Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “variable selection”

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 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

time-resolved spectroscopy fit (trspecfit) v0.01

Analyze 2D time- and energy-resolved data, such as from a pump-probe spectroscopy experiment. User can select and input different peak shapes/ functions and background types to first fit a ground state/ unperturbed spectrum. This would be similar to how standard spectroscopy data is fit. Subsequently, to describe the time domain, users can choose functions that describe the temporal dynamics of one or more spectral features, such as a peak amplitude, peak position, etc. These time dynamics functions can be added or convoluted (e.g. describing an instrument response function) with each other. Functionality to integrate implicit variables leading to distributions of certain parameters/ functions is in development. Alternatively, 2D data can be analyzed one time step at a time to get an idea of the time dynamics of the system before deploying the global 2D fit described above. Typically people write custom software for this purpose. During my PhD I've seen five internal LBL and external researchers write one-off code in different languages to analyze time- and energy-resolved spectra. While this was specifically was for a laser pump - X-ray probe spectroscopy experiment, I'm trying to write a general package for the time-resolved spectroscopy community.

Mahl, Johannes [Lawrence Berkeley National Laborat↗
DOE OSTI2023

Group Projected subspace pursuit for IDENTification of variable coefficient differential equations (GP-IDENT)

We propose an effective and robust algorithm for identifying partial differential equations (PDEs) with space-time varying coefficients from the noisy observation of a single solution trajectory. Identifying unknown differential equations from noisy data is a difficult task, and it is even more challenging with space and time varying coefficients in the PDE. The proposed algorithm, GP-IDENT, has three ingredients: (i) we use B-spline bases to express the unknown space and time varying coefficients, (ii) we propose Group Projected Subspace Pursuit (GPSP) to find a sequence of candidate PDEs with various levels of complexity, and (iii) we propose a new criterion for model selection using the Reduction in Residual (RR) to choose an optimal one among a pool of candidates. The new GPSP considers group projected subspaces which is more robust than existing methods in distinguishing correlated group features. We test GP-IDENT on a variety of PDEs and PDE systems, and compare it with the state-of-the-art parametric PDE identification algorithms under different settings to illustrate its outstanding performance. Furthermore, our experiments show that GP-IDENT is effective in identifying the correct terms from a large dictionary, and our model selection scheme is robust to noise.

Data-driven method↗
DOE OSTI2015

SU-E-J-21: Setup Variability of Colorectal Cancer Patients Treated in the Prone Position and Dosimetric Comparison with the Supine Position

Purpose: Many cancer centers treat colorectal patients in the prone position on a belly board to minimize dose to the small bowel. That may potentially Result in patient setup instability with corresponding impact on dose delivery accuracy for highly conformal techniques such as IMRT/VMAT. Two aims of this work are 1) to investigate setup accuracy of rectum patients treated in the prone position on a belly board using CBCT and 2) to evaluate dosimetric impact on bladder and small bowel of treating rectum patients in supine vs. prone position. Methods: For the setup accuracy study, 10 patients were selected. Weekly CBCTs were acquired and matched to bone. The CBCT-determined shifts were recorded. For the dosimetric study, 7 prone-setup patients and 7 supine-setup patients were randomly selected from our clinical database. Various clinically relevant dose volume histogram values were recorded for the small bowel and bladder. Results: The CBCT-determined rotational shifts had a wide variation. For the dataset acquired at the time of this writing, the ranges of rotational setup errors for pitch, roll, and yaw were [−3.6° 4.7°], [−4.3° 3.2°], and [−1.4° 1.4°]. For the dosimetric study: the small bowel V(45Gy) and mean dose for the prone position was 5.6±12.1% and 18.4±6.2Gy (ranges indicate standard deviations); for the supine position the corresponding dose values were 12.9±15.8% and 24.7±8.8Gy. For the bladder, the V(30Gy) and mean dose for prone position were 68.7±12.7% and 38.4±3.3Gy; for supine position these dose values were 77.1±13.7% and 40.7±3.1Gy. Conclusion: There is evidence of significant rotational instability in the prone position. The OAR dosimetry study indicates that there are some patients that may still benefit from the prone position, though many patients can be safely treated supine.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Polarization and variability of compact sources measured in Planck time-ordered data

This paper introduces a new Planck Catalog of Polarized and Variable Compact Sources (PCCS-PV) comprising 153 sources, the majority of which are extragalactic. The data include both the total flux density and linear polarization measured by Planck with frequency coverage from 30 to 353 GHz, and temporal spacing ranging from days to years. We classify most sources as beamed, extragalactic radio sources; the catalog also includes several radio galaxies, Seyfert galaxies, and Galactic and Magellanic Cloud sources, including H II regions and planetary nebulae. An advanced extraction method applied directly to the multifrequency Planck time-ordered data, rather than the mission sky maps, was developed to allow an assessment of the variability of polarized sources. Our analysis of the time-ordered data from the Planck mission, tod2flux, allowed us to catalog the time-varying emission and polarization properties for these sources at the full range of polarized frequencies employed by Planck, 30-353 GHz. PCCS-PV provides the time-and frequency-dependent, polarized flux densities for all 153 sources. To illustrate some potential applications of the PCCS-PV, we conducted preliminary comparisons of our measurements of selected sources with published data from other astronomical instruments. In summary, we find general agreement between the Planck and the Institut de Radioastronomie Millimétrique (IRAM) polarization measurements as well as with the Metsähovi 37 GHz values at closely similar epochs. Here, these combined measurements also show the value of PCCS-PV results and the PCCS2 catalog for filling in missing spectral (or temporal) coverage and helping to define the spectral energy distributions of extragalactic sources. In turn, these results provide useful clues as to the physical properties of the sources.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Characterizing Wolf-Rayet stars in the near- and mid-infrared

We present refined color-color selection criteria for identifying Wolf-Rayet (WR) stars using available mid-infrared (MIR) photometry from WISE in combination with near-infrared (NIR) photometry from the Two Micron All Sky Survey. Using a sample of spectrally classified objects, we find that WR stars are well distinguished from the field stellar population in the (W1 – W2) versus (J – K{sub s} ) color-color diagram, and further distinguished from other emission line objects such as planetary nebulae, Be, and cataclysmic variable stars using a combination of NIR and MIR color constraints. As proof of concept we applied the color constraints to a photometric sample in the Galactic plane, located WR star candidates, and present five new spectrally confirmed and classified WC (1) and WN (4) stars. Analysis of the 0.8-5.0 μm spectral data for a subset of known, bright WC and WN stars shows that emission lines (primarily He I) extend into the 3.0-5.0 μm spectral region, although their strength is greatly diminished compared to the 0.8-2.5 μm region. The WR population stands out relative to background field stars at NIR and MIR colors due to an excess continuum contribution, likely caused by free-free scattering in dense winds. Mean photometric properties of known WRs are presented and imply that reddened late-type WN and WC sources are easier to detect than earlier-type sources at larger Galactic radii. WISE W3 and W4 images of 10 WR stars show evidence of circumstellar shells linked to mass ejections from strong stellar winds.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

A Novel Protection Scheme for Unbalanced Faults in Inverter Dominated Networks: A Computationally Efficient Algorithm for Entry-Level Relays

Microgrids are now a common practice in distribution systems to increase resilience and reliability. However, microgrid protection remains a critical challenge, considering its requirement to operate in both grid connected and islanded, and the variability in fault characteristics under each mode of operation. This paper presents unbalanced power (S unb ) based fault detection algorithm, which considers local voltage and current unbalances to determine faults in the system. S unb is a computationally efficient fault detection algorithm that is suitable for implementation in the programmable logic of entry level protective relays. In addition, the difference in current and voltage unbalance (D n ) is used to determine the fault type. The proposed method demonstrates high sensitivity and selectivity for line-to-ground (LG), line-to-line (LL), and double line-to-ground (LLG) faults, representing the most common faults in distribution systems. It also allows relay coordination with upstream and downstream protection devices in both island and grid connected operation, while preserving grading margins. The same pickup and time multiplier settings of a particular relay for both modes of operation eliminates the need for adaptive settings, which rely on communication networks. Validation was performed with a hardware-in-the-loop (HIL) setup using Typhoon HIL real time simulator interfaced with three entry-level, SEL 751 relays. Results confirmed the algorithm’s ability to discriminate fault conditions, and determine the fault type under both operating modes, maintain fast detection times, and ensure proper protection coordination.

fault classification↗
DOE OSTI2013

Uncertainty Analysis of Runoff Simulations and Parameter Identifiability in the Community Land Model – Evidence from MOPEX Basins

With the emergence of earth system models as important tools for understanding and predicting climate change and implications to mitigation and adaptation, it has become increasingly important to assess the fidelity of the land component within earth system models to capture realistic hydrological processes and their response to the changing climate and quantify the associated uncertainties. This study investigates the sensitivity of runoff simulations to major hydrologic parameters in version 4 of the Community Land Model (CLM4) by integrating CLM4 with a stochastic exploratory sensitivity analysis framework at 20 selected watersheds from the Model Parameter Estimation Experiment (MOPEX) spanning a wide range of climate and site conditions. We found that for runoff simulations, the most significant parameters are those related to the subsurface runoff parameterizations. Soil texture related parameters and surface runoff parameters are of secondary significance. Moreover, climate and soil conditions play important roles in the parameter sensitivity. In general, site conditions within water-limited hydrologic regimes and with finer soil texture result in stronger sensitivity of output variables, such as runoff and its surface and subsurface components, to the input parameters in CLM4. This study demonstrated the feasibility of parameter inversion for CLM4 using streamflow observations to improve runoff simulations. By ranking the significance of the input parameters, we showed that the parameter set dimensionality could be reduced for CLM4 parameter calibration under different hydrologic and climatic regimes so that the inverse problem is less ill posed.

analysis↗
DOE OSTI2024

Viral Envelope Evolution in Simian–HIV-Infected Neonate and Adult-Dam Pairs of Rhesus Macaques

We recently demonstrated that Simian–HIV (SHIV)-infected neonate rhesus macaques (RMs) generated heterologous HIV-1 neutralizing antibodies (NAbs) with broadly-NAb (bNAb) characteristics at a higher frequency compared with their corresponding dam. Here, we characterized genetic diversity in Env sequences from four neonate or adult/dam RM pairs: in two pairs, neonate and dam RMs made heterologous HIV-1 NAbs; in one pair, neither the neonate nor the dam made heterologous HIV-1 NAbs; and in another pair, only the neonate made heterologous HIV-1 NAbs. Phylogenetic and sequence diversity analyses of longitudinal Envs revealed that a higher genetic diversity, within the host and away from the infecting SHIV strain, was correlated with heterologous HIV-1 NAb development. We identified 22 Env variable sites, of which 9 were associated with heterologous HIV-1 NAb development; 3/9 sites had mutations previously linked to HIV-1 Env bNAb development. These data suggested that viral diversity drives heterologous HIV-1 NAb development, and the faster accumulation of viral diversity in neonate RMs may be a potential mechanism underlying bNAb induction in pediatric populations. Moreover, these data may inform candidate Env immunogens to guide precursor B cells to bNAb status via vaccination by the Env-based selection of bNAb lineage members with the appropriate mutations associated with neutralization breadth.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Regional Real-Time PV Spinning Reserve Estimator

Curtailed photovoltaic (PV) generation is a zero-marginal-cost spinning reserve that can be used for a number of active power control services. Unlike traditional spinning reserve providers, however, i.e., fossil-fueled generators, which have well-defined operating characteristics, e.g., available headroom or potential high limit (PHL), PV plants have by nature variable and uncertain operating characteristics. To ensure the effective coordination between PV plants and the system operator during an active power control event, accurate knowledge of the PV PHL is essential. It ensures that enough headroom is reserved by the PV plants to deliver the award services in real time and informs feasible dispatch decisions made by the market operator. To tackle this challenge, a novel reference-control grouping-based PV plant reserve estimation method has been proposed by the National Renewable Energy Laboratory under past projects funded by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Solar Energy Technologies Office. The estimation method separates inverters within a plant into two groups: a control group and a reference group. While the reference group is reserved to operate at its PHL, the control group can be curtailed to provide the grid services. Real-time outputs from the reference inverters are used to estimate the PHL for the whole plant based on the ratio between capacities of the reference group and of the plant. This work further enhances the methodology by (1) improving the model accuracy through machine learning; (2) automating the reference inverter selection through correlation analysis; (3) considering estimation look-ahead windows; and (4) applying to regional spinning reserve estimation. Significant performance improvement has been observed based on real-world data collected by CAISO, Southern Company, and Terabase Energy. Compared with the original scaling method, the newly proposed machine learning-based approach reduces the estimation errors by 30% and 13% at the plant level and region level, respectively. Results obtained from this project are intended to be used by grid operators, market operators, balancing authorities, and PV plant owners and operators to facilitate PV participation in ancillary service markets. Regulators, policymakers, and system planners can also consider the results of this work in their decision-making processes. In addition to the performance improvement on the existing reference-control based grouping method, we also investigated how the variability of PV generation from a single PV inverter can be used to represent the variability of PV generation at the plant level.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Application of High Performance Computing for Studying Cyclic Variability in Dilute Internal Combustion Engines

Combustion instabilities in dilute internal combustion engines are manifest in cyclic variability (CV) in engine performance measures such as integrated heat release or shaft work. Understanding the factors leading to CV is important in model-based control, especially with high dilution where experimental studies have demonstrated that deterministic effects can become more prominent. Observation of enough consecutive engine cycles for significant statistical analysis is standard in experimental studies but is largely wanting in numerical simulations because of the computational time required to compute hundreds or thousands of consecutive cycles. We have proposed and begun implementation of an alternative approach to allow rapid simulation of long series of engine dynamics based on a low-dimensional mapping of ensembles of single-cycle simulations which map input parameters to output engine performance. This paper details the use Titan at the Oak Ridge Leadership Computing Facility to investigate CV in a gasoline direct-injected spark-ignited engine with a moderately high rate of dilution achieved through external exhaust gas recirculation. The CONVERGE™ CFD software was used to perform single-cycle simulations with imposed variations of operating parameters and boundary conditions selected according to a sparse grid sampling of the parameter space. Using an uncertainty quantification technique, the sampling scheme is chosen similar to a design of experiments grid but uses algorithms designed to minimize the number of samples required to achieve a desired degree of accuracy. The simulations map input parameters to output metrics of engine performance for a single cycle, and by mapping over a large parameter space, results can be interpolated from within that space. This interpolation scheme forms the basis for a low-dimensional ‘metamodel’ (or model of a model) which can be used to mimic the dynamical behavior of corresponding high-dimensional simulations. Simulations of high-EGR spark-ignition combustion cycles within a parametric sampling grid were performed and analyzed statistically, and sensitivities of the physical factors leading to high CV are presented. With these results, the prospect of producing low-dimensional metamodels to describe engine dynamics at any point in the parameter space will be discussed. Additionally, modifications to the methodology to account for nondeterministic effects in the numerical solution environment are proposed.

Finney, Charles E. A.↗
DOE OSTI2020

CheKiPEUQ Intro 2: Harnessing Uncertainties from Data Sets, Bayesian Design of Experiments in Chemical Kinetics**

When choosing experimental conditions, Bayesian statistical tools can predict the experimental choices which will yield the highest information gain. Experimental choices could be temperature, pressure, reaction time, number of measurements, reactor volume, etc.. Three example analyses are presented here, each using the software Chemical Kinetics Parameter Estimation and Uncertainty Quantification (CheKiPEUQ). Information gain is a measure of reduction of uncertainty in a model's parameters. The three chemical system examples presented each illustrate Bayesian Design of Experiments using information gain. In the first chemical example, temperature selection impacts the information gain for the free energy of reaction in a two-component equilibrium reaction. In the second example, temperature and pressure are explored for a competitive adsorption Langmuir replacement reaction system. Finally, the third example is a catalytic membrane reactor which is a culmination of the previous examples. The catalytic membrane reactor has a complex and nonlinear response in the observables which is solved by numerical evaluation. In the three examples, the experimental conditions are treated as design variables for maximizing information gain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Aqueous Sulfate Separation by Sequestration of [(SO 4 ) 2 (H 2 O) 4 ] 4− Clusters within Highly Insoluble Imine‐Linked Bis‐Guanidinium Crystals

Abstract Selective crystallization of sulfate with a simple bis‐guanidinium ligand, self‐assembled in situ from terephthalaldehyde and aminoguanidinium chloride, was employed as an effective way to separate the highly hydrophilic sulfate anion from aqueous solutions. The resulting bis‐iminoguanidinium sulfate salt has exceptionally low aqueous solubility ( K sp =2.4×10 −10 ), comparable to that of BaSO 4 . Single‐crystal X‐ray diffraction analysis showed the sulfate anions are sequestered as [(SO 4 ) 2 (H 2 O) 4 ] 4− clusters within the crystals. Variable‐temperature solubility measurements indicated the sulfate crystallization is slightly endothermic ( ΔH cryst =3.7 kJ mol −1 ), thus entropy driven. The real‐world utility of this crystallization‐based approach for sulfate separation was demonstrated by removing up to 99 % of sulfate from seawater in a single step.

Custelcean, Radu↗
DOE OSTI2021

Machine Learning Self-Diffusion Prediction for Lennard-Jones Fluids in Pores

Predicting the diffusion coefficient of fluids under nanoconfinement is important for many applications including the extraction of shale gas from kerogen and product turnover in porous catalysts. Due to the large number of important variables, including pore shape and size, fluid temperature and density, and the fluid–wall interaction strength, simulating diffusion coefficients using molecular dynamics (MD) in a systematic study could prove to be prohibitively expensive. Here, we use machine learning models trained on a subset of MD data to predict the self-diffusion coefficients of Lennard-Jones fluids in pores. Our MD data set contains 2280 simulations of ideal slit pore, cylindrical pore, and hexagonal pore geometries. We use the forward feature selection method to determine the most useful features (i.e., descriptors) for developing an artificial neutral network (ANN) model with an emphasis on easily acquired features. Our model shows good predictive ability with a coefficient of determination (i.e., R 2 ) of ~0.99 and a mean squared error of ~2.9 × 10 –5 . Finally, we propose an alteration to our feature set that will allow the ANN model to be applied to nonideal pore geometries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Modular Linear Thermoviscoelastic Model

Time-dependent, viscoelastic responses of materials like polymers and glasses have long been studied. As such, a variety of models have been put forth to describe the behavior including simple rheological models (e.g. Maxwell, Kelvin), linear "fading memory" theories, and hereditary integral based linear thermal viscoelastic approaches as well as more recent nonlinear theories that are either integral, fictive temperature, or differential internal state variable based. The current work details a new LINEAR_THERMOVISCOELASTIC model that has been added to LAME. This formulation represents a viscoelastic theory that neglects some of the phenomenological details of the PEC/SPEC models in favor of efficiency and simplicity. Furthermore, this new model is a first step towards developing "modular" viscoelastic capabilities akin to those available with hardening descriptions for plasticity models in LAME. Specifically, multiple different (including user-defined) shift-factor forms are implemented with each being easily selected via parameter specification rather than requiring distinct material models.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Urban weather modeling using WRF: linking physical assumptions, code implementation, and observational needs

The Weather Research and Forecasting (WRF) model includes urban schemes that simulate the influence of urban surfaces on the atmosphere using parameterizations for flux, and radiative exchanges. Three core schemes – the Bulk urban parameterization, Single-Layer Urban Canopy Model (SLUCM), and Multi-Layer Urban Canopy Model (MLUCM) – represent increasing levels of complexity. Although the parameterizations within these urban schemes are described in the literature, their specific implementation remains poorly documented, thus slowing down model development efforts. This manuscript provides a roadmap to the three urban schemes in WRF version 4.5.2, presenting equations using the same symbols as in the model code, along with references to code lines, and including graphics and explanations that connect the code to its physical foundations. Our thorough review of the urban parameterizations implemented in WRF version 4.5.2 highlighted a handful of parameters that may introduce discontinuities in simulations: (i) in the SLUCM, a 1 mm h −1 rain rate threshold is employed to switch between two minimum moisture availability parameterizations, thus impacting latent heat flux calculations; (ii) in the SLUCM a threshold is used to partition shortwave radiation into direct and diffuse components; (iii) in all three urban schemes, the bulk Richardson number is employed to select the similarity function, which influences the vertical distribution of heat and momentum. We also identified a highly simplified treatment of the radiative balance on roof surfaces. The implications of these simplifications can be assessed through targeted observations across relevant conditions, including varying precipitation rates, cloud cover, and transitions between stability regimes. Furthermore, the widespread application of the Monin-Obukhov similarity theory in these urban schemes warrants model evaluation under highly stable and unstable conditions and in heterogeneous urban settings with variable land cover and building heights on scales finer than model resolution. To address these challenges, we offer guidance on observational strategies, emphasizing the need for multi-parametric measurements to capture potential compensating biases and multi-height measurements that align with the levels where quantities are diagnostic and prognosed in the model (i.e., the lowest atmospheric level of the WRF model). Finally, our inspection of the code revealed implementation bugs that have now been corrected in WRF versions 4.6.0 and 4.6.1. Sensitivity tests over the Atlanta urban area show that these corrections affect surface temperatures, underscoring the importance of performing rigorous documentation and verification of the implementation of parameterizations in model code.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Clinical Usefulness of {sup 18}F-Fluorodeoxyglucose-Positron Emission Tomography in Patients With Locally Advanced Pancreatic Cancer Planned to Undergo Concurrent Chemoradiation Therapy

Purpose: To assess the role of coregistered {sup 18}F-fluorodeoxyglucose positron emission tomography (FDG-PET) in detecting radiographically occult distant metastasis (DM) at staging in patients with locally advanced pancreatic cancer (LAPC) and to study whether FDG-PET parameters can predict relatively long-term survival in patients who are more likely to benefit from chemoradiation therapy (CRT). Methods and Materials: From our institutional database, we identified 388 LAPC patients with M0 on conventional computed tomography (CT) who were planned to undergo CRT. Coregistered FDG-PET staging was offered to all patients, and follow-up FDG-PET was used at the clinical discretion of the physician. Results: FDG-PET detected unsuspected CT-occult DM in 33% of all 388 patients and allowed them to receive systemic therapy immediately. The remaining 260 patients (PET-M0) underwent CRT selectively as an initial treatment. Early DM arose in 13.1% of 260 patients, and the 1-year estimated locoregional recurrence rate was 5.4%. Median overall survival (OS) and progression-free survival (PFS) were 14.6 and 9.3 months, respectively, at a median follow-up time of 32.3 months (range, 10-99.1 months). Patients with a baseline standardized uptake value (SUV) <3.5 and/or SUV decline ≥60% had significantly better OS and PFS than those having none, even after adjustment for all potential confounding variables (all P<.001). Conclusions: FDG-PET can detect radiographically occult DM at staging in one-third of patients and spare them from the potentially toxic therapy. Additionally, FDG-PET parameters including baseline SUV and SUV changes may serve as useful clinical markers for predicting the prognosis in LAPC patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Antibody-independent Targeted Quantification of TMPRSS2-ERG Fusion Protein Products in Prostate Cancer

Fusions between the transmembrane protease serine 2 (TMPRSS2) and ETS related gene (ERG) represent one of the most specific biomarkers that define a distinct molecular subtype of prostate cancer. The studies on TMPRSS2-ERG gene fusions have seldom been performed at the protein level, primarily due to the lack of high-quality antibodies or an antibody-independent method that is sufficiently sensitive for detecting the truncated ERG protein products resulting from TMPRSS2-ERG gene fusions and alternative splicing. Herein, we applied a recently developed PRISM (high-pressure high-resolution separations with intelligent selection and multiplexing)-SRM (selected reaction monitoring) strategy for quantifying ERG protein in prostate cancer cell lines and tumors. The highly sensitive PRISM-SRM assays led to confident detection of 6 unique ERG peptides in either the TMPRSS2-ERG positive cell lines or tissues but not in the negative controls, indicating that ERG protein expression is highly correlated with TMPRSS2-ERG gene rearrangements. Significantly, our results demonstrated for the first time that at least two groups of ERG protein isoforms were simultaneously expressed at variable levels in TMPRSS2-ERG positive samples as evidenced by concomitant detection of two mutually exclusive peptides. Three peptides shared across almost all fusion protein products were determined to be the most abundant peptides, and hence can be used as “signature” peptides for detecting ERG overexpression resulting from TMPRSS2-ERG gene fusion. These PRISM-SRM assays provide valuable tools for studying TMPRSS2-ERG gene fusion protein products, thus improving our understanding of the role of TMPRSS2-ERG gene fusion in the biology of prostate cancer.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2016

A Droplet Microfluidic Platform for Automating Genetic Engineering

We present a water-in-oil droplet microfluidic platform for transformation, culture and expression of recombinant proteins in multiple host organisms including bacteria, yeast and fungi. The platform consists of a hybrid digital microfluidic/channel-based droplet chip with integrated temperature control to allow complete automation and integration of plasmid addition, heat-shock transformation, addition of selection medium, culture, and protein expression. The microfluidic format permitted significant reduction in consumption (100-fold) of expensive reagents such as DNA and enzymes compared to the benchtop method. Furthermore, the chip contains a channel to continuously replenish oil to the culture chamber to provide a fresh supply of oxygen to the cells for long-term (~5 days) cell culture. The flow channel also replenished oil lost to evaporation and increased the number of droplets that could be processed and cultured. The platform was validated by transforming several plasmids into Escherichia coli including plasmids containing genes for fluorescent proteins GFP, BFP and RFP; plasmids with selectable markers for ampicillin or kanamycin resistance; and a Golden Gate DNA assembly reaction. We also demonstrate the applicability of this platform for transformation in widely used eukaryotic organisms such as Saccharomyces cerevisiae and Aspergillus Niger. Duration and temperatures of the microfluidic heat-shock procedures were optimized to yield transformation efficiencies comparable to those obtained by benchtop methods with a throughput up to 6 droplets/min. The platform we proposed offers potential for automation of molecular biology experiments significantly reducing cost, time and variability while improving throughput.

59 BASIC BIOLOGICAL SCIENCES↗