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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

SIRT1 reduces epigenetic and non-epigenetic changes to maintain the quality of postovulatory aged oocytes in mice

Highlights: • The intensity of H3K9ac and H3K4me2/3 increased in postovulatory aged oocytes. • SIRT1 overexpression inhibited the increase of H3K9ac and H3K4me2/3. • SIRT1 overexpression ameliorated aging-induced epigenetic and non-epigenetic changes in oocytes. Postovulatory oocyte aging has a major influence on the development potential of embryos. Many antioxidants can delay oocyte aging by regulating the expression of SIRT1. However, there is a lack of knowledge on SIRT1 function in postovulatory oocyte aging. In vitro transcribed RNA of Sirt1 was injected into fresh oocytes to investigate the function of SIRT1 during postovulatory oocyte aging. In the present study, SIRT1 was found to be down-regulated in aged oocytes compared with fresh oocytes. Meanwhile the intensity of acetylation of H3K9 (H3K9ac) and H3K4 methylation increased in postovulatory aged oocytes. After the oocytes were injected with SIRT1 and aged for 12 h, the intensity of H3K9ac and H3K4 methylation markedly decreased compared with controls. Furthermore, SIRT1 overexpression also reduced the aging-induced oocyte morphological changes and reactive oxygen species accumulation, maintained the spindle normal morphology and attenuated the aging-associated abnormalities of mitochondrial function. The role of SIRT1 in protecting oocyte aging was diminished when oocytes with overexpressed SIRT1 were cultured with SIRT1 inhibitor EX-527. Briefly, these present results show that SIRT1 not only reduced the non-epigenetic changes such as abnormal oocyte morphology, ROS accumulation, spindle defects and mitochondrial dysfunctions but also regulated the epigenetic changes in order to maintain the quality of postovulatory aged oocytes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Checkpoint kinases are required for oocyte meiotic progression by the maintenance of normal spindle structure and chromosome condensation

Highlights: • Inhibition of Chk1/2 has no significant effects on germinal vesicle breakdown. • Chk1/2 inhibition results in the first polar body extrusion defects. • Chk1/2 is critically involved in meiotic spindle organization. • Inhibition of Chk1/2 leads to abnormal chromosome condensation. • Chk1/2 is important for the development of MII stage oocytes. Checkpoint kinases (Chk) 1/2 are known for DNA damage checkpoint and cell cycle control in somatic cells. According to recent findings, the involvement of Chk1 in oocyte meiotic resumption and Chk2 is regarded as an essential regulator for progression at the post metaphase I stage (MI). In this study, AZD7762 (Chk1/2 inhibitor) and SB218078 (Chk1 inhibitor) were used to uncover the joint roles of Chk1/2 and differentiate the importance of Chk1 and Chk2 during oocyte meiotic maturation. Inhibition of Chk1/2 or Chk1 alone had no significant effect on germinal vesicle breakdown (GVBD) but significantly inhibited the first polar body (PB1). Interestingly, inhibition of Chk1 alone could not increase or completely block the extrusion of PB1 like Chk1/2 inhibition. Also, Chk1/2 inhibition resulted in defective meiotic spindle organization and chromosome condensation both in MI and metaphase II (MII) stages of oocytes. The location of γ-tubulin and Securin were abnormal or missing, while P38 MAPK was activated by Chk1/2 inhibition. Meanwhile, Chk1/2 inhibition reduced the percentage of the second polar body extrusion and pronuclear formation. In conclusion, our results further understand the functions and regulatory mechanism of Chk1/2 during oocyte meiotic maturation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

SAA1 is transcriptionally activated by STAT3 and accelerates renal interstitial fibrosis by inducing endoplasmic reticulum stress

Renal interstitial fibrosis (RIF) is the common irreversible pathway by which chronic kidney disease (CKD) progresses to the end stage. The transforming growth factor-β (TGF-β)/signal transducer and activator of transcription 3 (STAT3) signaling pathway is a common factor leading to inflammation-mediated RIF, but its downstream regulatory mechanism is still unclear. Bioinformatics analysis predicted that serum amyloid A protein 1 (SAA1) was one of the target genes for transcriptional activation of STAT3 signaling. As an acute phase reaction protein, SAA1 plays an important role in many inflammatory reactions, and research has suggested that SAA1 is significantly elevated in the serum of patients with CKD. In this research, multiple experiments were performed to investigate the role of SAA1 in the process of RIF. SAA1 was abnormally highly expressed in kidney tissue from individuals who underwent unilateral ureteral obstruction (UUO) and TGF-β-induced HK2 cells, and the abnormal expression was directly related to the transcriptional activation of STAT3. Additionally, SAA1 can directly target and bind valosin-containing protein (VCP)-interacting membrane selenoprotein (VIMP) to inhibit the function of the Derlin-1/VCP/VIMP complex, preventing the transportation and degradation of the misfolded protein, resulting in endoplasmic reticulum (ER) stress characterized by an increase in glucose-regulated protein 78 (GRP78) levels and ultimately promoting the occurrence and development of RIF.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Enhancing Extreme Precipitation Predictions With Dynamical Downscaling: A Convection‐Permitting Modeling Study in Texas and Oklahoma

Precipitation in the Southern Plains of the United States is relatively well depicted by the Community Earth System Model (CESM). However, despite its ability to capture seasonal mean precipitation anomalies, CESM consistently underestimates extreme pluvial and drought events, rendering it an insufficient tool for extending simulation lead times for exceptional events, such as the abnormally dry May 2011, which helped drive Texas into its worst period of drought in more than a century, and the abnormally wet May 2015, which led to widespread flooding in that state. Ensemble‐based regional climate experiments are completed for the two extreme years using Weather Research and Forecasting model (WRF) and downscaled from CESM. WRF simulations are at convection‐permitting grid resolution for improved physical representation of simulated precipitation over the Southern Great Plains. By integrating convection‐permitting models (CPMs) into each individual member of a CESM ocean data assimilation ensemble, this study demonstrates that high‐resolution dynamical downscaling can improve model skillfulness at capturing these two events and is thus a potentially useful tool for forecasting extremely high and extremely low precipitation events at subseasonal or even seasonal lead times.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Potential design problems for ITER fusion device

The international thermonuclear experimental reactor (ITER) is a worldwide project currently being built in France for the demonstration of the feasibility of thermonuclear technologies for future realization of successful commercial fusion energy. ITER is of the tokamak based design using strong magnetic fields to confine the very hot plasma needed to induce the fusion reaction. Tokamak devices are currently the front leading designs. Building a successful magnetic fusion device for energy production is of great challenge. A key obstacle to such design is the performance during abnormal events including plasma disruptions and so-called edge-localized modes (ELMs). In these events, a massive and sudden release of energy occurs quickly, due to loss of full or partial plasma confinement, leading to very high transient power loads on the reactor surface boundaries. A successful reactor design should tolerate several of these transient events without serious damages such as melting and vaporization of the structure. This paper highlights, through comprehensive state-of-the-art computer simulation of the entire ITER interior design during such transient events, e.g., ELMs occurring at normal operation and disruptions during abnormal operation, potential serious problems with current plasma facing components (PFCs) design. The HEIGHTS computer package is used in these simulations. The ITER reactor design was simulated in full and exact 3D geometry including all known relevant physical processes involved during these transient events. The current ITER divertor design may not work properly and may requires significant modifications or new innovative design to prevent serious damage and to ensure successful operation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

New proposed ITER divertor design using carbon insert on tungsten to mitigate ELMs and secondary radiation effects on nearby components

Abstract Building a successful device for the magnetic fusion energy production is a great challenge. ITER is an international project of the tokamak based magnetic fusion design being developed for the demonstration of the feasibility of thermonuclear technologies for future realization of successful commercial fusion energy. A key obstacle to a successful magnetic fusion energy production is however, the performance during abnormal events including plasma disruptions and edge-localized modes (ELMs). A credible reactor design must tolerate at least a few of these transient events without serious consequences such as melting of the structure. This paper investigates and compares the performance of the current ITER tokamak design during two types of transient events, i.e., ELMs occurring at normal operation and disruptions during abnormal operation. We simulated the divertor components response using our integrated 3D HEIGHTS package. The simulations include self-consistent modeling of the interaction of the released core plasma particles with the initial solid divertor material, energy deposition processes, vaporization of divertor material, secondary plasma formation and MHD evolution, incident core particles collisions and scattering from this dense secondary plasma, photon radiation of secondary plasma, and the resulting heat loads on nearby components. Our simulations showed that using a small carbon insert around the strike point can significantly reduce the overall expected damage on the tungsten dome structure, reflector plates, and prevent tungsten vaporization and its potential core plasma contamination.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Prevalence of Self-Reported Voice Concerns and Associated Risk Markers in a Nonclinical Sample of Military Service Members

Introduction: Difficult communication environments are common in military settings, and effective voice use can be critical to mission success. This study aimed to estimate the prevalence of self-reported voice disorders among U.S. military service members and to identify factors that contribute to their voice concerns. Method: A nonclinical sample of 4,123 active-duty service members was recruited across Department of Defense hearing conservation clinics. During their required annual hearing evaluation, volunteers provided responses to voice-related questions including a slightly adapted version of the Voice Handicap Index-10 (VHI-10) as part of a larger survey about communication issues. Changepoint detection was applied to age and years of service to explore cohort effects in the reporting of voice concerns. Logistic regression analyses examined multiple available factors related to communication to identify factors associated with abnormal results on the VHI-10. Results: Among the respondents, 41% reported experiencing vocal hoarseness or fatigue at least several times per year, and 8.2% ( n = 336) scored above the recommended abnormal cut-point value of 11 on the VHI-10. Factors independently associated with the greatest risk for self-reported voice concerns were sex (female), cadmium exposure, vocal demands (the need for a strong, clear voice), and auditory health measures (frequency of experiencing temporary threshold shifts; self-reported hearing difficulties). Conclusions: Based on self-reported voice concerns and false negative rates reported in the literature, the prevalence of dysphonia in a large sample of active-duty service members is estimated to be 11.7%, which is higher than that in the general population. Certain predictors for voice concerns were expected based on previous literature, like female sex and voice use, but frequency of temporary threshold shifts and exposure to cadmium were surprising. The strong link between voice and auditory problems has particular implications regarding the need for effective communication in high-noise military and other occupational environments.

Audiology & Speech-Language Pathology↗
DOE OSTI2022

Excited states of lutetium oxide and its singly charged cation

Vibronic spectra of lutetium oxide (LuO) seeded in supersonic molecule beams are investigated with mass-analyzed threshold ionization (MATI) spectroscopy and second-order multiconfigurational quasi-degenerate perturbation (MCQDPT2) theory. Six states of LuO and four states of LuO + are located by the MCQDPT2 calculations, and an a 3 Π(LuO + ) ← C 2 Σ + (LuΟ) transition is observed by the MATI measurement. Finally, the vibronic spectra show abnormal vibrational intervals for both the neural and cation excited states, and the abnormality is attributed to vibrational perturbations induced by interactions with neighboring states.

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

Efficient generation of bone morphogenetic protein 15-edited Yorkshire pigs using CRISPR/Cas9†

Abstract Bone morphogenetic protein 15 (BMP15), a member of the transforming growth factor beta (TGF-β) superfamily, plays an essential role in ovarian follicular development in mono-ovulatory mammalian species. Studies using a biallelic knockout mouse model revealed BMP15 potentially has just a minimal impact on female fertility and ovarian follicular development in poly-ovulatory species. In contrast, our previous study demonstrated that in vivo knockdown of BMP15 significantly affected porcine female fertility, as evidenced by the dysplastic ovaries containing significantly decreased numbers of follicles and an increased number of abnormal follicles. This finding implied that BMP15 plays an important role in the regulation of female fertility and ovarian follicular development in poly-ovulatory species. To further investigate the regulatory role of BMP15 in porcine ovarian and follicular development, here, we describe the efficient generation of BMP15-edited Yorkshire pigs using CRISPR/Cas9. Using artificial insemination experiments, we found that the biallelically edited gilts were all infertile, regardless of different genotypes. One monoallelically edited gilt #4 (Δ66 bp/WT) was fertile and could deliver offspring with a litter size comparable to that of wild-type gilts. Further analysis established that the infertility of biallelically edited gilts was caused by the arrest of follicular development at pre-antral stages, with formation of numerus structurally abnormal follicles, resulting in streaky ovaries and the absence of obvious estrous cycles. Our results strongly suggest that the role of BMP15 in non-rodent poly-ovulatory species may be as important as that in mono-ovulatory species.

Shi, Xuan↗
DOE OSTI2022

Chlamydomonas CHT7 is involved in repressing DNA replication and mitotic genes during synchronous growth

In the green alga Chlamydomonas reinhardtii, regulation of the cell cycle in response to external cues is critical for survival in a changing environment. The loss of the nuclear COMPROMISED HYDROLYSIS OF TRIACYLGLYCEROLS 7 (CHT7) protein affects the expression of many genes especially in response to nitrogen availability. Cells lacking CHT7 exhibit abnormal cell morphology following nitrogen deprivation and fail to resume normal cell division after N resupply. To investigate the function of CHT7 in the regulation of cell cycle-related pathways, cells were synchronized, and RNA-seq analysis was performed during various stages of the cell cycle. In the cht7 mutant following nitrogen deprivation, the cells were not dividing, but a subset of cell cycle genes involved in DNA replication and mitosis were found to be derepressed, suggesting that the CHT7 protein plays a role in cell cycle regulation that is opposite to that of the mitotic cyclin-dependent kinases. Furthermore, genes for cell wall synthesis and remodeling were found to be abnormally induced in nondividing cht7 cells; this misregulation may deplete cellular resources and thus contribute to cell death following nitrogen deprivation. Lastly, 43 minimally characterized kinases were found to be highly misregulated in cht7. Further analysis suggested that some of these CHT7-regulated kinases may be related to the MAP3K and Aurora-like kinases, while others are unique. Together, these results suggest a role of CHT7 in transcriptional regulation of the cell cycle and reveal several pathways and genes whose expression appears to be subject to a CHT7-mediated regulatory network.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Spatio-temporal control of phenylpropanoid biosynthesis by inducible complementation of a cinnamate 4-hydroxylase mutant

Abstract Cinnamate 4-hydroxylase (C4H) is a cytochrome P450-dependent monooxygenase that catalyzes the second step of the general phenylpropanoid pathway. Arabidopsis reduced epidermal fluorescence 3 (ref3) mutants, which carry hypomorphic mutations in C4H, exhibit global alterations in phenylpropanoid biosynthesis and have developmental abnormalities including dwarfing. Here we report the characterization of a conditional Arabidopsis C4H line (ref3-2pOpC4H), in which wild-type C4H is expressed in the ref3-2 background. Expression of C4H in plants with well-developed primary inflorescence stems resulted in restoration of fertility and the production of substantial amounts of lignin, revealing that the developmental window for lignification is remarkably plastic. Following induction of C4H expression in ref3-2pOpC4H, we observed rapid and significant reductions in the levels of numerous metabolites, including several benzoyl and cinnamoyl esters and amino acid conjugates. These atypical conjugates were quickly replaced with their sinapoylated equivalents, suggesting that phenolic esters are subjected to substantial amounts of turnover in wild-type plants. Furthermore, using localized application of dexamethasone to ref3-2pOpC4H, we show that phenylpropanoids are not transported appreciably from their site of synthesis. Finally, we identified a defective Casparian strip diffusion barrier in the ref3-2 mutant root endodermis, which is restored by induction of C4H expression.

Plant Sciences↗
DOE OSTI2020

The Human Phenotype Ontology in 2021

The Human Phenotype Ontology (HPO, https://hpo.jax.org) was launched in 2008 to provide a comprehensive logical standard to describe and computationally analyze phenotypic abnormalities found in human disease. The HPO is now a worldwide standard for phenotype exchange. The HPO has grown steadily since its inception due to considerable contributions from clinical experts and researchers from a diverse range of disciplines. Here, we present recent major extensions of the HPO for neurology, nephrology, immunology, pulmonology, newborn screening, and other areas. For example, the seizure subontology now reflects the International League Against Epilepsy (ILAE) guidelines and these enhancements have already shown clinical validity. We present new efforts to harmonize computational definitions of phenotypic abnormalities across the HPO and multiple phenotype ontologies used for animal models of disease. These efforts will benefit software such as Exomiser by improving the accuracy and scope of cross-species phenotype matching. The computational modeling strategy used by the HPO to define disease entities and phenotypic features and distinguish between them is explained in detail. We also report on recent efforts to translate the HPO into indigenous languages. Finally, we summarize recent advances in the use of HPO in electronic health record systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Kensor: Coordinated Intelligence from Co-Located Sensors

Internet of Things (IoT) is becoming more pervasive in many installations, including homes, manufacturing plants, and industrial facilities of all kinds. The data that IoT produces is a reflection of usual behavior such as daily routines and scheduled tasks, but also from unexpected behavior due to unintentional or undesirable abnormalities. Here, we focus on achieving coordinated intelligence about normal and abnormal phenomena from multiple sensors that are geographically colocated in close proximity, monitoring and controlling a set of co-located devices. Given a set of co-located sensors, we seek an intelligent approach that would automatically determine the “normal” patterns of behaviors among the correlated sensors. After normal behavior is extracted, later monitoring should detect any deviant variations over time. An example application is an entry monitoring and alert system for facilities such as nuclear reactors, where badge readers, door locks, lights, weight trackers and other co-located sensors at the entry point are collectively tracked. To address this problem, we identify the possible solution approach that can be used to solve its different variants. The implemented model is developed as a combination of rules and Markov Chain methods.

Kotevska, Olivera↗
DOE OSTI2021

Intelligent Prediction of States in Multi-port Autonomous Reconfigurable Solar power plant (MARS)

In power electronics, prediction of states may be used for identification of faults, determination of aging of components, identification of bad data measurements, among others. Prediction of states in power electronics have broadly been based on: (a) physics-based models, (b) data-driven models, and (c) hybrid models. In this paper, data-driven approaches are presented for intelligent prediction of states in multi-port autonomous reconfigurable solar power plant (MARS) and compared. The data-set needed to train the data-driven models based on artificial intelligence (AI) algorithms has been identified and the trained models are evaluated under different extrapolated normal and abnormal operating conditions. The AI algorithms include nonlinear auto-regressive exogenous model (NARX), spiking neural networks (SNN), and decision tree. The models are compared and contrasted. The best model (NARX) is evaluated under different normal and abnormal operating conditions that have indicated accurate prediction.

Debnath, Suman↗
DOE OSTI2020

Smart Inverters for Seamless Reconnection of Isolated Residential Microgrids to Utility Grid

This paper proposes an approach to achieve seamless reconnection of isolated residential microgrids to utility grid. Any abnormal condition on the grid side results in isolating the residential microgrid from utility grid, and giving the full responsibility of supplying household loads to local distributed generation (DG) units. However, after resolving the abnormal condition on the grid side, the residential microgrid needs to seamlessly reconnect to the main grid. To this end, a seamless transition algorithm is presented which monitors the system condition in real time, and coordinates the operation of all inverter-based DG units in residential microgrid before reconnection to the main grid. A modified control scheme is proposed for single-phase inverters which turns them into smart inverters enable to interact with seamless transition algorithm. The proposed approach synchronizes each phase voltage with its respective grid-side voltage in order to seamlessly reconnect the residential microgrid to the main grid. Case study results are carried out in PSCAD/EMTDC environment to verify the validity of proposed method.

Pilehvar, Mohsen S.↗
DOE OSTI2024

PMU Data Quality and Sensor Health Monitoring

Phasor Measurement Units (PMUs) play a critical role in the evolution of the electric power industry by providing high-precision, real-time monitoring of essential power system metrics. However, effectively detecting abnormalities and critical events from PMU data is a complex task, complicated by intricate temporal patterns, a scarcity of labeled data for training algo- rithms, and constraints on online computational power. In this study, we apply TranAD, an innovative algorithm that combines transformer architectures with the refinement of adversarial learning, to both synthetic and real-world PMU datasets for developing a data quality and sensor online health monitoring platform for utilities. Our findings reveal that TranAD not only provides efficient detection and localization but also enhances the detail with which abnormalities are detected, marking a a significant step forward in the field of clean data acquisition processes for power system monitoring

deep neural network, machine learning (ML)↗
DOE OSTI2024

Developing IEEE Std 2800-Compliant Algorithms for Transmission-Connected Inverter-Based Resources

This study addresses the compliance of Inverter-based Resources (IBRs) with IEEE Standard 2800, a leading standard that defines interconnection and interoperability requirements for IBRs integrated into transmission systems. Focusing on abnormal grid scenarios, the research evaluates the specific demands on IBRs, proposing a controller development framework for abnormal grid conditions. This framework caters to maintaining ride-through operation in line with IEEE Std 2800, alongside managing currents during voltage ride-through scenarios. The effectiveness of this proposed controller frame-work is rigorously validated through case studies, employing a MATLAB/Simulink model of an IBR to test its performance under diverse grid fault conditions, ensuring the IBRs' alignment with standard requirements and their robust performance in enhancing grid reliability.

IEEE Std 2800↗
DOE OSTI2021

Robust Deep Gaussian Process-Based Probabilistic Electrical Load Forecasting Against Anomalous Events

The abnormal events, such as the unprecedented COVID-19 pandemic, can significantly change the load behaviors, leading to huge challenges for traditional short-term forecasting methods. This article proposes a robust deep Gaussian processes (DGP)-based probabilistic load forecasting method using a limited number of data. Since the proposed method only requires a limited number of training samples for load forecasting, it allows us to deal with extreme scenarios that cause short-term load behavior changes. In particular, the load forecasting at the beginning of abnormal event is cast as a regression problem with limited training samples and solved by double stochastic variational inference DGP. The mobility data are also utilized to deal with the uncertainties and pattern changes and enhance the flexibility of the forecasting model. The proposed method can quantify the uncertainties of load forecasting outcomes, which would be essential under uncertain inputs. Extensive comparison results with other state-of-the-art point and probabilistic forecasting methods show that our proposed approach can achieve high forecasting accuracies with only a limited number of data while maintaining the excellent performance of capturing the forecasting uncertainties.

anomalous events↗