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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.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Role of isothiocyanate conjugate of pterostilbene on the inhibition of MCF-7 cell proliferation and tumor growth in Ehrlich ascitic cell induced tumor bearing mice

Naturally occurring pterostilbene (PTER) and isothiocyanate (ITC) attract great attention due to their wide range of biological properties, including anti-cancer, anti-leukemic, anti-bacterial and anti-inflammatory activities. A novel class of hybrid compound synthesized by introducing an ITC moiety on PTER backbone was evaluated for its anti-cancer efficacy in hormone-dependent breast cancer cell line (MCF-7) in vitro and Ehrlich ascitic tumor bearing mice model in vivo. The novel hybrid molecule showed significant in vitro anti-cancer activity (IC{sub 50}=25±0.38) when compared to reference compound PTER (IC{sub 50}=65±0.42). The conjugate molecule induced both S and G2/M phase cell cycle arrest as indicated by flow cytometry analysis. In addition, the conjugate induced cell death was characterized by changes in cell morphology, DNA fragmentation, activation of caspase-9, release of cytochrome-c into cytosol and increased Bax: Bcl-2 ratio. The conjugate also suppressed the phosphorylation of Akt and ERK. The conjugate induced cell death was significantly increased in presence of A6730 (a potent Akt1/2 kinase inhibitor) and PD98059 (a specific ERK inhibitor). Moreover, the conjugated PTER inhibited tumor growth in Ehrlich ascitic cell induced tumor bearing mice as observed by reduction in tumor volume compared to untreated animals. Collectively, the pro-apoptotic effect of conjugate is mediated through the activation of caspases, and is correlated with the blockade of the Akt and ERK signaling pathways in MCF-7 cells. - Highlights: • Conjugate was prepared by appending isothiocyanate moiety on pterostilbene backbone. • Conjugate showed anticancer effects at comparatively lower dose than pterostilbene. • Conjugate caused blockage of the Akt and ERK signaling pathways in MCF-7 cells. • Conjugate significantly reduced solid tumor volume as compared to pterostilbene.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

The Electron-Conformational Model of Ryanodine Receptors of the Heart Cell

The main ideas of an electron-conformational (EC) model of ligand-activated ryanodine channels (RyR) that reduces many degrees of freedom of this gigantic nanoscopic molecular complex to two so-called electron and conformational degrees of freedom are presented. In the toy model, the conformational potential or energy profile of the RyR channel represents two branches that describe the dependence of energy on the conformational coordinate (reaction coordinate) in the initial and ligand-activated states, respectively. A model extension that takes into account both the tetrameric structure of the RyR channel and additional (orthogonal) rotational conformational mode has been considered. The EC model has been demonstrated to give a biophysical basis to the traditional phenomenological model of Markov chains. To demonstrate the possibilities of the EC model, we refer to examples of model description of the dynamics of isolated RyR channels and clusters of RyR channels in release units of the heart cell.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Conditional reprogrammed human limbal epithelial cells represent a novel in vitro cell model for drug responses

Highlights: • This is the first study describing long term cultures of normal human limbal epithelial cells (CR-LECs) using CR technology. • CR-LEC cells maintain normal karyotype, normal response to DNA damage, well-defined structured spheres in 3D culture. • CR-LEC cells retain the commitment of limbal tissue origin in defined culture conditions. • CR-LEC cells may serve a stable normal human cell model for toxicity assessment. In this study, we established human limbal epithelial cells (LECs) from normal limbal tissues by using Conditional Reprogramming (CR) technology (refer to CR-LEC cells in this study). We have successfully established CR-LEC cell strains from three human donors (3 out of 3), and normal rabbits (2 out of 2) and pig (1 out of 1) as well. CR-LEC cells sustained a continuous and stable proliferation status with a normal karyotype, normal response to DNA damage, well-defined structured spheres in matrigel 3D culture. Responses of CR-LEC cells to IFN α2b, Ganciclovir and 5-Fluorouracil were different, suggesting that these drugs had different toxicities to these cells as expected. More important, there was no significant difference of responses to drugs between early and late passages of CR-LEC cells (p>0.05), indicating CR-LEC cells can serve a stable normal human cell model for toxicity assessment. Toxicity tests with monolayer cultures of CR-LEC cells were measured by staining the F-actin and Dsg-1 expression. Toxicity of three drugs at LD50 concentration resulted in a gradually increased destruction of monolayer, which is, in accordance with the irritation grade of three drugs on human cornea epithelium. Therefore, CR-LEC cells provide a novel and reliable in vitro physiological cell model for corneal toxicity assessment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Electrochemical Modeling and Experimental Verification of Lithiation Gradients in Oxide Cathodes of Lithium-Ion Cells

Lithiated nickel-cobalt-manganese oxides, such as NCM523, are used in the positive electrode (cathode) of Li-ion cells. Using operando X-ray diffraction profilometry, lithiation gradients in the cathode matrix can be observed and quantified by expansion into Legendre polynomials with time-dependent weights. These weights (referred to as gradients) increase in magnitude when electric current flows through the cell, decrease during potentiostatic hold and finally relax to zero when the current is interrupted during open circuit rest. Both physics-based electrochemical models and operando X-ray experiments suggest that the time constants for gradient growth and abatement are primarily determined by ionic diffusion in the oxide particles, which in turn depends on their lithium content. In contrast, the magnitude of gradients depends mainly on the applied current. The X-ray profilometry provides a way of directly probing the formation and disappearance of Li gradients across the cathode during fast cycling, which can help to diagnose the effects of material degradation in the cells.

25 ENERGY STORAGE↗
DOE OSTI2022

Towards replacement of animal tests with in vitro assays: a gene expression biomarker predicts in vitro and in vivo estrogen receptor activity

High-throughput transcriptomics (HTTr) has the potential to support efforts to reduce or replace some animal tests. In past studies, we described a computational approach utilizing a gene expression biomarker consisting of 46 genes to predict estrogen receptor (ER) activity after chemical exposure in ER-positive human breast cancer cells including the MCF-7 cell line. We hypothesized that the biomarker model could identify ER activities of chemicals examined by Endocrine Disruptor Screening Program (EDSP) Tier 1 screening assays in which transcript profiles of the same chemicals were examined in MCF-7 cells. For the 62 chemicals examined including 5 chemicals examined in this study using RNA-Seq, the ER biomarker model accuracy was 1) 97% for in vitro reference chemicals, 2) 76–85% for guideline uterotrophic assays, and 3) 87–88% for guideline and nonguideline uterotrophic assays. For the same chemicals, these accuracies were similar or slightly better than those of the ToxCast ER model based on 18 in vitro assays. The performance of the ER biomarker model indicates that HTTr interpreted using the ER biomarker correctly identifies active and inactive ER reference chemicals. Finally, as part of the HTTr screening program the approach could rapidly identify chemicals with potential ER bioactivities for additional screening and testing.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-494: Influence of Proton Track-Cell Nucleus Incidence Angle On Relative Biological Effectiveness

Purpose: To explain a Monte Carlo (MC) simulation artifact whereby differences in relative biological effectiveness (RBE) in the induction of initial double strand breaks are observed as a function of the proton track incidence angles in a geometric cell nucleus model. Secondly, to offer an alternative isotropic irradiation procedure to mitigate this effect. Methods: MC tracks of 1 MeV protons were generated in an event-by-event mode. They were overlaid on a cylindrical model of a cell nucleus containing 6×109 nucleotide base pairs. The tracks incidence angle θ with respect to the cell nucleus’s axis was varied in 10 degrees intervals, each time generating one hundred fractions of ∼2 Gy. Strand breaks were scored in the modeled DNA sugar-phosphate groups and further sub-classified into single or double strand breaks (ssbs or dsbs). For each angle, an RBE for the induction of initial dsbs with reference to Co-60 was calculated. Results: Our results show significant angular dependencies of RBE, with maximum values for incidence angles parallel to the nucleus central axis. Further examination shows that the higher cross-sections for the creation of dsbs is due to the preferential alignment of tracks with geometrical sub-parts of the cell nucleus model, especially the nucleosomes containing the sugar-phosphate groups. To alleviate the impact of this simulation artifact, an average RBE was calculated with a procedure based on a weighted sampling of the angular data. Conclusion: This work demonstrates a possible numerical artifact in estimated RBE if the influence of the particle incidence angle is not correctly taken into account. A correction procedure is presented to better conform the simulations to real-life experimental conditions. We would like to acknowledge support from the Fonds de recherche du Quebec Sante (FRQS), from the CREATE Medical Physics Research Training Network grant (number 432290) of NSERC, support from NSERC under grants RGPIN 397711-11 and RGPIN-2014-06475 and support from the CIHR under grants MOP-114910, MOP-136774 and MOP-102550.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Non-destructive electrochemical diagnosis of failure mechanisms in aqueous zinc batteries

The early detection of secondary reactions that affect the life and performance of zinc manganese oxide batteries requires a shift from conventional time-consuming and often destructive procedures to rapid lifetime-predictive techniques. In this work, an electrochemical approach is employed to elucidate independent signatures for four common types of failure mechanisms in zinc manganese dioxide (Zn||MnO2) batteries—namely, the loss of zinc inventory, the loss of active material at the cathode, electrolyte depletion, and increased cell impedance. Our findings, specific to coin cell configurations, reveal that each induced failure mechanism can be distinctively modeled and identified based on responses from the rest voltage and columbic-efficiency data for prompt detection. For instance, electrolyte depletion response manifests a distinctive abrupt (>80 %) decrease in columbic efficiency (CE) and charge-rest voltage (Vc) while the discharge-rest voltage remained constant at ~1.3 V. Furthermore, electrolyte rejuvenation of the cell increased the CE to >95 % and restored Vc from ~0.3 to >1.7 V. Recovery experiments and reference performance tests demonstrated consistency between electrochemical descriptors and their associated failure mechanisms. Further, the outcomes of this work provide valuable insights and data models for some of the dominant failure mechanisms present in zinc manganese battery chemistries, which are beneficial to accelerated early-lifetime diagnosis and advancement of Zn batteries development.

25 ENERGY STORAGE↗
DOE OSTI2022

The “Fresnel Equations” for Diffuse radiation on Inclined photovoltaic Surfaces (FEDIS)

Here the well-known Fresnel equations solve for the reflection and transmission of light for precise incident angles. The transmission of diffuse radiation incident on a planar or domed surface is often needed for real-world applications. Due to the complexity of the Fresnel equations, the analytical solution of the integration has hitherto been unobtainable over the last centuries. Therefore, this problem was numerically solved by integrating the angular transmittances in space often leading to substantial computing burden and bias in the results. To efficiently estimate the solar energy resource for a glass-covered photovoltaic (PV) module, we derive an analytical solution of diffuse transmission based on the rigorous integration of an alternate form of the Fresnel equations. The approach leads to a simple yet accurate relative transmittance model that reconciles the solar energy sensed by pyranometers and PV panels. With limited and clearly stated approximations, the complex mathematical derivation resulted in an elegant solution. An experiment using 1-year of data at the National Renewable Energy Laboratory's (NREL's) Solar Radiation Research Laboratory (SRRL) shows that the new model dramatically decreases the disparity between the solar radiation measurements by a Kipp and Zonen CM Pyranometer 22 (CMP22) and an IMT reference cell on a 1-axis tracking system. The solution in this paper can be widely used in scientific and engineering research, development, and applications wherever the Fresnel equations are used.

14 SOLAR ENERGY↗
DOE OSTI2020

The changing mouse embryo transcriptome at whole tissue and single-cell resolution

During mammalian embryogenesis, differential gene expression gradually builds the identity and complexity of each tissue and organ system 1 . Here we systematically quantified mouse polyA-RNA from day 10.5 of embryonic development to birth, sampling 17 tissues and organs. The resulting developmental transcriptome is globally structured by dynamic cytodifferentiation, body-axis and cell-proliferation gene sets that were further characterized by the transcription factor motif codes of their promoters. We decomposed the tissue-level transcriptome using single-cell RNA-seq (sequencing of RNA reverse transcribed into cDNA) and found that neurogenesis and haematopoiesis dominate at both the gene and cellular levels, jointly accounting for one-third of differential gene expression and more than 40% of identified cell types. By integrating promoter sequence motifs with companion ENCODE epigenomic profiles, we identified a prominent promoter de-repression mechanism in neuronal expression clusters that was attributable to known and novel repressors. Focusing on the developing limb, single-cell RNA data identified 25 candidate cell types that included progenitor and differentiating states with computationally inferred lineage relationships. We extracted cell-type transcription factor networks and complementary sets of candidate enhancer elements by using single-cell RNA-seq to decompose integrative cis -element (IDEAS) models that were derived from whole-tissue epigenome chromatin data. These ENCODE reference data, computed network components and IDEAS chromatin segmentations are companion resources to the matching epigenomic developmental matrix, and are available for researchers to further mine and integrate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

PV Reference Cells for Outdoor Use: An Investigation of Calibration Factors

Reference cells are widely used in the photovoltaic (PV) industry to measure irradiance. For field applications and outdoor use, a variety of products are on the market, and they are often perceived as a low-cost alternative to thermopile radiometers. But reference cell characteristics differ substantially from the latter, therefore measurements made by one category of instrument cannot be substituted for or directly compared with the other. The National Renewable Energy Laboratory's (NREL's) Solar Radiation Research Laboratory is currently in a multiyear effort to develop guidance and recommendations for the design and use of outdoor reference cells, with a view to reducing inconsistencies and measurement uncertainty. The core of this effort is the long-term deployment of 39 units of 10 distinct types made by 6 manufacturers. This report compares the calibration factors provided by manufacturers - which most users rely upon - to those measured at a high level of accuracy by NREL's Cell Lab. It also reports on the application of the Broadband Outdoor Radiometer Calibration (BORCAL) method to reference cells. As a group, the factory calibrations for the crystalline silicon cells showed a small positive bias of +0.7%, with a tight distribution around this value. This is a very good result for the manufacturers. The two World Photovoltaic Scale cells constituted outliers, with a mean deviation of -0.8%, which is still within the reported uncertainty ranges. The data collected during the BORCAL procedures show a strong and systematic fluctuation of the apparent responsivity of the reference cells over the course of a day, which was anticipated. Consequently, the standard BORCAL R@45 calibration factors underestimated the reference cell responsivities by 1%-4%. An alternate responsivity indicator was developed, R'@30, incorporating adjustments for temperature response, spectral response, and directional response. This reduced the mean deviation to -0.4% compared to the Cell Lab. Further, two independent BORCAL sessions were able to produce the same values to within ±0.2%. This could be a viable approach for verifying reference cells using existing BORCAL infrastructure, for example, to evaluate their long-term stability. The daily profiles of responsivity obtained during the BORCAL sessions (provided in Appendix A) show clear patterns of differences between models, which provides evidence that their directional responses differ from each other; thus, two sensors that are calibrated correctly might give the same reading at 30° zenith angle but systematically different readings at 60°. The impact of these inconsistencies in field operation will be quantified using the long-term observations started in 2020.

14 SOLAR ENERGY↗
DOE OSTI2017

Efficient Safety and Degradation Modeling of Automotive Lithium-ion Cells and Packs

This document is intended to give an overall synopsis of the activities and accomplishments of the EC Power CAEBAT2 project over the course of four years. The reader is referred to the previously submitted quarterly reports, review presentations, and AMR presentations for further technical details. As highlighted by the numerous results shown herein and the volume and quality of the publications and presentations made in the course of this project, we feel that we have made a strong impact in the community.

25 ENERGY STORAGE↗
DOE OSTI2016

Stable discrete representation of relativistically drifting plasmas

Representing the electrodynamics of relativistically drifting particle ensembles in discrete, co-propagating Galilean coordinates enables the derivation of a Particle-In-Cell algorithm that is intrinsically free of the numerical Cherenkov instability for plasmas flowing at a uniform velocity. Application of the method is shown by modeling plasma accelerators in a Lorentz-transformed optimal frame of reference.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2010

Evaluation of PV performance models and their impact on project risk.

Photovoltaic systems are often priced in $/W{sub p}, where Wp refers to the DC power rating of the modules at Standard Test Conditions (1000 W/m{sup 2}, 25 C cell temperature) and $ refers to the installed cost of the system. However, the true value of the system is in the energy it will produce in kWhs, not the power rating. System energy production is a function of the system design and location, the mounting configuration, the power conversion system, and the module technology, as well as the solar resource. Even if all other variables are held constant, the annual energy yield (kWh/kW{sup p}) will vary among module technologies because of differences in response to low-light levels and temperature. Understanding energy yield is a key part of understanding system value. System performance models are used during project development to estimate the expected output of PV systems for a given design and location. Performance modeling is normally done by the system designer/system integrator. Often, an independent engineer will also model system output during a due diligence review of a project. A variety of system performance models are available. The most commonly used modeling tool for project development and due diligence in the United States is probably PVsyst, while those seeking a quick answer to expected energy production may use PVWatts. In this paper, we examine the variation in predicted energy output among modeling tools and users and compare that to measured output.

14 SOLAR ENERGY↗
DOE OSTI2016

Zero-Kelvin Compression Isotherms of the Elements 1 ≤ Z ≤ 92 to 100 GPa

Most of the chemical elements have now been compressed close to or above 100 GPa (1 Mbar) pressure in diamond-anvil cells and the pressure–volume room-temperature isotherms have been measured. We collect these data and use simple lattice-dynamics models to reduce the isotherms to 0 K. We have extended the published work by making new diamond-anvil-cell measurements on Cr and Rh, and by conducting density-functional calculations on the elements Po, At, Rn, Fr, Ra, and Ac. The 0 K data are tabulated for all elements 1 ≤ Z ≤ 92 and 0 ≤ P ≤ 100 GPa. These data are useful for generating wide-range equation of state models and for studying the stability of chemical compounds at high pressure (“Megabar chemistry”). The tables presented here are intended to be reference thermodynamic tables for use in high-pressure research. Further experimental and theoretical work will be needed to extend the tables to higher pressure and to improve accuracy.

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

DECENTRALIZED APPROACH TO MULTI-ZONE GREY-BOX MODELING FOR MODEL-BASED PREDICTIVE CONTROL

This study aims to improve the easiness of utilizing the grey-box model (i.e., Resistance-Capacitance circuit) for Model-based Predictive Control (MPC). The primary barrier of implementing the MPC is estimating the control-oriented building model that needs to be computationally inexpensive and quick but reasonably precise in predicting building load and indoor conditions. The estimating of the model parameters becomes more complicated when the building scale is larger; e.g., multi-zone building. In this study, a decentralized approach is introduced; each zone is split and individually estimated with measured boundary temperature from adjacent zones integrated into one single system model. The proposed decentralized method is demonstrated with experimental data from a full-scale multi-zone test cell compared with the centralized reference case.

Joe, Jaewan↗
DOE OSTI2022

Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample

Accurate detection of somatic mutations is challenging but critical in understanding cancer formation, progression, and treatment. We recently proposed NeuSomatic, the first deep convolutional neural network-based somatic mutation detection approach, and demonstrated performance advantages on in silico data. In this study, we use the first comprehensive and well-characterized somatic reference data sets from the SEQC2 consortium to investigate best practices for using a deep learning framework in cancer mutation detection. Using the high-confidence somatic mutations established for a cancer cell line by the consortium, we identify the best strategy for building robust models on multiple data sets derived from samples representing real scenarios, for example, a model trained on a combination of real and spike-in mutations had the highest average performance. The strategy identified in our study achieved high robustness across multiple sequencing technologies for fresh and FFPE DNA input, varying tumor/normal purities, and different coverages, with significant superiority over conventional detection approaches in general, as well as in challenging situations such as low coverage, low variant allele frequency, DNA damage, and difficult genomic regions.

59 BASIC BIOLOGICAL SCIENCES↗
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 OSTI2016

Lipid bilayer thickness determines cholesterol's location in model membranes

Cholesterol is an essential biomolecule of animal cell membranes, and an important precursor for the biosynthesis of certain hormones and vitamins. It is also thought to play a key role in cell signaling processes associated with functional plasma membrane microdomains (domains enriched in cholesterol), commonly referred to as rafts. In all of these diverse biological phenomena, the transverse location of cholesterol in the membrane is almost certainly an important structural feature. Using a combination of neutron scattering and solid-state 2 H NMR, we have determined the location and orientation of cholesterol in phosphatidylcholine (PC) model membranes having fatty acids of different lengths and degrees of unsaturation. The data establish that cholesterol reorients rapidly about the bilayer normal in all the membranes studied, but is tilted and forced to span the bilayer midplane in the very thin bilayers. The possibility that cholesterol lies flat in the middle of bilayers, including those made from PC lipids containing polyunsaturated fatty acids (PUFAs), is ruled out. Finally, these results support the notion that hydrophobic thickness is the primary determinant of cholesterol's location in membranes.

59 BASIC BIOLOGICAL SCIENCES↗