Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Expression systems”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Fecal microbiota transplant rescues mice from human pathogen mediated sepsis by restoring systemic immunity

Death due to sepsis remains a persistent threat to critically ill patients confined to the intensive care unit and is characterized by colonization with multi-drug-resistant healthcare-associated pathogens. Here we report that sepsis in mice caused by a defined four-member pathogen community isolated from a patient with lethal sepsis is associated with the systemic suppression of key elements of the host transcriptome required for pathogen clearance and decreased butyrate expression. More specifically, these pathogens directly suppress interferon regulatory factor 3. Fecal microbiota transplant (FMT) reverses the course of otherwise lethal sepsis by enhancing pathogen clearance via the restoration of host immunity in an interferon regulatory factor 3-dependent manner. This protective effect is linked to the expansion of butyrate-producing Bacteroidetes. Taken together these results suggest that fecal microbiota transplantation may be a treatment option in sepsis associated with immunosuppression.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Ubiquitin-like conjugation by bacterial cGAS enhances anti-phage defence

Abstract cGAS is an evolutionarily conserved enzyme that has a pivotal role in immune defence against infection 1–3 . In vertebrate animals, cGAS is activated by DNA to produce cyclic GMP–AMP (cGAMP) 4,5 , which leads to the expression of antimicrobial genes 6,7 . In bacteria, cyclic dinucleotide (CDN)-based anti-phage signalling systems (CBASS) have been discovered 8–11 . These systems are composed of cGAS-like enzymes and various effector proteins that kill bacteria on phage infection, thereby stopping phage spread. Of the CBASS systems reported, approximately 39% contain Cap2 and Cap3 , which encode proteins with homology to ubiquitin conjugating (E1/E2) and deconjugating enzymes, respectively 8,12 . Although these proteins are required to prevent infection of some bacteriophages 8 , the mechanism by which the enzymatic activities exert an anti-phage effect is unknown. Here we show that Cap2 forms a thioester bond with the C-terminal glycine of cGAS and promotes conjugation of cGAS to target proteins in a process that resembles ubiquitin conjugation. The covalent conjugation of cGAS increases the production of cGAMP. Using a genetic screen, we found that the phage protein Vs.4 antagonized cGAS signalling by binding tightly to cGAMP (dissociation constant of approximately 30 nM) and sequestering it. A crystal structure of Vs.4 bound to cGAMP showed that Vs.4 formed a hexamer that was bound to three molecules of cGAMP. These results reveal a ubiquitin-like conjugation mechanism that regulates cGAS activity in bacteria and illustrates an arms race between bacteria and viruses through controlling CDN levels.

Science & Technology - Other Topics↗
DOE OSTI2021

Description of longitudinal space charge effects in beams and plasma through dielectric permittivity

We develop a universal framework which allows quickly solve a wide class of problems for longitudinal space charge effects in beams and plasmas in cylindrical geometry. We introduce the longitudinal dielectric permittivity for the beam of charged particles, which describes its collective space charge response. The analysis yields an effective plasma frequency, which depends on the transverse geometry of the system. This dielectric permittivity mirrors the dielectric permittivity of plasma and matches the one dimensional (1D) expression once the transverse size of the beam is large. Several particle species can be included as additive terms describing susceptibility of each specie. The developed approach allows to study stability criteria for collective beam-beam and beam-plasma instabilities for arbitrary transverse distributions in particle densities.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Prediction of condition-specific regulatory genes using machine learning

Recent advances in genomic technologies have generated data on large-scale protein–DNA interactions and open chromatin regions for many eukaryotic species. How to identify condition-specific functions of transcription factors using these data has become a major challenge in genomic research. To solve this problem, we have developed a method called ConSReg, which provides a novel approach to integrate regulatory genomic data into predictive machine learning models of key regulatory genes. Using Arabidopsis as a model system, we tested our approach to identify regulatory genes in data sets from single cell gene expression and from abiotic stress treatments. Our results showed that ConSReg accurately predicted transcription factors that regulate differentially expressed genes with an average auROC of 0.84, which is 23.5–25% better than enrichment-based approaches. To further validate the performance of ConSReg, we analyzed an independent data set related to plant nitrogen responses. ConSReg provided better rankings of the correct transcription factors in 61.7% of cases, which is three times better than other plant tools. We applied ConSReg to Arabidopsis single cell RNA-seq data, successfully identifying candidate regulatory genes that control cell wall formation. Our methods provide a new approach to define candidate regulatory genes using integrated genomic data in plants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Signature analysis of high-throughput transcriptomics screening data for mechanistic inference and chemical grouping

Abstract High-throughput transcriptomics (HTTr) uses gene expression profiling to characterize the biological activity of chemicals in in vitro cell-based test systems. As an extension of a previous study testing 44 chemicals, HTTr was used to screen an additional 1,751 unique chemicals from the EPA’s ToxCast collection in MCF7 cells using 8 concentrations and an exposure duration of 6 h. We hypothesized that concentration-response modeling of signature scores could be used to identify putative molecular targets and cluster chemicals with similar bioactivity. Clustering and enrichment analyses were conducted based on signature catalog annotations and ToxPrint chemotypes to facilitate molecular target prediction and grouping of chemicals with similar bioactivity profiles. Enrichment analysis based on signature catalog annotation identified known mechanisms of action (MeOAs) associated with well-studied chemicals and generated putative MeOAs for other active chemicals. Chemicals with predicted MeOAs included those targeting estrogen receptor (ER), glucocorticoid receptor (GR), retinoic acid receptor (RAR), the NRF2/KEAP/ARE pathway, AP-1 activation, and others. Using reference chemicals for ER modulation, the study demonstrated that HTTr in MCF7 cells was able to stratify chemicals in terms of agonist potency, distinguish ER agonists from antagonists, and cluster chemicals with similar activities as predicted by the ToxCast ER Pathway model. Uniform manifold approximation and projection (UMAP) embedding of signature-level results identified novel ER modulators with no ToxCast ER Pathway model predictions. Finally, UMAP combined with ToxPrint chemotype enrichment was used to explore the biological activity of structurally related chemicals. The study demonstrates that HTTr can be used to inform chemical risk assessment by determining in vitro points of departure, predicting chemicals’ MeOA and grouping chemicals with similar bioactivity profiles.

Toxicology↗
DOE OSTI2020

OsWRKY21 and OsWRKY108 function redundantly to promote phosphate accumulation through maintaining the constitutive expression of OsPHT1;1 under phosphate‐replete conditions

Summary Plant Phosphate Transporter 1 (PHT1) proteins, probably the only influx transporters for phosphate (Pi) uptake, are partially degraded on sufficient Pi levels to prevent excessive Pi accumulation. Therefore, the basal/constitutive expression level of PHT1 genes is vital for maintaining Pi uptake under Pi‐replete conditions. Rice ( Oryza sativa ) OsPHT1;1 is a unique gene as it is highly expressed and not responsive to Pi, however the mechanism for maintaining its basal/constitutive expression remains unknown. Using biochemical and genetic approaches, we identified and functionally characterised the transcription factors maintaining the basal/constitutive expression of OsPHT1;1 . OsWRKY21 and OsWRKY108 interact within the nucleus and both bind to the W‐box in the OsPHT1;1 promoter. Overexpression of OsWRKY21 or OsWRKY108 led to increased Pi accumulation, resulting from elevated expression of OsPHT1;1 . By contrast, oswrky21 oswrky108 double mutants showed decreased Pi accumulation and OsPHT1;1 expression in a Pi‐dependent manner. Moreover, similar to ospht1;1 mutants, plants expressing the OsWRKY21–SRDX fusion protein (a chimeric dominant suppressor) were impaired in Pi accumulation in Pi‐replete roots, accompanied by downregulation of OsPHT1;1 expression. Our findings demonstrated that rice WRKY transcription factors function redundantly to promote Pi uptake by activating OsPHT1;1 expression under Pi‐replete conditions, and represent a novel pathway independent of the central Pi signalling system.

Zhang, Jun↗
DOE OSTI2020

On Transfer Learning Of Neural Networks Using Bi-Fidelity Data For Uncertainty Propagation

Due to their high degree of expressiveness, neural networks have recently been used as surrogate models for mapping inputs of an engineering system to outputs of interest. Once trained, neural networks are computationally inexpensive to evaluate and remove the need for repeated evaluations of computationally expensive models in uncertainty quantification applications. However, given the highly parameterized construction of neural networks, especially deep neural networks, accurate training often requires large amounts of simulation data that may not be available in the case of computationally expensive systems. In this paper, to alleviate this issue for uncertainty propagation, we explore the application of transfer learning techniques using training data generated from both high- and low-fidelity models. We explore two strategies for coupling these two datasets during the training procedure, namely, the standard transfer learning and the bi-fidelity-weighted learning. In the former approach, a neural network model mapping the inputs to the outputs of interest is trained based on the low-fidelity data. The high-fidelity data are then used to adapt the parameters of the upper layer(s) of the low-fidelity network, or train a simpler neural network to map the output of the low-fidelity network to that of the high-fidelity model. In the latter approach, the entire low-fidelity network parameters are updated using data generated via a Gaussian process model trained with a small high-fidelity dataset. The parameter updates are performed via a variant of stochastic gradient descent with learning rates given by the Gaussian process model. Using three numerical examples, we illustrate the utility of these bi-fidelity transfer learning methods where we focus on accuracy improvement achieved by transfer learning over standard training approaches.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Using Machine Learning for Quantum Annealing Accuracy Prediction

Quantum annealers, such as the device built by D-Wave Systems, Inc., offer a way to compute solutions of NP-hard problems that can be expressed in Ising or quadratic unconstrained binary optimization (QUBO) form. Although such solutions are typically of very high quality, problem instances are usually not solved to optimality due to imperfections of the current generations quantum annealers. In this contribution, we aim to understand some of the factors contributing to the hardness of a problem instance, and to use machine learning models to predict the accuracy of the D-Wave 2000Q annealer for solving specific problems. We focus on the maximum clique problem, a classic NP-hard problem with important applications in network analysis, bioinformatics, and computational chemistry. By training a machine learning classification model on basic problem characteristics such as the number of edges in the graph, or annealing parameters, such as the D-Wave’s chain strength, we are able to rank certain features in the order of their contribution to the solution hardness, and present a simple decision tree which allows to predict whether a problem will be solvable to optimality with the D-Wave 2000Q. We extend these results by training a machine learning regression model that predicts the clique size found by D-Wave.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1975

Information services and information processing

Attempts made to design and extend space system capabilities are reported. Special attention was given to establishing user needs for information or services which might be provided by space systems. Data given do not attempt to detail scientific, technical, or economic bases for the needs expressed by the users.

Source record↗
NASA NTRS1979

Notes on the meteorology of the intertropical convergence zone during the July 1977 experiment

The stratosphere and troposphere are large-scale open systems which exchange mass and trace constituents. If averaged over all longitudes, mass exchange can be expressed as products of the means and the mean of the product of the deviations from the mean. At high latitudes, the mass exchange is dominated by the deviations from the mean. At low latitudes, in the tropics, it is generally assumed that the mass exchange is caused by the mean motion. Figures are presented which depict: Northern Hemisphere mean motion; Convergence Zone motion; clouds and their motions; surface pressure variations; and meteorological parameters such as temperature, relative humidity, and ozone mixing ratios.

Danielson, E. F.↗
NASA NTRS1979

Radiation forces on small particles in the solar system

Solar radiation forces on small particles in the solar system are examined, and the resulting orbital evolution of interplanetary and circumplanetary dust is considered. An expression is derived for the effects of radiation pressure and Poynting-Robertson drag on small, spherical particles using the energy and momentum transformation laws of special relativity, and numerical examples are presented to illustrate that radiation pressure and Poynting-Robertson drag are only important for particles within a narrow size range. The orbital consequences of these radiation forces are considered both for heliocentric and planetocentric orbiting particles, and the coupling between particle sizes and dynamics is discussed. A qualitative derivation is presented for the differential Doppler effect, which is due to the differential Doppler shifting of radiation from approaching and receding solar hemispheres, and the Yarkovsky effect, which is important for rotating meter-to kilometer-sized particles, is briefly described.

Burns, J. A.↗
NASA NTRS1981

Charged particle concepts for fog dispersion

Charged particle techniques hold promise for dispersing warm fog in the terminal area of commercial airports. This report focuses on features of the charged particle technique which require further study. The basic physical principles of the technique and the major verification experiments carried out in the past are described. The fundamentals of the nozzle operation are given. The nozzle characteristics and the theory of particle charging in the nozzle are discussed, including information from extensive literature on electrostatic precipitation relative to environmental pollution control and a description of some preliminary reported analyses on the jet characteristics and interaction with neighboring jets. The equation governing the transfer of water substances and of electrical charge is given together with a brief description of several semi-empirical, mathematical expressions necessary for the governing equations. The necessary ingredients of a field experiment to verify the system once a prototype is built are described.

Frost, W.↗
NASA NTRS1981

Development of an unsteady aerodynamic analysis for finite-deflection subsonic cascades

An unsteady potential flow analysis, which accounts for the effects of blade geometry and steady turning, was developed to predict aerodynamic forces and moments associated with free vibration or flutter phenomena in the fan, compressor, or turbine stages of modern jet engines. Based on the assumption of small amplitude blade motions, the unsteady flow is governed by linear equations with variable coefficients which depend on the underlying steady low. These equations were approximated using difference expressions determined from an implicit least squares development and applicable on arbitrary grids. The resulting linear system of algebraic equations is block tridiagonal, which permits an efficient, direct (i.e., noniterative) solution. The solution procedure was extended to treat blades with rounded or blunt edges at incidence relative to the inlet flow.

Verdon, J. M.↗
NASA NTRS1981

Measurement of very large flow angles with non-nulling seven-hole probes

This paper describes a method for measuring local direction and total and static pressures of a flow by means of a fixed probe, provided that the local air flow does not make an angle of more than 80 degrees with the axis of the probe. The probe is easily manufactured from standard-sized tubing materials. The power series calibration method used with the probe results in explicit polynomial expressions for the desired aerodynamic properties. The calibration method is easily programmed on a data acquisition system. This paper includes an example of a complete incompressible calibration.

Gallington, R. W.↗
NASA NTRS1984

Thermal barrier coating life prediction model development

The objective of this program is to develop an integrated life prediction model accounting for all potential life-limiting Thermal Barrier Coating (TBC) degradation and failure modes including spallation resulting from cyclic thermal stress, oxidative degradation, hot corrosion, erosion, and foreign object damage (FOD). The mechanisms and relative importance of the various degradation and failure modes will be determined, and the methodology to predict predominant mode failure life in turbine airfoil application will be developed and verified. An empirically based correlative model relating coating life to parametrically expressed driving forces such as temperature and stress will be employed. The two-layer TBC system being investigated, designated PWA264, currently is in commercial aircraft revenue service. It consists of an inner low pressure chamber plasma-sprayed NiCoCrAlY metallic bond coat underlayer (4 to 6 mils) and an outer air plasma-sprayed 7 w/o Y2O3-ZrO2 (8 to 12 mils) ceramic top layer.

Demasi, J.↗
NASA NTRS1986

Small particle melting of pure metals

Submicron-sized crystallites of lead, tin, indium and bismuth were melted in situ in the modified specimen chamber of a Siemens transmission e lectron microscope. Melting point and size determinations were made directly from the dark field images of the crystallites. Particles exhibited melting points that decreased with decreasing particle size. A near-linear relationship was observed for the melting point as a function of the reciprocal of the radius. Thermodynamnic expressions based on the significant contributions of the surface energy to the free energy of the system also suggest a linear relation. Other factors, such as shape and surface contamination, were also observed to affect the size-dependent melting of particles. Crystallites of extended platelet shape did not exhibit a significant depression in melting point. Elevated residual gas pressures were found to lessen the melting point depression of spherical particles.

Allen, G. L.↗
NASA NTRS1988

Densities of Pb-Sn alloys during solidification

Data for the densities and expansion coefficients of solid and liquid alloys of the Pb-Sn system are consolidated in this paper. More importantly, the data are analyzed with the purpose of expressing either the density of the solid or of the liquid as a function of its composition and temperature. In particular, the densities of the solid and of the liquid during dendritic solidification are derived. Finally, the solutal and thermal coefficients of volume expansion for the liquid are given as functions of temperature and composition.

Poirier, D. R.↗
NASA NTRS1988

IMF control of geomagnetic activity

Recent work on the IMF control of geomagnetic activity is reviewed. The goal is to quantitatively express the temporal relation between the solar wind input and the ionospheric output from the magnetospheric system. Linear prediction filtering was used which treats the magnetosphere as a black box characterized by an impulse response. It is shown that an average impulse response can account for only about 40 percent of the variance in the AL index.

Mcpherron, R. L.↗