Search NASA⌕ Search

SEARCH · Search NASA

Results for “Predictors”

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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Multiphysics analysis of fuel fragmentation, relocation, and dispersal susceptibility–Part 3: Thermal hydraulic evaluation of large break LOCA under high-burnup conditions

Increasing the peak rod average burnup of pressurized water reactor (PWR) fuel beyond 62 GWd/tU may increase fuel fragmentation, relocation, and dispersal (FFRD) susceptibility during a large break loss of coolant accident (LBLOCA). TRACE thermal hydraulic (TH) LBLOCA analyses were performed for a realistic 24-month high-burnup PWR equilibrium cycle, to inform subsequent transient BISON high-burnup FFRD susceptibility evaluations. Realistic LBLOCA systems behavior was first established by configuring to and comparing with the BEMUSE OECD LBLOCA benchmark. Fuel and operating conditions were then applied from high-burnup VERA depletion calculations. LBLOCA simulations were performed for 281 selected high-burnup rods, for which transient TH boundary conditions were collected for later use in BISON. The TRACE results indicated that rod linear heat rate (rather than burnup) is the main predictor of peak cladding temperature (PCT) during the event. PCT typically occurred at a local burnup lower than the rod-average burnup, especially for twice-burned fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

The Transient Multi-Level method for Monte Carlo reactor statics calculations

The Transient Multi-Level (TML) method is applied to a time-dependent Monte Carlo transport solver to offload some of the computational burden of the expensive Monte Carlo solve to lower-order Coarse Mesh Finite Difference (CMFD) and Exact Point Kinetics Equations (EPKE) solvers via factorization of the neutron flux at the transport and CMFD levels using the Predictor Corrector Quasi-Static Method (PCQM). The Monte Carlo transient is solved by a modified fission source iteration scheme that introduces a single transient source bank. The method is implemented in the production-level Monte Carlo code, Shift, and verified with prescribed reactivity ramps from the two-dimensional version of the C5G7-TD reactor benchmark. The results show that, as compared to other quasi-static methods, the TML reduces the stochastic noise inherent to the transient Monte Carlo solver by factors of ~2 to 6 for various norm comparisons of the reactor power amplitude. Finally, the TML additionally reduces the number of Monte Carlo evaluations needed to simulate the transient, leading to roughly an order of magnitude improvement in CPU time relative to the standard PCQM for the problems tested.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

A regression-based approach to estimating retrofit savings using the Building Performance Database

Retrofitting building systems is known to provide cost-effective energy savings. This article addresses how the Building Performance Database is used to help identify potential savings. Currently, prioritizing retrofits and computing their expected energy savings and cost/benefits can be a complicated, costly, and an uncertain effort. Prioritizing retrofits for a portfolio of buildings can be even more difficult if the owner must determine different investment strategies for each of the buildings. Meanwhile, we are seeing greater availability of data on building energy use, characteristics, and equipment. These data provide opportunities for the development of algorithms that link building characteristics and retrofits empirically. In this paper we explore the potential of using such data for predicting the expected energy savings from equipment retrofits for a large number of buildings. We show that building data with statistical algorithms can provide savings estimates when detailed energy audits and physics-based simulations are not cost- or time-feasible. We develop a multivariate linear regression model with numerical predictors (e.g., operating hours, occupant density) and categorical indicator variables (e.g., climate zone, heating system type) to predict energy use intensity. The model quantifies the contribution of building characteristics and systems to energy use, and we use it to infer the expected savings when modifying particular equipment. We verify the model using residual analysis and cross-validation. We demonstrate the retrofit analysis by providing a probabilistic estimate of energy savings for several hypothetical building retrofits. We discuss the ways understanding the risk associated with retrofit investments can inform decision making. The contributions of this work are the development of a statistical model for estimating energy savings, its application to a large empirical building dataset, and a discussion of its use in informing building retrofit decisions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Load response of a floating wind turbine to turbulent atmospheric flow

The two turbulence-generation models [Kaimal Spectrum Exponential Coherence (KSEC) and Mann] specified in the international standard for wind turbine design assume neutral atmospheric conditions and are based on statistical and spectral methods. Mainly due to the lack of physics, the flow fields simulated with these models ultimately differ in their underlying structure, especially in terms of the spatial coherence of longitudinal velocity perturbations. While this may not be critical for smaller wind turbine rotors, it becomes important when rotor sizes increase. Furthermore, it might be especially important in the context of floating technologies as they are more sensitive to large turbulent coherent structures. Previous work found that these differences between KSEC and Mann can propagate to loads predictions and thereby affect the design space of the entire wind turbine system. It is therefore crucial to determine in which ways these two models are underperforming. Up until now, validation of these models had only been done in the vertical direction because it is extremely difficult to obtain atmospheric turbulence measurements separated laterally, and sampled at heights relevant to wind energy. In this work, we address the lack of measurements by using high-fidelity, high-resolution simulation data as a reference. We perform hour-long, large-eddy simulations of turbulent velocity fields that are stability-dependent and contain three-dimensional coherent structures. These flow fields are then used to investigate which stochastic model is a better predictor of loads on a realistic spar-system floating offshore wind turbine, and to quantify how the assumption of neutral stratification propagates to short-term load estimates. Both stochastic turbulence models are found to overpredict fatigue loading in high-wind scenarios (in some cases, by more than 25%) and underpredict it when the wind speed is low (by as much as 20%). The KSEC model matches the high-fidelity flow fields more closely than Mann at high wind speeds, and the opposite is true at low wind speeds. Finally, turbine loading is found to be sensitive to atmospheric stability even when the turbulence intensity remains fairly constant. This sensitivity is most pronounced at low wind speeds, when fatigue load estimates on the spar system can differ by 40%.

17 WIND ENERGY↗
DOE OSTI2022

Convolutional neural networks for intra-hour solar forecasting based on sky image sequences

Accurate and timely solar forecasts play an increasingly critical role in power systems. Compared to longer forecasting timescales, very short-term solar forecasting has lagged behind in both research and practice. In this paper, we propose deep convolutional neural networks (CNNs) to provide operational intra-hour (10-minute-ahead to 60-minute-ahead) solar forecasts. We develop two CNN structures inspired by a widely-used CNN architecture. The CNNs are tailored to our solar forecasting regression tasks and rely solely on sky image sequences. Case studies based on six years of data (over 150,000 data points) demonstrate that the best CNN model has forecast skill scores of 20%-39% over the naive persistence of cloudiness benchmark, even at these very short timescales. The CNNs also have consistently superior performance when compared to shallow machine learning models with meteorological predictors, where the improvement averages around 7%. The sensitivity analyses show that the sky image length, resolution, and weather conditions have impacts on the deep learning model accuracy. In our intra-hour problem with specific setups, two sky images with a 10-minute 128 x 128 resolution yield the most accurate forecasts. Current limitations, future work, and deployment challenges and solutions are also discussed.

14 SOLAR ENERGY↗
DOE OSTI2022

Dispatch optimization of a concentrating solar power system under uncertain solar irradiance and energy prices

The integration of thermal energy storage into a concentrating solar power system allows for mitigating some of the risk associated with uncertain solar irradiance and uncertain energy prices. We solve a 48 h dispatch optimization model with continually updated conditional point forecasts of both direct normal irradiance (DNI) and electricity prices with a rolling-horizon scheme at hourly resolution over the course of a year. Joint, conditional forecasts for DNI and prices are formed using an autoregressive moving-average time series model with exogenous weather predictors. We guide dispatch using a mixed-integer programming model, but in order to evaluate performance we use the System Advisor Model (SAM) of the National Renewable Energy Laboratory. SAM is a techno-economic simulation model that accounts for plant thermodynamics with higher fidelity. Our conditional DNI forecasts improve annual revenue by 4%–12% over using historical forecasts based on data from previous years. Conditional price forecasts improve annual revenue by 6%–19% in the real-time market over analogous historical forecasts. Updating these forecasts every six hours, rather than every 24 h, further improves annual revenue by 5%–6%. Here, we also investigate a method that values terminal inventory in our dispatch optimization model, again when used in a rolling-horizon scheme.

14 SOLAR ENERGY↗
DOE OSTI2016

CO 2 solubility in aqueous solutions containing Na + , Ca 2+ , Cl - , SO 4 2- and HCO 3 - : The effects of electrostricted water and ion hydration thermodynamics

Dissolution of CO 2 into deep subsurface brines for carbon sequestration is regarded as one of the few viable means of reducing the amount of CO 2 entering the atmosphere. Ions in solution partially control the amount of CO 2 that dissolves, but the mechanisms of the ion's influence are not clearly understood and thus CO 2 solubility is difficult to predict. Here in this study, CO 2 solubility was experimentally determined in water, NaCl, CaCl 2 , Na 2 SO 4 , and NaHCO 3 solutions and a mixed brine similar to the Bravo Dome natural CO 2 reservoir; ionic strengths ranged up to 3.4 molal, temperatures to 140 °C, and CO 2 pressures to 35.5 MPa. Increasing ionic strength decreased CO 2 solubility for all solutions when the salt type remained unchanged, but ionic strength was a poor predictor of CO 2 solubility in solutions with different salts. A new equation was developed to use ion hydration number to calculate the concentration of electrostricted water molecules in solution. Dissolved CO 2 was strongly correlated (R 2 = 0.96) to electrostricted water concentration. Strong correlations were also identified between CO 2 solubility and hydration enthalpy and hydration entropy. These linear correlation equations predicted CO 2 solubility within 1% of the Bravo Dome brine and within 10% of two mixed brines from literature (a 10 wt % NaCl + KCl + CaCl 2 brine and a natural Na + , Ca 2+ , Cl - type brine with minor amounts of Mg 2+ , K + , Sr 2+ and Br - ).

58 GEOSCIENCES↗
DOE OSTI2025

Reduced soil diazotroph diversity decreases nitrogen fixation rates, but depends on land management

Soil diazotrophs convert atmospheric nitrogen into plant-available ammonium through free-living nitrogen fixation (FLNF). This sustainable nitrogen source can reduce our dependence on synthetic fertilizer inputs in conventional agricultural systems. However, we know little about the effect of diazotroph diversity on FLNF, especially given that FLNF is intermediate within the broad-narrow functional spectrum. Here, we determined how management-mediated shifts in diazotroph diversity would impact their ecosystem function (FLNF) by quantifying diazotroph diversity across a long-term management gradient during and after the growing season. In addition to field observations, we leveraged the same management gradient to manipulate diversity in soil microcosms via chloroform fumigation exposure. In the field, diazotroph diversity was significantly higher after the growing season, and the biologically-based annual cropping system harbored the highest diazotroph diversity. However, perennial cropping systems maintained the highest FLNF despite lower diazotroph diversity, and both soil moisture and temperature were stronger predictors of FLNF. Based on these results, integrating diverse perennial crops into agricultural landscape could result in greater N from FLNF, particularly at the end of the growing season. When we reduced biodiversity in a manipulation experiment, the diversity-FLNF association was stronger than in the field experiment, suggesting that FLNF communities are not as functionally redundant as taxonomically ‘broad’ ecosystem functions. Here, the strength of diversity-FLNF correlation varied by previous land management. Diazotroph diversity better predicted FLNF in annual and forest soil microcosms, and microbial biomass carbon better predicted FLNF in perennial soil microcosms. Taken together, our results show that while diazotroph diversity influences FLNF, especially under extreme environmental disturbances, abiotic factors like soil moisture and temperature are stronger constraints on FLNF in the field.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

Cdc20 mediates D-box-dependent degradation of Sp100

Highlights: Black-Right-Pointing-Pointer Cdc20 is a co-activator of APC/C complex. Black-Right-Pointing-Pointer Cdc20 recruits Sp100 and mediates its degradation. Black-Right-Pointing-Pointer The D-box of Sp100 is required for Cdc20-mediated degradation. Black-Right-Pointing-Pointer Sp100 expresses consistently at both the mRNA and protein levels in cell cycle. -- Abstract: Cdc20 is a co-activator of the anaphase-promoting complex/cyclosome (APC/C complex), which recruits substrates at particular phases of the cell cycle and mediates their degradation. Sp100 is a PML-NB scaffold protein, which localizes to nuclear particles during interphase and disperses from them during mitosis, participates in viral resistance, transcriptional regulation, and apoptosis. However, its metabolism during the cell cycle has not yet been fully characterized. We found a putative D-box in Sp100 using the Eukaryotic Linear Motif (ELM) predictor database. The putative D-box of Sp100 was verified by mutational analysis. Overexpression of Cdc20 resulted in decreased levels of both endogenous Sp100 protein and overexpressed Sp100 mRNA in HEK 293 cells. Only an overexpressed D-box deletion mutant of Sp100 accumulated in HEK293 cells that also overexpressed Cdc20. Cdc20 knockdown by cdc20 specific siRNA resulted in increased Sp100 protein levels in cells. Furthermore, we discovered that the Cdc20 mediated degradation of Sp100 is diminished by the proteasome inhibitor MG132, which suggests that the ubiquitination pathway is involved in this process. However, unlike the other Cdc20 substrates, which display oscillating protein levels, the level of Sp100 protein remains constant throughout the cell cycle. Additionally, both overexpression and knockdown of endogenous Sp100 had no effect on the cell cycle. Our results suggested that sp100 is a novel substrate of Cdc20 and it is degraded by the ubiquitination pathway. The intact D-box of Sp100 was necessary for this process. These findings expand our knowledge of both Sp100 and Cdc20 as well as their role in ubiquitination.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

miR-206 is down-regulated in breast cancer and inhibits cell proliferation through the up-regulation of cyclinD2

Highlights: ► miR-206 was downexpressed in tumor samples compared with matched normal samples. ► Enhanced expression of miR-206 could inhibit breast cancer growth in vitro. ► Luciferase confirmed miR-206 functions as an anti-oncogene by targeting cyclinD2. ► A reverse correlation between miR-206 and cyclinD2 in breast cancer was found. -- Abstract: MicroRNAs act as important gene regulators in human genomes, and their aberrant expression is linked to many malignancies. Aberrant expression of miR-206 has been frequently reported in cancer studies; however, the role and mechanism of its function in breast cancer remains unclear. Quantitative real-time PCR was performed to detect the relative expression levels of miR-206 in breast cancer and normal breast tissues. Lower expression of miR-206 in breast cancer tissues was associated with larger tumour size and a more advanced clinical stage. Further in vitro observations showed that the enforced expression of miR-206 in MCF-7 breast cancer cells inhibited cell growth by blocking the G1/S transition and suppressed cell proliferation and colony formation, implying that miR-206 functions as a tumour suppressor in the progression of breast cancer. Interestingly, Luciferase assays first revealed that miR-206 inhibited cyclinD2 expression by targeting two binding sites in the 3′-untranslated region of cyclinD2 mRNA. qRT-PCR and Western blot assays verified that miR-206 reduced cyclinD2 expression at both the mRNA and protein levels. A reverse correlation between miR-206 and cyclinD2 expression was noted in breast cancer tissues. Altogether, our results identify a crucial tumour suppressive role of miR-206 in the progression of breast cancer, at least partly via up-regulation of the expression of cyclinD2, and suggest that miR-206 might be a candidate prognostic predictor or an anticancer therapeutic target for breast cancer patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

USP22 acts as an oncogene by regulating the stability of cyclooxygenase-2 in non-small cell lung cancer

The histone ubiquitin hydrolase ubiquitin-specific protease 22 (USP22) is an epigenetic modifier and an oncogene that is upregulated in many types of cancer. In non-small cell lung cancer (NSCLC), aberrant expression of USP22 is a predictor of poor survival, as is high expression of cyclooxygenase-2 (COX-2). Despite its oncogenic role, few substrates of USP22 have been identified and its mechanism of action in cancer remains unclear. Here, we identified COX-2 as a direct substrate of USP22 and showed that its levels are modulated by USP22 mediated deubiquitination. Silencing of USP22 downregulated COX-2, decreased its half-life, and inhibited lung carcinoma cell proliferation by directly interacting with and modulating the stability and activity of COX-2 through the regulation of its ubiquitination status. The findings of the present study suggest a potential mechanism underlying the oncogenic role of USP22 mediated by the modulation of the stability and activity of COX-2. - Highlights: • USP22 interacts with COX-2. • USP22 deubiquitinates and stabilizes COX-2. • USP22 is required for COX-2-mediated upregulation of prostaglandin E2.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

BLZF1 expression is of prognostic significance in hepatocellular carcinoma

BLZF1, a member of b-ZIP family, has been implicated in epigenetic regulation and Wnt/β-catenin signaling. Its expression and clinical significance in human cancers remain largely unknown. In this study, we showed that BLZF1 expression was reduced in hepatocellular carcinoma (HCC) tissues, compared to the paracarcinoma tissues, at both mRNA and protein levels. Results of immunohistochemistry revealed that BLZF1 was presented in both nuclear and cytoplasm. Decreased expression of nuclear and cytosolic BLZF1 in HCC was depicted in 68.2% and 79.2% of the 634 cases. Nuclear BLZF1 expression was significantly associated with tumor multiplicity (P = 0.048) and tumor capsule (P = 0.028), while cytosolic BLZF1 expression was correlated with serum AFP level (P = 0.017), tumor differentiation (P = 0.001) and tumor capsule (P = 0.003). Kaplan–Meier analysis indicated both nuclear and cytosolic BLZF1 expression was associated with poor overall survival. Low nuclear BLZF1 also indicated unfavorable disease-free survival and high tendency of tumor recurrence. Furthermore, multiple Cox regression analysis revealed nuclear BLZF1 as an independent factor for overall survival (Hazard Ratio (HR) = 0.827, 95% confident interval (95%CI): 0.697–0.980, P = 0.029). The prognostic value of BLZF1 was further confirmed by stratified analyses. Collectively, our data suggest BLZF1 is a novel unfavorable biomarker for prognosis of patients with HCC. - Highlights: • BLZF1 expression was much lower in HCC tissues. • Low BLZF1 expression was associated with poor outcomes in a cohort of 634 HCC patients. • Multiple Cox regression analysis indicated nuclear BLZF1 as an independent predictor for overall survival.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

p53-dependent and p53-independent anticancer activity of a new indole derivative in human osteosarcoma cells

Osteosarcoma (OS) is the most common primary malignant tumor of bone, occurring most frequently in children and adolescents. The mechanism of formation and development of OS have been studied for a long time. Tumor suppressor pathway governed by p53 gene are known to be involved in the pathogenesis of osteosarcoma. Moreover, loss of wild-type p53 activity is thought to be a major predictor of failure to respond to chemotherapy in various human cancers. In previous studies, we described the activity of a new indole derivative, NSC743420, belonging to the tubulin inhibitors family, capable to induce apoptosis and arrest of the cell cycle in the G2/M phase of various cancer cell lines. However, this molecule has never been tested on OS cell line. Here we address the activity of NSC743420 by examine whether differences in the p53 status could influence its effects on cell proliferation and death of OS cells. In particular, we compared the effect of the tested molecule on p53-wild type and p53-silenced U2OS cells, and on SaOS2 cell line, which is null for p53. Our results demonstrated that NSC743420 reduces OS cell proliferation by p53-dependent and p53-independent mechanisms. In particular, the molecule induces proliferative arrest that culminate to apoptosis in SaOS2 p53-null cells, while it brings a cytostatic and differentiating effect in U2OS cells, characterized by the cell cycle arrest in G0/G1 phase and increased alkaline phosphatase activity. - Highlights: • The indole derivative NSC743420 induces antitumor effects on osteosarcoma cells. • p53 status could drive the activity of antitumor agents on osteosarcoma cells. • NSC743420 induces cytostatic and differentiating effects on U2OS cells. • NSC743420 causes apoptosis on p53-null SaOS2 cells.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Blockade of FLT4 suppresses metastasis of melanoma cells by impaired lymphatic vessels

The metastatic spread of tumor cells via lymphatic vessels affects the relapse of tumor patients. New lymphatic vessel formation, including lymphangiogenesis, is promoted in the tumor environment. The lymphangiogenic factor VEGF-C can mediate lymphatic vessel formation and induce tumor metastasis by binding with FLT4. In melanoma, metastasis via lymphatics such as lymph nodes is one of the main predictors of poor outcome. Thus, we investigated whether blockade of FLT4 can reduce metastasis via the suppression of lymphatic capillaries. Proliferative lymphatic capillaries in melanoma were estimated by immunohistochemistry using FLT4 antibody after the injection of the FLT4 antagonist MAZ51. The numbers of tumor modules in metastasised lungs were calculated by gross examination and lymphatic related factors were examined by qRT-PCR. MAZ51 injection resulted in the suppression of tumor size and module number and the inhibition of proliferative lymphatic vessels in the intratumoral region in the lung and proliferating melanoma cells in the lung compared to those of untreated groups. Additionally, high FLT4 and TNF-alpha were detected in melanoma-induced tissue, while lymphatic markers such as VEGF-C, FLT4 and Prox-1 were significantly decreased in MAZ51 treated groups, implying that anti-lymphangiogenesis by MAZ51 may provide a potential strategy to prevent tumor metastasis in melanoma and high number of lymphatic capillaries could be used diagnosis for severe metastasis. - Highlights: • Tumor metastasis is closely involved with lymphatic vessels. • Metastatic melanoma cells rapidly migrate into lung via lymphatic vessels. • FLT4 antagonist, MAZ51 can induce impaired lymphatic endothelial cells without proliferation. • Melanoma metastasis into lung is inhibited by the suppression of FLT4-expressing lymphatic vessels, when MAZ51 treated.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

High expression of CREPT promotes tumor growth and is correlated with poor prognosis in colorectal cancer

CREPT (cell cycle-related and expression elevated protein in tumor) is highly expressed in many kinds of cancer, and has been shown to be prognostic in certain cancers. However, the clinical significance of CREPT in colorectal cancer (CRC) has not been sufficiently investigated. In this study, we examined the CREPT expression in 225 clinical CRC tissues and paired adjacent normal tissues, and analyzed the correlation between CREPT expression and other clinicopathological features. We also evaluated the biological function of CREPT both in vitro and in vivo using knockdown or overexpressing CRC cells. Our results showed that CREPT expressed in 175 of 225 (77.8%) CRC patients and the CREPT expression was significantly associated with tumor differentiation (P = 0.000), Dukes' stages (P = 0.013) and metastasis (P = 0.038). Patients with high CREPT expression tended to have shorter survival time. Multivariate analysis showed that positive CREPT expression can be used as an independent predictor for CRC prognosis. CREPT knockdown cells showed inhibited cell proliferation and arrested cell cycle, while CREPT overexpressing cells showed increased proliferation and promoted cell cycle. In addition, CREPT overexpression significantly promoted tumor growth in vivo. Mechanism study showed that CREPT may regulate cell proliferation and cell cycle through the regulation on cyclin D3, CDK4 and CDK6. - Highlights: • CREPT expression was associated with decreased overall survival in CRC. • CREPT expression is correlated with tumor progression in CRC. • Overexpression of CREPT promoted tumor growth both in vitro and in vivo.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Lnc-ATB contributes to gastric cancer growth through a MiR-141-3p/TGFβ2 feedback loop

The long noncoding RNA (lncRNA) ATB is an important regulator in human tumors. Here, we aimed to investigate the potential molecular mechanisms of lnc-ATB in gastric cancer (GC) tumorigenesis. RT-qPCR analysis was used to detect lnc-ATB expression level in 20 pairs of gastric cancer tissues and adjacent normal gastric mucosa tissues (ANTs). Moreover, the biological role of lnc-ATB was determined in vitro. We found that lnc-ATB was significantly upregulated in GC tissues compared to lnc-ATB expression in ANTs. These high lnc-ATB expression levels predicted poor prognosis in GC patients. Low levels of lnc-ATB inhibited GC cell proliferation and cell cycle arrest in vitro. Lnc-ATB was found to directly bind miR-141-3p. Moreover, TGF-β actives lnc-ATB and TGF-β2 directly binds mir-141-3p. Finally, we demonstrated that lnc-ATB fulfilled its oncogenic roles in a ceRNA-mediated manner. Our study suggests that lnc-ATB promotes tumor progression by interacting with miR-141-3p and that Lnc-ATB may be a valuable prognostic predictor for GC. In conclusion, the positive feedback loop of lnc-ATB/miR-141-3p/TGF-β2 may be a potential therapeutic target for the treatment of GC. - Highlights: • Lnc-ATB was up-regulated in GC tissue. • Knockdown of lnc-ATB inhibited proliferation and cell cycle arrest. • The positive feedback loop of lnc-ATB/miR-141-3p/TGF-β2 may be a potential therapeutic target for the treatment of GC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Prognostic significance of high YY1AP1 and PCNA expression in colon adenocarcinoma

Highlights: • YY1AP1 expression might play an important role in the tumorgenesis of colon adenocarcinoma. • YY1AP1 expression is related with colon adenocarcinoma patient M-class/distant metastasis. • High YY1AP1 indicates poor overall survival of colon adenocarcinoma patients. • Cox proportional-hazards model analysis indicated YY1AP1 as an independent predictor for overall survival. To investigate the relationship between YY1AP1 and various clinicopathological features of colon adenocarcinoma (COAD), we conducted immunohistochemical (IHC) analyses of human tissue microarrays. We found that YY1AP1 protein expression was significantly higher in tumor tissue of the colon and liver, and was significantly lower in tumor tissue of the kidney. An analysis that employed the SurvExpress database indicated that increased expression of YY1AP1 mRNA was significantly associated with the overall survival of COAD patients. To clarify the validity of YY1AP1 or PCNA as determined by the IHC analysis was performed on 59 paired samples from COAD and adjacent normal tissue. Statistically significant differences of immunoreactivity for YY1AP1 or PCNA protein expression was observed between COAD tissue and adjacent normal tissue. High protein expression levels of YY1AP1 and PCNA were also found to be significantly correlated with M-class and distant metastasis. We also determined that YY1AP1 was correlated with PCNA expression in COAD samples, and Kaplan-Meier survival curves indicated that YY1AP1 protein expression was significantly associated with poor survival. Finally, a univariate analysis demonstrated that YY1AP1 protein expression was related to YY1AP1 score, and multivariate analysis revealed that the YY1AP1 protein expression level was an independent risk factor of overall COAD survival. Taken together, our findings indicate that YY1AP1 expression plays an important role in the tumorigenesis and progression of COAD and could serve as a clinical prognostic indicator for COAD.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Long non-coding RNA OGFRP1 regulates LYPD3 expression by sponging miR-124-3p and promotes non-small cell lung cancer progression

Highlights: • The expression levels of lncRNA OGFRP1 was up-regulated in NSCLC tissues and cell lines. • Overexpression of lncRNA OGFRP1 was associated with advanced clinical features and poor prognosis in NSCLC patients. • LncRNA OGFRP1 promoted NSCLC cells proliferation, migration and invasion by regulation of miR-124-3p-LYPD3 pathway. Long noncoding RNA (OGFRP1) has been reported to be involved in the progression of non-small cell lung cancer (NSCLC). However, the expression pattern, functions and molecular mechanisms of OGFRP1 in NSCLC remains unclear. In the present study, we found that OGFRP1 expression was significantly up-regulated in both NSCLC tissues and cell lines, and the upregulation of OGFRP1 expression is a powerful predictor of advanced clinical stage, lymph nodes metastasis and poor prognosis for NSCLC patients. Loss-of-function assay indicated that knockdown of OGFRP1 inhibited proliferation, migration and invasion, and induced apoptosis in vitro. Mechanistically, OGFRP1 could directly bind to miR-124-3p and effectively act as a competing endogenous RNA (ceRNA) for miR-124-3p to promote the expression of the target gene LYPD3. Taken together, OGFRP1 contributed to progression of NSCLC at least partly through upregulating LYPD3 expression by sponging miR-124-3p, indicating that OGFRP1 may be a novel prognostic biomarker and therapeutic target in NSCLC.

60 APPLIED LIFE SCIENCES↗