallo, O. E.; Byrd, E. F. C.

2016-05-01

We are investigating the accuracy of theoretical models used to predict the visible, ultraviolet, and infrared spectra, as well as other properties, of product materials ejected from the muzzle of currently fielded systems. Recent advances in solid propellants has made the management of muzzle signature (flash) a principle issue in weapons development across the calibers. A priori prediction of the electromagnetic spectra of formulations will allow researchers to tailor blends that yield desired signatures and determine spectrographic detection ranges. Quantum chemistry methods at various levels of sophistication have been employed to optimize molecular geometries, compute unscaled harmonic frequencies, and determine the optical spectra of specific gas-phase species. Electronic excitations are being computed using Time Dependent Density Functional Theory (TD-DFT). Calculation of approximate global harmonic frequency scaling factors for specific DFT functionals is also in progress. A full statistical analysis and reliability assessment of computational results is currently underway. Work supported by the ARL, DoD-HPCMP, and USMA.

FASCODE - Fast Atmospheric Signature Code (Spectral Transmittance and Radiance)

DTIC Science & Technology

1978-01-16

cA6 Approvued o ulcrlae distrnibuin nimtd I? OSTIUTIN TAEMNT(. te ~FrAc1aieW iRD ADDRES 10- iiON 1diE$@NT.t haul fl TASK VIS. dn IPLM nTAR viNOT...the Voigt line shape profile model discussed above. In addition, the Voigt model provides a proper treatment of the transition region at those

Animating a Human Body Mesh with Maya for Doppler Signature Computer Modeling

DTIC Science & Technology

2009-06-01

three color-coded transformation tools attached to the AK47 mesh used to create the man with weapon model. Red, green, and blue correspond to the x-, y...animation scenario, the human moves in a natural walking motion cycle (figure 9). In the other two, the walking human carries an AK47 rifle in the port

Attenuated Signature-Tagged Mutagenesis Mutants of Brucella melitensis Identified during the Acute Phase of Infection in Mice

PubMed Central

Lestrate, P.; Dricot, A.; Delrue, R.-M.; Lambert, C.; Martinelli, V.; De Bolle, X.; Letesson, J.-J.; Tibor, A.

2003-01-01

For this study, we screened 1,152 signature-tagged mutagenesis mutants of Brucella melitensis 16M in a mouse model of infection and found 36 of them to be attenuated in vivo. Molecular characterization of transposon insertion sites showed that for four mutants, the affected genes were only present in Rhizobiaceae. Another mutant contained a disruption in a gene homologous to mosA, which is involved in rhizopine biosynthesis in some strains of Rhizobium, suggesting that this sugar may be involved in Brucella pathogenicity. A mutant was disrupted in a gene homologous to fliF, a gene potentially coding for the MS ring, a basal component of the flagellar system. Surprisingly, a mutant was affected in the rpoA gene, coding for the essential α-subunit of the RNA polymerase. This disruption leaves a partially functional protein, impaired for the activation of virB transcription, as demonstrated by the absence of induction of the virB promoter in the Tn5::rpoA background. The results presented here highlight the fact that the ability of Brucella to induce pathogenesis shares similarities with the molecular mechanisms used by both Rhizobium and Agrobacterium to colonize their hosts. PMID:14638795

Background-Modeling-Based Adaptive Prediction for Surveillance Video Coding.

PubMed

Zhang, Xianguo; Huang, Tiejun; Tian, Yonghong; Gao, Wen

2014-02-01

The exponential growth of surveillance videos presents an unprecedented challenge for high-efficiency surveillance video coding technology. Compared with the existing coding standards that were basically developed for generic videos, surveillance video coding should be designed to make the best use of the special characteristics of surveillance videos (e.g., relative static background). To do so, this paper first conducts two analyses on how to improve the background and foreground prediction efficiencies in surveillance video coding. Following the analysis results, we propose a background-modeling-based adaptive prediction (BMAP) method. In this method, all blocks to be encoded are firstly classified into three categories. Then, according to the category of each block, two novel inter predictions are selectively utilized, namely, the background reference prediction (BRP) that uses the background modeled from the original input frames as the long-term reference and the background difference prediction (BDP) that predicts the current data in the background difference domain. For background blocks, the BRP can effectively improve the prediction efficiency using the higher quality background as the reference; whereas for foreground-background-hybrid blocks, the BDP can provide a better reference after subtracting its background pixels. Experimental results show that the BMAP can achieve at least twice the compression ratio on surveillance videos as AVC (MPEG-4 Advanced Video Coding) high profile, yet with a slightly additional encoding complexity. Moreover, for the foreground coding performance, which is crucial to the subjective quality of moving objects in surveillance videos, BMAP also obtains remarkable gains over several state-of-the-art methods.

Predicting the Performance of an Axial-Flow Compressor

NASA Technical Reports Server (NTRS)

Steinke, R. J.

1986-01-01

Stage-stacking computer code (STGSTK) developed for predicting off-design performance of multi-stage axial-flow compressors. Code uses meanline stagestacking method. Stage and cumulative compressor performance calculated from representative meanline velocity diagrams located at rotor inlet and outlet meanline radii. Numerous options available within code. Code developed so user modify correlations to suit their needs.

Advanced turboprop noise prediction based on recent theoretical results

NASA Technical Reports Server (NTRS)

Farassat, F.; Padula, S. L.; Dunn, M. H.

1987-01-01

The development of a high speed propeller noise prediction code at Langley Research Center is described. The code utilizes two recent acoustic formulations in the time domain for subsonic and supersonic sources. The structure and capabilities of the code are discussed. Grid size study for accuracy and speed of execution on a computer is also presented. The code is tested against an earlier Langley code. Considerable increase in accuracy and speed of execution are observed. Some examples of noise prediction of a high speed propeller for which acoustic test data are available are given. A brisk derivation of formulations used is given in an appendix.

An edge-based solution-adaptive method applied to the AIRPLANE code

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Thomas, Scott D.; Cliff, Susan E.

1995-01-01

Computational methods to solve large-scale realistic problems in fluid flow can be made more efficient and cost effective by using them in conjunction with dynamic mesh adaption procedures that perform simultaneous coarsening and refinement to capture flow features of interest. This work couples the tetrahedral mesh adaption scheme, 3D_TAG, with the AIRPLANE code to solve complete aircraft configuration problems in transonic and supersonic flow regimes. Results indicate that the near-field sonic boom pressure signature of a cone-cylinder is improved, the oblique and normal shocks are better resolved on a transonic wing, and the bow shock ahead of an unstarted inlet is better defined.

Predicting ionizing radiation exposure using biochemically-inspired genomic machine learning.

PubMed

Zhao, Jonathan Z L; Mucaki, Eliseos J; Rogan, Peter K

2018-01-01

Background: Gene signatures derived from transcriptomic data using machine learning methods have shown promise for biodosimetry testing. These signatures may not be sufficiently robust for large scale testing, as their performance has not been adequately validated on external, independent datasets. The present study develops human and murine signatures with biochemically-inspired machine learning that are strictly validated using k-fold and traditional approaches. Methods: Gene Expression Omnibus (GEO) datasets of exposed human and murine lymphocytes were preprocessed via nearest neighbor imputation and expression of genes implicated in the literature to be responsive to radiation exposure (n=998) were then ranked by Minimum Redundancy Maximum Relevance (mRMR). Optimal signatures were derived by backward, complete, and forward sequential feature selection using Support Vector Machines (SVM), and validated using k-fold or traditional validation on independent datasets. Results: The best human signatures we derived exhibit k-fold validation accuracies of up to 98% ( DDB2 ,  PRKDC , TPP2 , PTPRE , and GADD45A ) when validated over 209 samples and traditional validation accuracies of up to 92% ( DDB2 ,  CD8A ,  TALDO1 ,  PCNA ,  EIF4G2 ,  LCN2 ,  CDKN1A ,  PRKCH ,  ENO1 ,  and PPM1D ) when validated over 85 samples. Some human signatures are specific enough to differentiate between chemotherapy and radiotherapy. Certain multi-class murine signatures have sufficient granularity in dose estimation to inform eligibility for cytokine therapy (assuming these signatures could be translated to humans). We compiled a list of the most frequently appearing genes in the top 20 human and mouse signatures. More frequently appearing genes among an ensemble of signatures may indicate greater impact of these genes on the performance of individual signatures. Several genes in the signatures we derived are present in previously proposed signatures. Conclusions: Gene signatures for ionizing radiation exposure derived by machine learning have low error rates in externally validated, independent datasets, and exhibit high specificity and granularity for dose estimation.

The prognostic value of a seven-microRNA classifier as a novel biomarker for the prediction and detection of recurrence in glioma patients.

PubMed

Chen, Wanghao; Yu, Qiang; Chen, Bo; Lu, Xingyu; Li, Qiaoyu

2016-08-16

Glioma is often diagnosed at a later stage, and the high risk of recurrence remains a major challenge. We hypothesized that the microRNA expression profile may serve as a biomarker for the prognosis and prediction of glioblastoma recurrence. We defined microRNAs that were associated with good and poor prognosis in 300 specimens of glioblastoma from the Cancer Genome Atlas. By analyzing microarray gene expression data and clinical information from three random groups, we identified 7 microRNAs that have prognostic and prognostic accuracy: microRNA-124a, microRNA-129, microRNA-139, microRNA-15b, microRNA-21, microRNA-218 and microRNA-7. The differential expression of these miRNAs was verified using an independent set of glioma samples from the Affiliated People's Hospital of Jiangsu University. We used the log-rank test and the Kaplan-Meier method to estimate correlations between the miRNA signature and disease-free survival/overall survival. Using the LASSO model, we observed a uniform significant difference in disease-free survival and overall survival between patients with high-risk and low-risk miRNA signature scores. Furthermore, the prognostic capability of the seven-miRNA signature was demonstrated by receiver operator characteristic curve analysis. A Circos plot was generated to examine the network of genes and pathways predicted to be targeted by the seven-miRNA signature. The seven-miRNA-based classifier should be useful in the stratification and individualized management of patients with glioma.

Comparison of Space Shuttle Hot Gas Manifold analysis to air flow data

NASA Technical Reports Server (NTRS)

Mcconnaughey, P. K.

1988-01-01

This paper summarizes several recent analyses of the Space Shuttle Main Engine Hot Gas Manifold and compares predicted flow environments to air flow data. Codes used in these analyses include INS3D, PAGE, PHOENICS, and VAST. Both laminar (Re = 250, M = 0.30) and turbulent (Re = 1.9 million, M = 0.30) results are discussed, with the latter being compared to data for system losses, outer wall static pressures, and manifold exit Mach number profiles. Comparison of predicted results for the turbulent case to air flow data shows that the analysis using INS3D predicted system losses within 1 percent error, while the PHOENICS, PAGE, and VAST codes erred by 31, 35, and 47 percent, respectively. The INS3D, PHOENICS, and PAGE codes did a reasonable job of predicting outer wall static pressure, while the PHOENICS code predicted exit Mach number profiles with acceptable accuracy. INS3D was approximately an order of magnitude more efficient than the other codes in terms of code speed and memory requirements. In general, it is seen that complex internal flows in manifold-like geometries can be predicted with a limited degree of confidence, and further development is necessary to improve both efficiency and accuracy of codes if they are to be used as design tools for complex three-dimensional geometries.

Multigene signature for predicting prognosis of patients with 1p19q co-deletion diffuse glioma.

PubMed

Hu, Xin; Martinez-Ledesma, Emmanuel; Zheng, Siyuan; Kim, Hoon; Barthel, Floris; Jiang, Tao; Hess, Kenneth R; Verhaak, Roel G W

2017-06-01

Co-deletion of 1p and 19q marks a diffuse glioma subtype associated with relatively favorable overall survival; however, heterogeneous clinical outcomes are observed within this category. We assembled gene expression profiles and sample annotation of 374 glioma patients carrying the 1p/19q co-deletion. We predicted 1p/19q status using gene expression when annotation was missing. A first cohort was randomly split into training (n = 170) and a validation dataset (n = 163). A second validation set consisted of 41 expression profiles. An elastic-net penalized Cox proportional hazards model was applied to build a classifier model through cross-validation within the training dataset. The selected 35-gene signature was used to identify high-risk and low-risk groups in the validation set, which showed significantly different overall survival (P = .00058, log-rank test). For time-to-death events, the high-risk group predicted by the gene signature yielded a hazard ratio of 1.78 (95% confidence interval, 1.02-3.11). The signature was also significantly associated with clinical outcome in the The Cancer Genome Atlas (CGA) IDH-mutant 1p/19q wild-type and IDH-wild-type glioma cohorts. Pathway analysis suggested that high risk was associated with increased acetylation activity and inflammatory response. Tumor purity was found to be significantly decreased in high-risk IDH-mutant with 1p/19q co-deletion gliomas and IDH-wild-type glioblastomas but not in IDH-wild-type lower grade or IDH-mutant, non-co-deleted gliomas. We identified a 35-gene signature that identifies high-risk and low-risk categories of 1p/19q positive glioma patients. We have demonstrated heterogeneity amongst a relatively new glioma subtype and provided a stepping stone towards risk stratification. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Non-conservative evolution in Algols: where is the matter?

NASA Astrophysics Data System (ADS)

Deschamps, R.; Braun, K.; Jorissen, A.; Siess, L.; Baes, M.; Camps, P.

2015-05-01

Context. There is indirect evidence of non-conservative evolutions in Algols. However, the systemic mass-loss rate is poorly constrained by observations and generally set as a free parameter in binary-star evolution simulations. Moreover, systemic mass loss may lead to observational signatures that still need to be found. Aims: Within the "hotspot" ejection mechanism, some of the material that is initially transferred from the companion star via an accretion stream is expelled from the system due to the radiative energy released on the gainer's surface by the impacting material. The objective of this paper is to retrieve observable quantities from this process and to compare them with observations. Methods: We investigate the impact of the outflowing gas and the possible presence of dust grains on the spectral energy distribution (SED). We used the 1D plasma code Cloudy and compared the results with the 3D Monte-Carlo radiative transfer code Skirt for dusty simulations. The circumbinary mass-distribution and binary parameters were computed with state-of-the-art binary calculations done with the Binstar evolution code. Results: The outflowing material reduces the continuum flux level of the stellar SED in the optical and UV. Because of the time-dependence of this effect, it may help to distinguish between different ejection mechanisms. If present, dust leads to observable infrared excesses, even with low dust-to-gas ratios, and traces the cold material at large distances from the star. By searching for this dust emission in the WISE catalogue, we found a small number of Algols showing infrared excesses, among which the two rather surprising objects SX Aur and CZ Vel. We find that some binary B[e] stars show the same strong Balmer continuum as we predict with our models. However, direct evidence of systemic mass loss is probably not observable in genuine Algols, since these systems no longer eject mass through the hotspot mechanism. Furthermore, owing to its high velocity, the outflowing material dissipates in a few hundred years. If hot enough, the hotspot may produce highly ionised species, such as Si iv, and observable characteristics that are typical of W Ser systems. Conclusions: If present, systemic mass loss leads to clear observational imprints. These signatures are not to be found in genuine Algols but in the closely related β Lyraes, W Serpentis stars, double periodic variables, symbiotic Algols, and binary B[e] stars. We emphasise the need for further observations of such objects where systemic mass loss is most likely to occur. Appendices are available in electronic form at http://www.aanda.org

High spin states in 164Lu

NASA Astrophysics Data System (ADS)

Juneja, P.; Gupta, S. L.; Pancholi, S. C.; Kumar, Ashok; Mehta, D.; Chaturvedi, L.; Katoch, S. K.; Malik, S.; Shanker, G.; Bhowmik, R. K.; Muralithar, S.; Rodrigues, G.; Singh, R. P.

1996-03-01

High spin states in the odd-odd 164Lu nucleus have been investigated for the first time, through in-beam gamma-ray spectroscopy, following the 150Sm(19F,5n) reaction at beam energy Elab=105 MeV. Four bands, including two signature split bands are identified. The interpretation of the experimental results is discussed in comparison with the existing data in the neighboring nuclei and in the framework of the cranked shell model. The πh11/2⊗νi13/2 yrast band exhibits anomalous signature splitting and signature inversion is observed at a spin of 18ħ. This provides the missing datum for the systematics of staggering and signature inversion for the neighboring odd-odd N=93 isotones and supports the predictions of angular-momentum projection calculations by Hara and Sun. In the second signature split πh 11/2h9/2 band, the AB neutron crossing occurs at a rotational frequency of ~0.29 MeV. This is indicative of the disappearance of the blocking effect of the odd neutron.

Light transport feature for SCINFUL.

PubMed

Etaati, G R; Ghal-Eh, N

2008-03-01

An extended version of the scintillator response function prediction code SCINFUL has been developed by incorporating PHOTRACK, a Monte Carlo light transport code. Comparisons of calculated and experimental results for organic scintillators exposed to neutrons show that the extended code improves the predictive capability of SCINFUL.

Dopamine reward prediction error coding.

PubMed

Schultz, Wolfram

2016-03-01

Reward prediction errors consist of the differences between received and predicted rewards. They are crucial for basic forms of learning about rewards and make us strive for more rewards-an evolutionary beneficial trait. Most dopamine neurons in the midbrain of humans, monkeys, and rodents signal a reward prediction error; they are activated by more reward than predicted (positive prediction error), remain at baseline activity for fully predicted rewards, and show depressed activity with less reward than predicted (negative prediction error). The dopamine signal increases nonlinearly with reward value and codes formal economic utility. Drugs of addiction generate, hijack, and amplify the dopamine reward signal and induce exaggerated, uncontrolled dopamine effects on neuronal plasticity. The striatum, amygdala, and frontal cortex also show reward prediction error coding, but only in subpopulations of neurons. Thus, the important concept of reward prediction errors is implemented in neuronal hardware.

Dopamine reward prediction error coding

PubMed Central

Schultz, Wolfram

2016-01-01

Reward prediction errors consist of the differences between received and predicted rewards. They are crucial for basic forms of learning about rewards and make us strive for more rewards—an evolutionary beneficial trait. Most dopamine neurons in the midbrain of humans, monkeys, and rodents signal a reward prediction error; they are activated by more reward than predicted (positive prediction error), remain at baseline activity for fully predicted rewards, and show depressed activity with less reward than predicted (negative prediction error). The dopamine signal increases nonlinearly with reward value and codes formal economic utility. Drugs of addiction generate, hijack, and amplify the dopamine reward signal and induce exaggerated, uncontrolled dopamine effects on neuronal plasticity. The striatum, amygdala, and frontal cortex also show reward prediction error coding, but only in subpopulations of neurons. Thus, the important concept of reward prediction errors is implemented in neuronal hardware. PMID:27069377

A Learning System for Discriminating Variants of Malicious Network Traffic

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

Beaver, Justin M; Symons, Christopher T; Gillen, Rob

Modern computer network defense systems rely primarily on signature-based intrusion detection tools, which generate alerts when patterns that are pre-determined to be malicious are encountered in network data streams. Signatures are created reactively, and only after in-depth manual analysis of a network intrusion. There is little ability for signature-based detectors to identify intrusions that are new or even variants of an existing attack, and little ability to adapt the detectors to the patterns unique to a network environment. Due to these limitations, the need exists for network intrusion detection techniques that can more comprehensively address both known unknown networkbased attacksmore » and can be optimized for the target environment. This work describes a system that leverages machine learning to provide a network intrusion detection capability that analyzes behaviors in channels of communication between individual computers. Using examples of malicious and non-malicious traffic in the target environment, the system can be trained to discriminate between traffic types. The machine learning provides insight that would be difficult for a human to explicitly code as a signature because it evaluates many interdependent metrics simultaneously. With this approach, zero day detection is possible by focusing on similarity to known traffic types rather than mining for specific bit patterns or conditions. This also reduces the burden on organizations to account for all possible attack variant combinations through signatures. The approach is presented along with results from a third-party evaluation of its performance.« less

A Whitham-Theory Sonic-Boom Analysis of the TU-144 Aircraft at a Mach Number of 2.2

NASA Technical Reports Server (NTRS)

Mack, Robert J.

1999-01-01

Officially, the Tu-144 was the first supersonic-cruise, passenger-carrying aircraft to enter commercial service. Design, construction, and testing were carried out by the Soviet Union, flight certification was by the Soviet Union, and the only regular passenger flights were scheduled and flown across the territory of the Soviet Union. Although it was not introduced to international passenger service, there were many significant engineering accomplishments achieved in the design, production, and flight of this aircraft. Development of the aircraft began with a prototype stage. Systematic testing and redesign led to a production aircraft in discrete stages that measurably improved the performance of the aircraft from the starting concept to final aircraft certification. It flew in competition with the English-French Concorde for a short time, but was withdrawn from national commercial service due to a lack of interest by airlines outside the Soviet Union. NASA became interested in the Tu- 144 aircraft when it was offered for use as a flying "testbed" in the study of operating characteristics of a supersonic-cruise commercial airplane. Since it had been in supersonic-cruise service, the Tu- 144 had operational characteris'tics similar to those anticipated in the conceptual aircraft designs being studied by the United States aircraft companies. In addition to the other operational tests being conducted on the Tu-144 aircraft, it was proposed that two sets of sonic-boom pressure signature measurements be made. The first set would be made on the ground, using techniques and devices similar to those in reference I and many other subsequent studies. A second set would be made in the air with an instrumented aircraft flying close under the Tu-144 in supersonic flight. Such in-flight measurements would require pressure gages that were capable of accurately recording the flow-field overpressures generated by the Tu- 144 at relatively close distances under the vehicle. Therefore, an analysis of the Tu-144 was made to obtain predictions of pressure signature shape and shock strengths at cruise conditions so that the range and characteristics of the required pressure gages could be determined well in advance of the tests. Cancellation of the sonic-boom signature measurement part of the tests removed the need for these pressure gages. Since CFD methods would be used to analyze the aerodynamic performance of the Tu-144 and make similar pressure signature predictions, the relatively quick and simple Whitham-theory pressure signature predictions presented in this paper could be used for comparisons. Pressure signature predictions of sonic-boom disturbances from the Tu- 144 aircraft were obtained from geometry derived from a three-view description of the production aircraft. The geometry was used to calculate aerodynamic performance characteristics at supersonic-cruise conditions. These characteristics and Whitham/Walkden sonic-boom theory were employed to obtain F-functions and flow-field pressure signature predictions at a Mach number of 2.2, at a cruise altitude of 61000 feet, and at a cruise weight of 350000 pounds.

Bi-orthogonal Symbol Mapping and Detection in Optical CDMA Communication System

NASA Astrophysics Data System (ADS)

Liu, Maw-Yang

2017-12-01

In this paper, the bi-orthogonal symbol mapping and detection scheme is investigated in time-spreading wavelength-hopping optical CDMA communication system. The carrier-hopping prime code is exploited as signature sequence, whose put-of-phase autocorrelation is zero. Based on the orthogonality of carrier-hopping prime code, the equal weight orthogonal signaling scheme can be constructed, and the proposed scheme using bi-orthogonal symbol mapping and detection can be developed. The transmitted binary data bits are mapped into corresponding bi-orthogonal symbols, where the orthogonal matrix code and its complement are utilized. In the receiver, the received bi-orthogonal data symbol is fed into the maximum likelihood decoder for detection. Under such symbol mapping and detection, the proposed scheme can greatly enlarge the Euclidean distance; hence, the system performance can be drastically improved.

A comparative study of Message Digest 5(MD5) and SHA256 algorithm

NASA Astrophysics Data System (ADS)

Rachmawati, D.; Tarigan, J. T.; Ginting, A. B. C.

2018-03-01

The document is a collection of written or printed data containing information. The more rapid advancement of technology, the integrity of a document should be kept. Because of the nature of an open document means the document contents can be read and modified by many parties so that the integrity of the information as a content of the document is not preserved. To maintain the integrity of the data, it needs to create a mechanism which is called a digital signature. A digital signature is a specific code which is generated from the function of producing a digital signature. One of the algorithms that used to create the digital signature is a hash function. There are many hash functions. Two of them are message digest 5 (MD5) and SHA256. Those both algorithms certainly have its advantages and disadvantages of each. The purpose of this research is to determine the algorithm which is better. The parameters which used to compare that two algorithms are the running time and complexity. The research results obtained from the complexity of the Algorithms MD5 and SHA256 is the same, i.e., ⊖ (N), but regarding the speed is obtained that MD5 is better compared to SHA256.

The LncRNA Connectivity Map: Using LncRNA Signatures to Connect Small Molecules, LncRNAs, and Diseases.

PubMed

Yang, Haixiu; Shang, Desi; Xu, Yanjun; Zhang, Chunlong; Feng, Li; Sun, Zeguo; Shi, Xinrui; Zhang, Yunpeng; Han, Junwei; Su, Fei; Li, Chunquan; Li, Xia

2017-07-27

Well characterized the connections among diseases, long non-coding RNAs (lncRNAs) and drugs are important for elucidating the key roles of lncRNAs in biological mechanisms in various biological states. In this study, we constructed a database called LNCmap (LncRNA Connectivity Map), available at http://www.bio-bigdata.com/LNCmap/ , to establish the correlations among diseases, physiological processes, and the action of small molecule therapeutics by attempting to describe all biological states in terms of lncRNA signatures. By reannotating the microarray data from the Connectivity Map database, the LNCmap obtained 237 lncRNA signatures of 5916 instances corresponding to 1262 small molecular drugs. We provided a user-friendly interface for the convenient browsing, retrieval and download of the database, including detailed information and the associations of drugs and corresponding affected lncRNAs. Additionally, we developed two enrichment analysis methods for users to identify candidate drugs for a particular disease by inputting the corresponding lncRNA expression profiles or an associated lncRNA list and then comparing them to the lncRNA signatures in our database. Overall, LNCmap could significantly improve our understanding of the biological roles of lncRNAs and provide a unique resource to reveal the connections among drugs, lncRNAs and diseases.

Preliminary sonic boom correlation of predicted and measured levels for STS-1 entry

NASA Technical Reports Server (NTRS)

Garcia, F., Jr.; Morrison, K. M.; Jones, J. H.; Henderson, H. R.

1982-01-01

A preliminary analysis correlating peaks from sonic boom pressure signatures recorded during the descent trajectory of the Orbiter Columbia, which landed in the dry lake bed at Edwards Air Force Base (EAFB), California, with measured wind tunnel signatures extrapolated from flight altitudes to the ground has been made for Mach numbers ranging from 1.3 to 6. The flight pressure signatures were recorded by microphones positioned at ground level near the groundtrack, whereas the wind tunnel signatures were measured during a test of a 0.0041-scale model Orbiter. The agreement between overpressure estimates based on wind tunnel data using preliminary flight trajectory data and oscillograph traces from ground measurements appears reasonable at this time for the range of Mach numbers considered. More detailed studies using final flight trajectory data and digitized ground measured data will be performed.

Search for photonic signatures of gauge-mediated supersymmetry in 8 TeV p p collisions with the ATLAS detector

DOE PAGES

Aad, G.

2015-10-06

A search is presented for photonic signatures motivated by generalized models of gauge-mediated supersymmetry breaking. This search makes use of 20.3 fb⁻¹ of proton-proton collision data at √s = 8 TeV recorded by the ATLAS detector at the LHC, and explores models dominated by both strong and electroweak production of supersymmetric partner states. Four experimental signatures incorporating an isolated photon and significant missing transverse momentum are explored. These signatures include events with an additional photon, lepton, b-quark jet, or jet activity not associated with any specific underlying quark flavor. In this study, no significant excess of events is observed abovemore » the Standard Model prediction and model-dependent 95% confidence-level exclusion limits are set.« less

Application of connectivity mapping in predictive toxicology based on gene-expression similarity.

PubMed

Smalley, Joshua L; Gant, Timothy W; Zhang, Shu-Dong

2010-02-09

Connectivity mapping is the process of establishing connections between different biological states using gene-expression profiles or signatures. There are a number of applications but in toxicology the most pertinent is for understanding mechanisms of toxicity. In its essence the process involves comparing a query gene signature generated as a result of exposure of a biological system to a chemical to those in a database that have been previously derived. In the ideal situation the query gene-expression signature is characteristic of the event and will be matched to similar events in the database. Key criteria are therefore the means of choosing the signature to be matched and the means by which the match is made. In this article we explore these concepts with examples applicable to toxicology. (c) 2009 Elsevier Ireland Ltd. All rights reserved.

GeneSigDB: a manually curated database and resource for analysis of gene expression signatures

PubMed Central

Culhane, Aedín C.; Schröder, Markus S.; Sultana, Razvan; Picard, Shaita C.; Martinelli, Enzo N.; Kelly, Caroline; Haibe-Kains, Benjamin; Kapushesky, Misha; St Pierre, Anne-Alyssa; Flahive, William; Picard, Kermshlise C.; Gusenleitner, Daniel; Papenhausen, Gerald; O'Connor, Niall; Correll, Mick; Quackenbush, John

2012-01-01

GeneSigDB (http://www.genesigdb.org or http://compbio.dfci.harvard.edu/genesigdb/) is a database of gene signatures that have been extracted and manually curated from the published literature. It provides a standardized resource of published prognostic, diagnostic and other gene signatures of cancer and related disease to the community so they can compare the predictive power of gene signatures or use these in gene set enrichment analysis. Since GeneSigDB release 1.0, we have expanded from 575 to 3515 gene signatures, which were collected and transcribed from 1604 published articles largely focused on gene expression in cancer, stem cells, immune cells, development and lung disease. We have made substantial upgrades to the GeneSigDB website to improve accessibility and usability, including adding a tag cloud browse function, facetted navigation and a ‘basket’ feature to store genes or gene signatures of interest. Users can analyze GeneSigDB gene signatures, or upload their own gene list, to identify gene signatures with significant gene overlap and results can be viewed on a dynamic editable heatmap that can be downloaded as a publication quality image. All data in GeneSigDB can be downloaded in numerous formats including .gmt file format for gene set enrichment analysis or as a R/Bioconductor data file. GeneSigDB is available from http://www.genesigdb.org. PMID:22110038

Characterizing the Properties of a Woven SiC/SiC Composite Using W-CEMCAN Computer Code

NASA Technical Reports Server (NTRS)

Murthy, Pappu L. N.; Mital, Subodh K.; DiCarlo, James A.

1999-01-01

A micromechanics based computer code to predict the thermal and mechanical properties of woven ceramic matrix composites (CMC) is developed. This computer code, W-CEMCAN (Woven CEramic Matrix Composites ANalyzer), predicts the properties of two-dimensional woven CMC at any temperature and takes into account various constituent geometries and volume fractions. This computer code is used to predict the thermal and mechanical properties of an advanced CMC composed of 0/90 five-harness (5 HS) Sylramic fiber which had been chemically vapor infiltrated (CVI) with boron nitride (BN) and SiC interphase coatings and melt-infiltrated (MI) with SiC. The predictions, based on the bulk constituent properties from the literature, are compared with measured experimental data. Based on the comparison. improved or calibrated properties for the constituent materials are then developed for use by material developers/designers. The computer code is then used to predict the properties of a composite with the same constituents but with different fiber volume fractions. The predictions are compared with measured data and a good agreement is achieved.

Use of the International Classification of Diseases, 9th revision, coding in identifying chronic hepatitis B virus infection in health system data: implications for national surveillance.

PubMed

Mahajan, Reena; Moorman, Anne C; Liu, Stephen J; Rupp, Loralee; Klevens, R Monina

2013-05-01

With increasing use electronic health records (EHR) in the USA, we looked at the predictive values of the International Classification of Diseases, 9th revision (ICD-9) coding system for surveillance of chronic hepatitis B virus (HBV) infection. The chronic HBV cohort from the Chronic Hepatitis Cohort Study was created based on electronic health records (EHR) of adult patients who accessed services from 2006 to 2008 from four healthcare systems in the USA. Using the gold standard of abstractor review to confirm HBV cases, we calculated the sensitivity, specificity, positive and negative predictive values using one qualifying ICD-9 code versus using two qualifying ICD-9 codes separated by 6 months or greater. Of 1 652 055 adult patients, 2202 (0.1%) were confirmed as having chronic HBV. Use of one ICD-9 code had a sensitivity of 83.9%, positive predictive value of 61.0%, and specificity and negative predictive values greater than 99%. Use of two hepatitis B-specific ICD-9 codes resulted in a sensitivity of 58.4% and a positive predictive value of 89.9%. Use of one or two hepatitis B ICD-9 codes can identify cases with chronic HBV infection with varying sensitivity and positive predictive values. As the USA increases the use of EHR, surveillance using ICD-9 codes may be reliable to determine the burden of chronic HBV infection and would be useful to improve reporting by state and local health departments.

Design of Experiments for Both Experimental and Analytical Study of Exhaust Plume Effects on Sonic Boom

NASA Technical Reports Server (NTRS)

Castner, Raymond S.

2009-01-01

Computational fluid dynamics (CFD) analysis has been performed to study the plume effects on sonic boom signature for isolated nozzle configurations. The objectives of these analyses were to provide comparison to past work using modern CFD analysis tools, to investigate the differences of high aspect ratio nozzles to circular (axisymmetric) nozzles, and to report the effects of under expanded nozzle operation on boom signature. CFD analysis was used to address the plume effects on sonic boom signature from a baseline exhaust nozzle. Nearfield pressure signatures were collected for nozzle pressure ratios (NPRs) between 6 and 10. A computer code was used to extrapolate these signatures to a ground-observed sonic boom N-wave. Trends show that there is a reduction in sonic boom N-wave signature as NPR is increased from 6 to 10. As low boom designs are developed and improved, there will be a need for understanding the interaction between the aircraft boat tail shocks and the exhaust nozzle plume. These CFD analyses will provide a baseline study for future analysis efforts. For further study, a design of experiments has been conducted to develop a hybrid method where both CFD and small scale wind tunnel testing will validate the observed trends. The CFD and testing will be used to screen a number of factors which are important to low boom propulsion integration, including boat tail angle, nozzle geometry, and the effect of spacing and stagger on nozzle pairs. To design the wind tunnel experiment, CFD was instrumental in developing a model which would provide adequate space to observe the nozzle and boat tail shock structure without interference from the wind tunnel walls.

Gene-expression signatures can distinguish gastric cancer grades and stages.

PubMed

Cui, Juan; Li, Fan; Wang, Guoqing; Fang, Xuedong; Puett, J David; Xu, Ying

2011-03-18

Microarray gene-expression data of 54 paired gastric cancer and adjacent noncancerous gastric tissues were analyzed, with the aim to establish gene signatures for cancer grades (well-, moderately-, poorly- or un-differentiated) and stages (I, II, III and IV), which have been determined by pathologists. Our statistical analysis led to the identification of a number of gene combinations whose expression patterns serve well as signatures of different grades and different stages of gastric cancer. A 19-gene signature was found to have discerning power between high- and low-grade gastric cancers in general, with overall classification accuracy at 79.6%. An expanded 198-gene panel allows the stratification of cancers into four grades and control, giving rise to an overall classification agreement of 74.2% between each grade designated by the pathologists and our prediction. Two signatures for cancer staging, consisting of 10 genes and 9 genes, respectively, provide high classification accuracies at 90.0% and 84.0%, among early-, advanced-stage cancer and control. Functional and pathway analyses on these signature genes reveal the significant relevance of the derived signatures to cancer grades and progression. To the best of our knowledge, this represents the first study on identification of genes whose expression patterns can serve as markers for cancer grades and stages.

Laboratory study of effects of sonic boom shaping on subjective loudness and acceptability

NASA Technical Reports Server (NTRS)

Leatherwood, Jack D.; Sullivan, Brenda M.

1992-01-01

A laboratory study was conducted to determine the effects of sonic boom signature shaping on subjective loudness and acceptability. The study utilized the sonic boom simulator at the Langley Research Center. A wide range of symmetrical, front-shock-minimized signature shapes were investigated together with a limited number of asymmetrical signatures. Subjective loudness judgments were obtained from 60 test subjects by using an 11-point numerical category scale. Acceptability judgments were obtained using the method of constant stimuli. Results were used to assess the relative predictive ability of several noise metrics, determine the loudness benefits of detailed boom shaping, and derive laboratory sonic boom acceptability criteria. These results indicated that the A-weighted sound exposure level, the Stevens Mark 7 Perceived Level, and the Zwicker Loudness Level metrics all performed well. Significant reductions in loudness were obtained by increasing front-shock rise time and/or decreasing front-shock overpressure of the front-shock minimized signatures. In addition, the asymmetrical signatures were rated to be slightly quieter than the symmetrical front-shock-minimized signatures of equal A-weighted sound exposure level. However, this result was based on a limited number of asymmetric signatures. The comparison of laboratory acceptability results with acceptability data obtained in more realistic situations also indicated good agreement.

Data integration of structured and unstructured sources for assigning clinical codes to patient stays

PubMed Central

Luyckx, Kim; Luyten, Léon; Daelemans, Walter; Van den Bulcke, Tim

2016-01-01

Objective Enormous amounts of healthcare data are becoming increasingly accessible through the large-scale adoption of electronic health records. In this work, structured and unstructured (textual) data are combined to assign clinical diagnostic and procedural codes (specifically ICD-9-CM) to patient stays. We investigate whether integrating these heterogeneous data types improves prediction strength compared to using the data types in isolation. Methods Two separate data integration approaches were evaluated. Early data integration combines features of several sources within a single model, and late data integration learns a separate model per data source and combines these predictions with a meta-learner. This is evaluated on data sources and clinical codes from a broad set of medical specialties. Results When compared with the best individual prediction source, late data integration leads to improvements in predictive power (eg, overall F-measure increased from 30.6% to 38.3% for International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnostic codes), while early data integration is less consistent. The predictive strength strongly differs between medical specialties, both for ICD-9-CM diagnostic and procedural codes. Discussion Structured data provides complementary information to unstructured data (and vice versa) for predicting ICD-9-CM codes. This can be captured most effectively by the proposed late data integration approach. Conclusions We demonstrated that models using multiple electronic health record data sources systematically outperform models using data sources in isolation in the task of predicting ICD-9-CM codes over a broad range of medical specialties. PMID:26316458

Low-Density Parity-Check (LDPC) Codes Constructed from Protographs

NASA Astrophysics Data System (ADS)

Thorpe, J.

2003-08-01

We introduce a new class of low-density parity-check (LDPC) codes constructed from a template called a protograph. The protograph serves as a blueprint for constructing LDPC codes of arbitrary size whose performance can be predicted by analyzing the protograph. We apply standard density evolution techniques to predict the performance of large protograph codes. Finally, we use a randomized search algorithm to find good protographs.

Software Assurance Curriculum Project Volume 1: Master of Software Assurance Reference Curriculum

DTIC Science & Technology

2010-08-01

activity by providing a check on the relevance and currency of the process used to develop the MSwA2010 curriculum content. Figure 2 is an expansion of...random oracle model, symmetric crypto primitives, modes of operations, asymmetric crypto primitives (Chapter 5) [16] Detailed design...encryption, public key encryption, digital signatures, message authentication codes, crypto protocols, cryptanalysis, and further detailed crypto

Non-Linear Acoustic Concealed Weapons Detector

DTIC Science & Technology

2006-05-01

signature analysis 8 the interactions of the beams with concealed objects. The Khokhlov- Zabolotskaya-Kuznetsov ( KZK ) equation is the most widely used...Hamilton developed a finite difference method based on the KZK equation to model pulsed acoustic emissions from axial symmetric sources. Using a...College of William & Mary, we have developed a simulation code using the KZK equation to model non-linear acoustic beams and visualize beam patterns

Initial Results: An Ultra-Low-Background Germanium Crystal Array

DTIC Science & Technology

2010-09-01

data (focused on γ -γ coincidence signatures) (Smith et al., 2004) and the Multi- Isotope Coincidence Analysis code (MICA) (Warren et al., 2006). The...The follow-on “CASCADES” project aims to develop a multicoincidence data- analysis package and make robust fission-product demonstration measurements...sensitivity. This effort is focused on improving gamma analysis capabilities for nuclear detonation detection (NDD) applications, e.g., nuclear treaty

37 CFR 270.1 - Notice of use of sound recordings under statutory license.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Notice and by the date of the signature. (e) Filing notices; fees. The original and three copies shall be... sound recordings when used under either section 112(e) or 114(d)(2) of title 17, United States Code, or... notice to sound recording copyright owners of the use of their works under section 112(e) or 114(d)(2) of...

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.

Vibration Response Models of a Stiffened Aluminum Plate Excited by a Shaker

NASA Technical Reports Server (NTRS)

Cabell, Randolph H.

2008-01-01

Numerical models of structural-acoustic interactions are of interest to aircraft designers and the space program. This paper describes a comparison between two energy finite element codes, a statistical energy analysis code, a structural finite element code, and the experimentally measured response of a stiffened aluminum plate excited by a shaker. Different methods for modeling the stiffeners and the power input from the shaker are discussed. The results show that the energy codes (energy finite element and statistical energy analysis) accurately predicted the measured mean square velocity of the plate. In addition, predictions from an energy finite element code had the best spatial correlation with measured velocities. However, predictions from a considerably simpler, single subsystem, statistical energy analysis model also correlated well with the spatial velocity distribution. The results highlight a need for further work to understand the relationship between modeling assumptions and the prediction results.

Identifying anti-cancer drug response related genes using an integrative analysis of transcriptomic and genomic variations with cell line-based drug perturbations.

PubMed

Sun, Yi; Zhang, Wei; Chen, Yunqin; Ma, Qin; Wei, Jia; Liu, Qi

2016-02-23

Clinical responses to anti-cancer therapies often only benefit a defined subset of patients. Predicting the best treatment strategy hinges on our ability to effectively translate genomic data into actionable information on drug responses. To achieve this goal, we compiled a comprehensive collection of baseline cancer genome data and drug response information derived from a large panel of cancer cell lines. This data set was applied to identify the signature genes relevant to drug sensitivity and their resistance by integrating CNVs and the gene expression of cell lines with in vitro drug responses. We presented an efficient in-silico pipeline for integrating heterogeneous cell line data sources with the simultaneous modeling of drug response values across all the drugs and cell lines. Potential signature genes correlated with drug response (sensitive or resistant) in different cancer types were identified. Using signature genes, our collaborative filtering-based drug response prediction model outperformed the 44 algorithms submitted to the DREAM competition on breast cancer cells. The functions of the identified drug response related signature genes were carefully analyzed at the pathway level and the synthetic lethality level. Furthermore, we validated these signature genes by applying them to the classification of the different subtypes of the TCGA tumor samples, and further uncovered their in vivo implications using clinical patient data. Our work may have promise in translating genomic data into customized marker genes relevant to the response of specific drugs for a specific cancer type of individual patients.

Identifying gnostic predictors of the vaccine response

PubMed Central

Haining, W. Nicholas; Pulendran, Bali

2012-01-01

Molecular predictors of the response to vaccination could transform vaccine development. They would allow larger numbers of vaccine candidates to be rapidly screened, shortening the development time for new vaccines. Gene-expression based predictors of vaccine response have shown early promise. However, a limitation of gene-expression based predictors is that they often fail to reveal the mechanistic basis for their ability to classify response. Linking predictive signatures to the function of their component genes would advance basic understanding of vaccine immunity and also improve the robustness of outcome classification. New analytic tools now allow more biological meaning to be extracted from predictive signatures. Functional genomic approaches to perturb gene expression in mammalian cells permit the function of predictive genes to be surveyed in highly parallel experiments. The challenge for vaccinologists is therefore to use these tools to embed mechanistic insights into predictors of vaccine response. PMID:22633886

Quantitative 1D diffraction signatures during dual detector scatter VOI breast CBCT

NASA Astrophysics Data System (ADS)

LeClair, Robert J.

2017-03-01

Dual detector VOI scatter CBCT is similar to dual detector VOI CBCT except that during the high resolution scan, the low resolution flat panel detector is also used to capture the scattered photons. Simulations show a potential use of scatter to diagnose suspicious VOIs. Energy integrated signals due to scatter (EISs) were computed for a specific imaging task involving a malignant lesion and was labelled as a hypothetical experiment (expt) result. The signal was compared to predictions (pred) using benign and malignant lesions. The ΔEISs=EISs|expt - EISs|pred displayed eye catching diffraction structure when the prediction calculation used a benign lesion. The structure occurred even when the phantom compositions were different for prediction and experiment calculations. Since the diffraction structure has a circularly symmetric behaviour because the tissues are amorphous in nature, the 2D ΔEISs patterns were transformed to 1D signals. The 1D signals were obtained by calculating the mean ΔEISs signals in rings. The mean pixel values were a function of the momentum transfer argument q = 4π sin(θ/2)/λ which ranged from 12 to 46 nm-1. The 1D signals correlated well with the 2D profiles. Of particular interest were scatter signatures between q = 20 and 30 nm-1 where malignant tissue is predicted to scatter more than benign fibroglandular tissue. The 1D diffraction signatures could allow a better method to diagnose a suspicious lesion during dual detector scatter VOI CBCT.

Network information improves cancer outcome prediction.

PubMed

Roy, Janine; Winter, Christof; Isik, Zerrin; Schroeder, Michael

2014-07-01

Disease progression in cancer can vary substantially between patients. Yet, patients often receive the same treatment. Recently, there has been much work on predicting disease progression and patient outcome variables from gene expression in order to personalize treatment options. Despite first diagnostic kits in the market, there are open problems such as the choice of random gene signatures or noisy expression data. One approach to deal with these two problems employs protein-protein interaction networks and ranks genes using the random surfer model of Google's PageRank algorithm. In this work, we created a benchmark dataset collection comprising 25 cancer outcome prediction datasets from literature and systematically evaluated the use of networks and a PageRank derivative, NetRank, for signature identification. We show that the NetRank performs significantly better than classical methods such as fold change or t-test. Despite an order of magnitude difference in network size, a regulatory and protein-protein interaction network perform equally well. Experimental evaluation on cancer outcome prediction in all of the 25 underlying datasets suggests that the network-based methodology identifies highly overlapping signatures over all cancer types, in contrast to classical methods that fail to identify highly common gene sets across the same cancer types. Integration of network information into gene expression analysis allows the identification of more reliable and accurate biomarkers and provides a deeper understanding of processes occurring in cancer development and progression. © The Author 2012. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer.

PubMed

Robertson, A Gordon; Kim, Jaegil; Al-Ahmadie, Hikmat; Bellmunt, Joaquim; Guo, Guangwu; Cherniack, Andrew D; Hinoue, Toshinori; Laird, Peter W; Hoadley, Katherine A; Akbani, Rehan; Castro, Mauro A A; Gibb, Ewan A; Kanchi, Rupa S; Gordenin, Dmitry A; Shukla, Sachet A; Sanchez-Vega, Francisco; Hansel, Donna E; Czerniak, Bogdan A; Reuter, Victor E; Su, Xiaoping; de Sa Carvalho, Benilton; Chagas, Vinicius S; Mungall, Karen L; Sadeghi, Sara; Pedamallu, Chandra Sekhar; Lu, Yiling; Klimczak, Leszek J; Zhang, Jiexin; Choo, Caleb; Ojesina, Akinyemi I; Bullman, Susan; Leraas, Kristen M; Lichtenberg, Tara M; Wu, Catherine J; Schultz, Nicholaus; Getz, Gad; Meyerson, Matthew; Mills, Gordon B; McConkey, David J; Weinstein, John N; Kwiatkowski, David J; Lerner, Seth P

2017-10-19

We report a comprehensive analysis of 412 muscle-invasive bladder cancers characterized by multiple TCGA analytical platforms. Fifty-eight genes were significantly mutated, and the overall mutational load was associated with APOBEC-signature mutagenesis. Clustering by mutation signature identified a high-mutation subset with 75% 5-year survival. mRNA expression clustering refined prior clustering analyses and identified a poor-survival "neuronal" subtype in which the majority of tumors lacked small cell or neuroendocrine histology. Clustering by mRNA, long non-coding RNA (lncRNA), and miRNA expression converged to identify subsets with differential epithelial-mesenchymal transition status, carcinoma in situ scores, histologic features, and survival. Our analyses identified 5 expression subtypes that may stratify response to different treatments. Copyright © 2017 Elsevier Inc. All rights reserved.

*K-means and cluster models for cancer signatures.

PubMed

Kakushadze, Zura; Yu, Willie

2017-09-01

We present *K-means clustering algorithm and source code by expanding statistical clustering methods applied in https://ssrn.com/abstract=2802753 to quantitative finance. *K-means is statistically deterministic without specifying initial centers, etc. We apply *K-means to extracting cancer signatures from genome data without using nonnegative matrix factorization (NMF). *K-means' computational cost is a fraction of NMF's. Using 1389 published samples for 14 cancer types, we find that 3 cancers (liver cancer, lung cancer and renal cell carcinoma) stand out and do not have cluster-like structures. Two clusters have especially high within-cluster correlations with 11 other cancers indicating common underlying structures. Our approach opens a novel avenue for studying such structures. *K-means is universal and can be applied in other fields. We discuss some potential applications in quantitative finance.

Focused and Steady-State Characteristics of Shaped Sonic Boom Signatures: Prediction and Analysis

NASA Technical Reports Server (NTRS)

Maglieri, Domenic J.; Bobbitt, Percy J.; Massey, Steven J.; Plotkin, Kenneth J.; Kandil, Osama A.; Zheng, Xudong

2011-01-01

The objective of this study is to examine the effect of flight, at off-design conditions, on the propagated sonic boom pressure signatures of a small "low-boom" supersonic aircraft. The amplification, or focusing, of the low magnitude "shaped" signatures produced by maneuvers such as the accelerations from transonic to supersonic speeds, climbs, turns, pull-up and pushovers is the concern. To analyze these effects, new and/or improved theoretical tools have been developed, in addition to the use of existing methodology. Several shaped signatures are considered in the application of these tools to the study of selected maneuvers and off-design conditions. The results of these applications are reported in this paper as well as the details of the new analytical tools. Finally, the magnitude of the focused boom problem for "low boom" supersonic aircraft designs has been more accurately quantified and potential "mitigations" suggested. In general, "shaped boom" signatures, designed for cruise flight, such as asymmetric and symmetric flat-top and initial-shock ramp waveforms retain their basic shape during transition flight. Complex and asymmetric and symmetric initial shock ramp waveforms provide lower magnitude focus boom levels than N-waves or asymmetric and symmetric flat-top signatures.

Analysis of view synthesis prediction architectures in modern coding standards

NASA Astrophysics Data System (ADS)

Tian, Dong; Zou, Feng; Lee, Chris; Vetro, Anthony; Sun, Huifang

2013-09-01

Depth-based 3D formats are currently being developed as extensions to both AVC and HEVC standards. The availability of depth information facilitates the generation of intermediate views for advanced 3D applications and displays, and also enables more efficient coding of the multiview input data through view synthesis prediction techniques. This paper outlines several approaches that have been explored to realize view synthesis prediction in modern video coding standards such as AVC and HEVC. The benefits and drawbacks of various architectures are analyzed in terms of performance, complexity, and other design considerations. It is hence concluded that block-based VSP prediction for multiview video signals provides attractive coding gains with comparable complexity as traditional motion/disparity compensation.

Genome-Wide Prediction and Validation of Intergenic Enhancers in Arabidopsis Using Open Chromatin Signatures[OPEN

PubMed Central

Zhu, Bo; Zhang, Wenli; Jiang, Jiming

2015-01-01

Enhancers are important regulators of gene expression in eukaryotes. Enhancers function independently of their distance and orientation to the promoters of target genes. Thus, enhancers have been difficult to identify. Only a few enhancers, especially distant intergenic enhancers, have been identified in plants. We developed an enhancer prediction system based exclusively on the DNase I hypersensitive sites (DHSs) in the Arabidopsis thaliana genome. A set of 10,044 DHSs located in intergenic regions, which are away from any gene promoters, were predicted to be putative enhancers. We examined the functions of 14 predicted enhancers using the β-glucuronidase gene reporter. Ten of the 14 (71%) candidates were validated by the reporter assay. We also designed 10 constructs using intergenic sequences that are not associated with DHSs, and none of these constructs showed enhancer activities in reporter assays. In addition, the tissue specificity of the putative enhancers can be precisely predicted based on DNase I hypersensitivity data sets developed from different plant tissues. These results suggest that the open chromatin signature-based enhancer prediction system developed in Arabidopsis may serve as a universal system for enhancer identification in plants. PMID:26373455

Signature neural networks: definition and application to multidimensional sorting problems.

PubMed

Latorre, Roberto; de Borja Rodriguez, Francisco; Varona, Pablo

2011-01-01

In this paper we present a self-organizing neural network paradigm that is able to discriminate information locally using a strategy for information coding and processing inspired in recent findings in living neural systems. The proposed neural network uses: 1) neural signatures to identify each unit in the network; 2) local discrimination of input information during the processing; and 3) a multicoding mechanism for information propagation regarding the who and the what of the information. The local discrimination implies a distinct processing as a function of the neural signature recognition and a local transient memory. In the context of artificial neural networks none of these mechanisms has been analyzed in detail, and our goal is to demonstrate that they can be used to efficiently solve some specific problems. To illustrate the proposed paradigm, we apply it to the problem of multidimensional sorting, which can take advantage of the local information discrimination. In particular, we compare the results of this new approach with traditional methods to solve jigsaw puzzles and we analyze the situations where the new paradigm improves the performance.

Nature's chemical signatures in human olfaction: a foodborne perspective for future biotechnology.

PubMed

Dunkel, Andreas; Steinhaus, Martin; Kotthoff, Matthias; Nowak, Bettina; Krautwurst, Dietmar; Schieberle, Peter; Hofmann, Thomas

2014-07-07

The biocatalytic production of flavor naturals that determine chemosensory percepts of foods and beverages is an ever challenging target for academic and industrial research. Advances in chemical trace analysis and post-genomic progress at the chemistry-biology interface revealed odor qualities of nature's chemosensory entities to be defined by odorant-induced olfactory receptor activity patterns. Beyond traditional views, this review and meta-analysis now shows characteristic ratios of only about 3 to 40 genuine key odorants for each food, from a group of about 230 out of circa 10 000 food volatiles. This suggests the foodborn stimulus space has co-evolved with, and roughly match our circa 400 olfactory receptors as best natural agonists. This perspective gives insight into nature's chemical signatures of smell, provides the chemical odor codes of more than 220 food samples, and beyond addresses industrial implications for producing recombinants that fully reconstruct the natural odor signatures for use in flavors and fragrances, fully immersive interactive virtual environments, or humanoid bioelectronic noses. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Protein Interactome of Muscle Invasive Bladder Cancer

PubMed Central

Bhat, Akshay; Heinzel, Andreas; Mayer, Bernd; Perco, Paul; Mühlberger, Irmgard; Husi, Holger; Merseburger, Axel S.; Zoidakis, Jerome; Vlahou, Antonia; Schanstra, Joost P.; Mischak, Harald; Jankowski, Vera

2015-01-01

Muscle invasive bladder carcinoma is a complex, multifactorial disease caused by disruptions and alterations of several molecular pathways that result in heterogeneous phenotypes and variable disease outcome. Combining this disparate knowledge may offer insights for deciphering relevant molecular processes regarding targeted therapeutic approaches guided by molecular signatures allowing improved phenotype profiling. The aim of the study is to characterize muscle invasive bladder carcinoma on a molecular level by incorporating scientific literature screening and signatures from omics profiling. Public domain omics signatures together with molecular features associated with muscle invasive bladder cancer were derived from literature mining to provide 286 unique protein-coding genes. These were integrated in a protein-interaction network to obtain a molecular functional map of the phenotype. This feature map educated on three novel disease-associated pathways with plausible involvement in bladder cancer, namely Regulation of actin cytoskeleton, Neurotrophin signalling pathway and Endocytosis. Systematic integration approaches allow to study the molecular context of individual features reported as associated with a clinical phenotype and could potentially help to improve the molecular mechanistic description of the disorder. PMID:25569276

Ex-Vessel Core Melt Modeling Comparison between MELTSPREAD-CORQUENCH and MELCOR 2.1

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

Robb, Kevin R.; Farmer, Mitchell; Francis, Matthew W.

System-level code analyses by both United States and international researchers predict major core melting, bottom head failure, and corium-concrete interaction for Fukushima Daiichi Unit 1 (1F1). Although system codes such as MELCOR and MAAP are capable of capturing a wide range of accident phenomena, they currently do not contain detailed models for evaluating some ex-vessel core melt behavior. However, specialized codes containing more detailed modeling are available for melt spreading such as MELTSPREAD as well as long-term molten corium-concrete interaction (MCCI) and debris coolability such as CORQUENCH. In a preceding study, Enhanced Ex-Vessel Analysis for Fukushima Daiichi Unit 1: Meltmore » Spreading and Core-Concrete Interaction Analyses with MELTSPREAD and CORQUENCH, the MELTSPREAD-CORQUENCH codes predicted the 1F1 core melt readily cooled in contrast to predictions by MELCOR. The user community has taken notice and is in the process of updating their systems codes; specifically MAAP and MELCOR, to improve and reduce conservatism in their ex-vessel core melt models. This report investigates why the MELCOR v2.1 code, compared to the MELTSPREAD and CORQUENCH 3.03 codes, yield differing predictions of ex-vessel melt progression. To accomplish this, the differences in the treatment of the ex-vessel melt with respect to melt spreading and long-term coolability are examined. The differences in modeling approaches are summarized, and a comparison of example code predictions is provided.« less

Tiltrotor Aeroacoustic Code (TRAC) Prediction Assessment and Initial Comparisons with Tram Test Data

NASA Technical Reports Server (NTRS)

Burley, Casey L.; Brooks, Thomas F.; Charles, Bruce D.; McCluer, Megan

1999-01-01

A prediction sensitivity assessment to inputs and blade modeling is presented for the TiltRotor Aeroacoustic Code (TRAC). For this study, the non-CFD prediction system option in TRAC is used. Here, the comprehensive rotorcraft code, CAMRAD.Mod1, coupled with the high-resolution sectional loads code HIRES, predicts unsteady blade loads to be used in the noise prediction code WOPWOP. The sensitivity of the predicted blade motions, blade airloads, wake geometry, and acoustics is examined with respect to rotor rpm, blade twist and chord, and to blade dynamic modeling. To accomplish this assessment, an interim input-deck for the TRAM test model and an input-deck for a reference test model are utilized in both rigid and elastic modes. Both of these test models are regarded as near scale models of the V-22 proprotor (tiltrotor). With basic TRAC sensitivities established, initial TRAC predictions are compared to results of an extensive test of an isolated model proprotor. The test was that of the TiltRotor Aeroacoustic Model (TRAM) conducted in the Duits-Nederlandse Windtunnel (DNW). Predictions are compared to measured noise for the proprotor operating over an extensive range of conditions. The variation of predictions demonstrates the great care that must be taken in defining the blade motion. However, even with this variability, the predictions using the different blade modeling successfully capture (bracket) the levels and trends of the noise for conditions ranging from descent to ascent.

Tiltrotor Aeroacoustic Code (TRAC) Prediction Assessment and Initial Comparisons With TRAM Test Data

NASA Technical Reports Server (NTRS)

Burley, Casey L.; Brooks, Thomas F.; Charles, Bruce D.; McCluer, Megan

1999-01-01

A prediction sensitivity assessment to inputs and blade modeling is presented for the TiltRotor Aeroacoustic Code (TRAC). For this study, the non-CFD prediction system option in TRAC is used. Here, the comprehensive rotorcraft code, CAMRAD.Mod 1, coupled with the high-resolution sectional loads code HIRES, predicts unsteady blade loads to be used in the noise prediction code WOPWOP. The sensitivity of the predicted blade motions, blade airloads, wake geometry, and acoustics is examined with respect to rotor rpm, blade twist and chord, and to blade dynamic modeling. To accomplish this assessment. an interim input-deck for the TRAM test model and an input-deck for a reference test model are utilized in both rigid and elastic modes. Both of these test models are regarded as near scale models of the V-22 proprotor (tiltrotor). With basic TRAC sensitivities established, initial TRAC predictions are compared to results of an extensive test of an isolated model proprotor. The test was that of the TiltRotor Aeroacoustic Model (TRAM) conducted in the Duits-Nederlandse Windtunnel (DNW). Predictions are compared to measured noise for the proprotor operating over an extensive range of conditions. The variation of predictions demonstrates the great care that must be taken in defining the blade motion. However, even with this variability, the predictions using the different blade modeling successfully capture (bracket) the levels and trends of the noise for conditions ranging from descent to ascent.

Monitoring Cosmic Radiation Risk: Comparisons between Observations and Predictive Codes for Naval Aviation

DTIC Science & Technology

2009-01-01

proton PARMA PHITS -based Analytical Radiation Model in the Atmosphere PCAIRE Predictive Code for Aircrew Radiation Exposure PHITS Particle and...radiation transport code utilized is called PARMA ( PHITS based Analytical Radiation Model in the Atmosphere) [36]. The particle fluxes calculated from the...same dose equivalent coefficient regulations from the ICRP-60 regulations. As a result, the transport codes utilized by EXPACS ( PHITS ) and CARI-6

Monitoring Cosmic Radiation Risk: Comparisons Between Observations and Predictive Codes for Naval Aviation

DTIC Science & Technology

2009-07-05

proton PARMA PHITS -based Analytical Radiation Model in the Atmosphere PCAIRE Predictive Code for Aircrew Radiation Exposure PHITS Particle and Heavy...transport code utilized is called PARMA ( PHITS based Analytical Radiation Model in the Atmosphere) [36]. The particle fluxes calculated from the input...dose equivalent coefficient regulations from the ICRP-60 regulations. As a result, the transport codes utilized by EXPACS ( PHITS ) and CARI-6 (PARMA

Receiver Operating Characteristic curves of the seismo-ionospheric precursors in GIM TEC associated with magnitude greater than 6.0 earthquakes in China during 1998-2013.

NASA Astrophysics Data System (ADS)

Huang, C. H.; Chen, Y. I.; Liu, J. Y. G.; Huang, Y. H.

2014-12-01

Statistical evidence of the Seismo-Ionospheric Precursors (SIPs) is reported by statistically investigating the relationship between the Total Electron Content (TEC) in Global Ionosphere Map (GIM) and 56 M≥6.0 earthquakes during 1998-2013 in China. A median-based method and a z test are employed to detect the overall earthquake signatures. It is found that a reduction of positive signatures and an enhancement of negative signatures appear simultaneously on 3-5 days prior to the earthquakes in China. Finally, receiver operating characteristic (ROC) curves are used to measure the power of TEC for predicting M≥6.0 earthquakes in China.

Numerical predictions of EML (electromagnetic launcher) system performance

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

Schnurr, N.M.; Kerrisk, J.F.; Davidson, R.F.

1987-01-01

The performance of an electromagnetic launcher (EML) depends on a large number of parameters, including the characteristics of the power supply, rail geometry, rail and insulator material properties, injection velocity, and projectile mass. EML system performance is frequently limited by structural or thermal effects in the launcher (railgun). A series of computer codes has been developed at the Los Alamos National Laboratory to predict EML system performance and to determine the structural and thermal constraints on barrel design. These codes include FLD, a two-dimensional electrostatic code used to calculate the high-frequency inductance gradient and surface current density distribution for themore » rails; TOPAZRG, a two-dimensional finite-element code that simultaneously analyzes thermal and electromagnetic diffusion in the rails; and LARGE, a code that predicts the performance of the entire EML system. Trhe NIKE2D code, developed at the Lawrence Livermore National Laboratory, is used to perform structural analyses of the rails. These codes have been instrumental in the design of the Lethality Test System (LTS) at Los Alamos, which has an ultimate goal of accelerating a 30-g projectile to a velocity of 15 km/s. The capabilities of the individual codes and the coupling of these codes to perform a comprehensive analysis is discussed in relation to the LTS design. Numerical predictions are compared with experimental data and presented for the LTS prototype tests.« less

Bayesian decision support for coding occupational injury data.

PubMed

Nanda, Gaurav; Grattan, Kathleen M; Chu, MyDzung T; Davis, Letitia K; Lehto, Mark R

2016-06-01

Studies on autocoding injury data have found that machine learning algorithms perform well for categories that occur frequently but often struggle with rare categories. Therefore, manual coding, although resource-intensive, cannot be eliminated. We propose a Bayesian decision support system to autocode a large portion of the data, filter cases for manual review, and assist human coders by presenting them top k prediction choices and a confusion matrix of predictions from Bayesian models. We studied the prediction performance of Single-Word (SW) and Two-Word-Sequence (TW) Naïve Bayes models on a sample of data from the 2011 Survey of Occupational Injury and Illness (SOII). We used the agreement in prediction results of SW and TW models, and various prediction strength thresholds for autocoding and filtering cases for manual review. We also studied the sensitivity of the top k predictions of the SW model, TW model, and SW-TW combination, and then compared the accuracy of the manually assigned codes to SOII data with that of the proposed system. The accuracy of the proposed system, assuming well-trained coders reviewing a subset of only 26% of cases flagged for review, was estimated to be comparable (86.5%) to the accuracy of the original coding of the data set (range: 73%-86.8%). Overall, the TW model had higher sensitivity than the SW model, and the accuracy of the prediction results increased when the two models agreed, and for higher prediction strength thresholds. The sensitivity of the top five predictions was 93%. The proposed system seems promising for coding injury data as it offers comparable accuracy and less manual coding. Accurate and timely coded occupational injury data is useful for surveillance as well as prevention activities that aim to make workplaces safer. Copyright © 2016 Elsevier Ltd and National Safety Council. All rights reserved.

An integrated mRNA and microRNA expression signature for glioblastoma multiforme prognosis.

PubMed

Xiong, Jie; Bing, Zhitong; Su, Yanlin; Deng, Defeng; Peng, Xiaoning

2014-01-01

Although patients with Glioblastoma multiforme (GBM) have grave prognosis, significant variability in patient outcome is observed. The objective of this study is to identify a molecular signature for GBM prognosis. We subjected 355 mRNA and microRNA expression profiles to elastic net-regulated Cox regression for identification of an integrated RNA signature for GBM prognosis. A prognostic index (PI) was generated for patient stratification. Survival comparison was conducted by Kaplan-Meier method and a general multivariate Cox regression procedure was applied to evaluate the independence of the PI. The abilities and efficiencies of signatures to predict GBM patient outcome was assessed and compared by the area under the curve (AUC) of the receiver-operator characteristic (ROC). An integrated RNA prognostic signature consisted by 4 protective mRNAs, 12 risky mRNAs, and 1 risky microRNA was identified. Decreased survival was associated with being in the high-risk group (hazard ratio = 2.864, P<0.0001). The prognostic value of the integrated signature was validated in five independent GBM expression datasets (n = 201, hazard ratio = 2.453, P<0.0001). The PI outperformed the known clinical factors, mRNA-only, and miRNA-only prognostic signatures for GBM prognosis (area under the ROC curve for the integrated RNA, mRNA-only, and miRNA-only signatures were 0.828, 0.742, and 0.757 at 3 years of overall survival, respectively, P<0.0001 by permutation test). We describe the first, to our knowledge, robust transcriptome-based integrated RNA signature that improves the current GBM prognosis based on clinical variables, mRNA-only, and miRNA-only signatures.

An Integrated mRNA and microRNA Expression Signature for Glioblastoma Multiforme Prognosis

PubMed Central

Xiong, Jie; Bing, Zhitong; Su, Yanlin; Deng, Defeng; Peng, Xiaoning

2014-01-01

Although patients with Glioblastoma multiforme (GBM) have grave prognosis, significant variability in patient outcome is observed. The objective of this study is to identify a molecular signature for GBM prognosis. We subjected 355 mRNA and microRNA expression profiles to elastic net-regulated Cox regression for identification of an integrated RNA signature for GBM prognosis. A prognostic index (PI) was generated for patient stratification. Survival comparison was conducted by Kaplan-Meier method and a general multivariate Cox regression procedure was applied to evaluate the independence of the PI. The abilities and efficiencies of signatures to predict GBM patient outcome was assessed and compared by the area under the curve (AUC) of the receiver-operator characteristic (ROC). An integrated RNA prognostic signature consisted by 4 protective mRNAs, 12 risky mRNAs, and 1 risky microRNA was identified. Decreased survival was associated with being in the high-risk group (hazard ratio = 2.864, P<0.0001). The prognostic value of the integrated signature was validated in five independent GBM expression datasets (n = 201, hazard ratio = 2.453, P<0.0001). The PI outperformed the known clinical factors, mRNA-only, and miRNA-only prognostic signatures for GBM prognosis (area under the ROC curve for the integrated RNA, mRNA-only, and miRNA-only signatures were 0.828, 0.742, and 0.757 at 3 years of overall survival, respectively, P<0.0001 by permutation test). We describe the first, to our knowledge, robust transcriptome-based integrated RNA signature that improves the current GBM prognosis based on clinical variables, mRNA-only, and miRNA-only signatures. PMID:24871302

Gene expression of Caenorhabditis elegans neurons carries information on their synaptic connectivity.

PubMed

Kaufman, Alon; Dror, Gideon; Meilijson, Isaac; Ruppin, Eytan

2006-12-08

The claim that genetic properties of neurons significantly influence their synaptic network structure is a common notion in neuroscience. The nematode Caenorhabditis elegans provides an exciting opportunity to approach this question in a large-scale quantitative manner. Its synaptic connectivity network has been identified, and, combined with cellular studies, we currently have characteristic connectivity and gene expression signatures for most of its neurons. By using two complementary analysis assays we show that the expression signature of a neuron carries significant information about its synaptic connectivity signature, and identify a list of putative genes predicting neural connectivity. The current study rigorously quantifies the relation between gene expression and synaptic connectivity signatures in the C. elegans nervous system and identifies subsets of neurons where this relation is highly marked. The results presented and the genes identified provide a promising starting point for further, more detailed computational and experimental investigations.

Solar cycle signatures in the NCEP equatorial annual oscillation

NASA Astrophysics Data System (ADS)

Mayr, H. G.; Mengel, J. G.; Huang, F. T.; Nash, E. R.

2009-08-01

Our analysis of temperature and zonal wind data (1958 to 2006) from the National Center for Atmospheric Research (NCAR) reanalysis (Re-1), supplied by the National Centers for Environmental Prediction (NCEP), shows that the hemispherically symmetric 12-month equatorial annual oscillation (EAO) contains spectral signatures with periods around 11 years. Moving windows of 44 years show that, below 20 km, the 11-year modulation of the EAO is phase locked to the solar cycle (SC). The spectral features from the 48-year data record reveal modulation signatures of 9.6 and 12 years, which produce EAO variations that mimic in limited altitude regimes the varying maxima and minima of the 10.7 cm flux solar index. Above 20 km, the spectra also contain modulation signatures with periods around 11 years, but the filtered variations are too irregular to suggest that systematic SC forcing is the principal agent.

Weighted bi-prediction for light field image coding

NASA Astrophysics Data System (ADS)

Conti, Caroline; Nunes, Paulo; Ducla Soares, Luís.

2017-09-01

Light field imaging based on a single-tier camera equipped with a microlens array - also known as integral, holoscopic, and plenoptic imaging - has currently risen up as a practical and prospective approach for future visual applications and services. However, successfully deploying actual light field imaging applications and services will require developing adequate coding solutions to efficiently handle the massive amount of data involved in these systems. In this context, self-similarity compensated prediction is a non-local spatial prediction scheme based on block matching that has been shown to achieve high efficiency for light field image coding based on the High Efficiency Video Coding (HEVC) standard. As previously shown by the authors, this is possible by simply averaging two predictor blocks that are jointly estimated from a causal search window in the current frame itself, referred to as self-similarity bi-prediction. However, theoretical analyses for motion compensated bi-prediction have suggested that it is still possible to achieve further rate-distortion performance improvements by adaptively estimating the weighting coefficients of the two predictor blocks. Therefore, this paper presents a comprehensive study of the rate-distortion performance for HEVC-based light field image coding when using different sets of weighting coefficients for self-similarity bi-prediction. Experimental results demonstrate that it is possible to extend the previous theoretical conclusions to light field image coding and show that the proposed adaptive weighting coefficient selection leads to up to 5 % of bit savings compared to the previous self-similarity bi-prediction scheme.

The Feedback-related Negativity Codes Components of Abstract Inference during Reward-based Decision-making.

PubMed

Reiter, Andrea M F; Koch, Stefan P; Schröger, Erich; Hinrichs, Hermann; Heinze, Hans-Jochen; Deserno, Lorenz; Schlagenhauf, Florian

2016-08-01

Behavioral control is influenced not only by learning from the choices made and the rewards obtained but also by "what might have happened," that is, inference about unchosen options and their fictive outcomes. Substantial progress has been made in understanding the neural signatures of direct learning from choices that are actually made and their associated rewards via reward prediction errors (RPEs). However, electrophysiological correlates of abstract inference in decision-making are less clear. One seminal theory suggests that the so-called feedback-related negativity (FRN), an ERP peaking 200-300 msec after a feedback stimulus at frontocentral sites of the scalp, codes RPEs. Hitherto, the FRN has been predominantly related to a so-called "model-free" RPE: The difference between the observed outcome and what had been expected. Here, by means of computational modeling of choice behavior, we show that individuals employ abstract, "double-update" inference on the task structure by concurrently tracking values of chosen stimuli (associated with observed outcomes) and unchosen stimuli (linked to fictive outcomes). In a parametric analysis, model-free RPEs as well as their modification because of abstract inference were regressed against single-trial FRN amplitudes. We demonstrate that components related to abstract inference uniquely explain variance in the FRN beyond model-free RPEs. These findings advance our understanding of the FRN and its role in behavioral adaptation. This might further the investigation of disturbed abstract inference, as proposed, for example, for psychiatric disorders, and its underlying neural correlates.

A data-driven, knowledge-based approach to biomarker discovery: application to circulating microRNA markers of colorectal cancer prognosis.

PubMed

Vafaee, Fatemeh; Diakos, Connie; Kirschner, Michaela B; Reid, Glen; Michael, Michael Z; Horvath, Lisa G; Alinejad-Rokny, Hamid; Cheng, Zhangkai Jason; Kuncic, Zdenka; Clarke, Stephen

2018-01-01

Recent advances in high-throughput technologies have provided an unprecedented opportunity to identify molecular markers of disease processes. This plethora of complex-omics data has simultaneously complicated the problem of extracting meaningful molecular signatures and opened up new opportunities for more sophisticated integrative and holistic approaches. In this era, effective integration of data-driven and knowledge-based approaches for biomarker identification has been recognised as key to improving the identification of high-performance biomarkers, and necessary for translational applications. Here, we have evaluated the role of circulating microRNA as a means of predicting the prognosis of patients with colorectal cancer, which is the second leading cause of cancer-related death worldwide. We have developed a multi-objective optimisation method that effectively integrates a data-driven approach with the knowledge obtained from the microRNA-mediated regulatory network to identify robust plasma microRNA signatures which are reliable in terms of predictive power as well as functional relevance. The proposed multi-objective framework has the capacity to adjust for conflicting biomarker objectives and to incorporate heterogeneous information facilitating systems approaches to biomarker discovery. We have found a prognostic signature of colorectal cancer comprising 11 circulating microRNAs. The identified signature predicts the patients' survival outcome and targets pathways underlying colorectal cancer progression. The altered expression of the identified microRNAs was confirmed in an independent public data set of plasma samples of patients in early stage vs advanced colorectal cancer. Furthermore, the generality of the proposed method was demonstrated across three publicly available miRNA data sets associated with biomarker studies in other diseases.

In the loop: promoter–enhancer interactions and bioinformatics

PubMed Central

Mora, Antonio; Sandve, Geir Kjetil; Gabrielsen, Odd Stokke

2016-01-01

Enhancer–promoter regulation is a fundamental mechanism underlying differential transcriptional regulation. Spatial chromatin organization brings remote enhancers in contact with target promoters in cis to regulate gene expression. There is considerable evidence for promoter–enhancer interactions (PEIs). In the recent years, genome-wide analyses have identified signatures and mapped novel enhancers; however, being able to precisely identify their target gene(s) requires massive biological and bioinformatics efforts. In this review, we give a short overview of the chromatin landscape and transcriptional regulation. We discuss some key concepts and problems related to chromatin interaction detection technologies, and emerging knowledge from genome-wide chromatin interaction data sets. Then, we critically review different types of bioinformatics analysis methods and tools related to representation and visualization of PEI data, raw data processing and PEI prediction. Lastly, we provide specific examples of how PEIs have been used to elucidate a functional role of non-coding single-nucleotide polymorphisms. The topic is at the forefront of epigenetic research, and by highlighting some future bioinformatics challenges in the field, this review provides a comprehensive background for future PEI studies. PMID:26586731