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At least 613 records · Page 34

The direct and indirect drivers shaping RNA viral communities in grassland soil

Recent studies have revealed diverse RNA viral communities in soils. Yet, how environmental factors influence soil RNA viruses remains largely unknown. Here, we recovered RNA viral communities from 24 metatranscriptomes sequenced from grassland soils managed under a range of environmental conditions including 1) water content: 100% and 25% water holding capacity, 2) plant presence: planted with tall wheatgrass (Thinopyrum ponticum) and bare soil, 3) cultivar type: Alkar and Jose, and 4) soil depth: 0-5 cm and 15-25 cm. The recovered RNA viral communities were novel with nearly one-third of the RNA viral contigs uniquely detected in the studied grassland. The classified RNA viral contigs are mostly known as eukaryotic RNA viruses (74.7%) belonging to Phyla Duplornaviricota, Kitrinoviricota, Lenarviricota, and Pisuviricota. Eukaryotic RNA viruses of Family Mitoviridae as well as their natural hosts, Fungi, are one of the most dominant taxa. Consistent with the results of nonmetric multidimensional scaling analysis, the four environmental conditions (water content, plant presence, cultivar, and soil depth) significantly influence the assemblages of soil RNA viral communities as suggested by the correlation analysis and the random forest algorithm. The modularity analysis of the factor network and the structural equation modeling further support the hierarchical associations among the four environmental factors and the community factors representing the co-existing eukaryotic, prokaryotic, and RNA viral communities. The soil water content, plant presence, and type of cultivar demonstrate a significant positive impact on eukaryotic RNA viral richness directly as well as indirectly on eukaryotic RNA viral abundance via influencing the co-existing eukaryotic members in this soil. Our data also provide statistical support for the negative influence of soil depth on soil eukaryotic richness and abundances resulting in its indirect impact on soil eukaryotic RNA viral communities. This study provides field-relevant information on how environmental and community factors collectively shape soil RNA communities and contribute to ecological understanding of RNA viral survival under various environmental conditions and virus-host interactions in soil.

Wu, Ruonan↗

SU-E-T-131: Artificial Neural Networks Applied to Overall Survival Prediction for Patients with Periampullary Carcinoma

Purpose: Artificial neural networks (ANN) can be used to discover complex relations within datasets to help with medical decision making. This study aimed to develop an ANN method to predict two-year overall survival of patients with peri-ampullary cancer (PAC) following resection. Methods: Data were collected from 334 patients with PAC following resection treated in our institutional pancreatic tumor registry between 2006 and 2012. The dataset contains 14 variables including age, gender, T-stage, tumor differentiation, positive-lymph-node ratio, positive resection margins, chemotherapy, radiation therapy, and tumor histology.After censoring for two-year survival analysis, 309 patients were left, of which 44 patients (∼15%) were randomly selected to form testing set. The remaining 265 cases were randomly divided into training set (211 cases, ∼80% of 265) and validation set (54 cases, ∼20% of 265) for 20 times to build 20 ANN models. Each ANN has one hidden layer with 5 units. The 20 ANN models were ranked according to their concordance index (c-index) of prediction on validation sets. To further improve prediction, the top 10% of ANN models were selected, and their outputs averaged for prediction on testing set. Results: By random division, 44 cases in testing set and the remaining 265 cases have approximately equal two-year survival rates, 36.4% and 35.5% respectively. The 20 ANN models, which were trained and validated on the 265 cases, yielded mean c-indexes as 0.59 and 0.63 on validation sets and the testing set, respectively. C-index was 0.72 when the two best ANN models (top 10%) were used in prediction on testing set. The c-index of Cox regression analysis was 0.63. Conclusion: ANN improved survival prediction for patients with PAC. More patient data and further analysis of additional factors may be needed for a more robust model, which will help guide physicians in providing optimal post-operative care. This project was supported by PA CURE Grant.

60 APPLIED LIFE SCIENCES↗

Low Risk of Development of a Regional Recurrence After an Unsuccessful Repeat Sentinel Lymph Node Biopsy in Patients with Ipsilateral Breast Tumor Recurrence

Background: Unlike sentinel lymph node biopsy (SLNB) in the primary setting, the repeat SLNB (rSLNB) in patients with ipsilateral breast tumor recurrence (IBTR) is challenging, because it is difficult to visualize and/or harvest a sentinel lymph node in every patient. Regional treatments options and safety in terms of regional disease control after such an unsuccessful rSLNB remain unclear. This study assesses factors associated with the performance of axillary lymph node dissection (ALND) after unsuccessful rSLNB and evaluates the occurrence of regional recurrences. Methods: Data were obtained from the Sentinel Node and Recurrent Breast Cancer (SNARB) study. In 239 patients, the rSLNB was unsuccessful, of whom 60 patients underwent ipsilateral ALND. Results: A shorter time interval between primary treatment and IBTR, and a primary negative SLNB were significantly associated with a higher probability to be treated with ALND after unsuccessful rSLNB (P < 0.001). The 5-year regional-recurrence rate was 0.0% in the ALND group compared with 3.7% in the group treated without ALND (P = 0.113). Of the 179 patients treated without ALND, after a median follow-up of 5.1 years (range 0.3–13.2), 7 (3.9%) developed a regional recurrence as first event after unsuccessful rSLNB. None of the seven recurrences occurred in the ipsilateral axilla. Univariable analysis showed no factors associated with regional recurrence as first event after unsuccessful rSLNB (P > 0.05). Conclusions: The present study demonstrates that the risk of regional recurrence in patients with an IBTR and an unsuccessful rSLNB is negligible, irrespective of the use of ALND. This suggests that there is no need for additional treatment of the axilla after an unsuccessful rSLNB.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Investigation of injury/illness data at a nuclear facility. Part II

At Los Alamos National Laboratory (LANL), there are several nuclear facilities, accelerator facilities, radiological facilities, explosives sites, moderate- and high-hazard non-nuclear facilities, biosciences laboratory, etc. The Plutonium Science and Manufacturing Directorate (ADPSM) provides special nuclear material research, process development, technology demonstration, and manufacturing capabilities. ADPSM manages the LANL Plutonium Facility. Within the Radiological Control Area at TA-55 (PF-4), chemical and metallurgical operations with plutonium and other hazardous materials are performed. LANL Health and Safety Programs investigate injury and illness data. In this study, statistically significant trends have been identified and compared for LANL, ADPSM, and PF-4 injury/illness cases. A previously described output metric is used to measures LANL management progress towards meeting its operational safety objectives and goals. Timelines are used to determine trends in Injury/Illness types. Pareto Charts are used to prioritize causal factors. The data generated from analysis of Injury/Illness data have helped identify and reduce the number of corresponding causal factors.

97 MATHEMATICS AND COMPUTING↗

Charge transport studies in donor-acceptor block copolymer PDPP-TNT and PC71BM based inverted organic photovoltaic devices processed in room conditions

Diketopyrrolopyrole-naphthalene polymer (PDPP-TNT), a donor-acceptor co-polymer, has shown versatile behavior demonstrating high performances in organic field-effect transistors (OFETs) and organic photovoltaic (OPV) devices. In this paper we report investigation of charge carrier dynamics in PDPP-TNT, and [6,6]-phenyl C{sub 71} butyric acid methyl ester (PC71BM) bulk-heterojunction based inverted OPV devices using current density-voltage (J-V) characteristics, space charge limited current (SCLC) measurements, capacitance-voltage (C-V) characteristics, and impedance spectroscopy (IS). OPV devices in inverted architecture, ITO/ZnO/PDPP-TNT:PC71BM/MoO{sub 3}/Ag, are processed and characterized at room conditions. The power conversion efficiency (PCE) of these devices are measured ∼3.8%, with reasonably good fill-factor 54.6%. The analysis of impedance spectra exhibits electron’s mobility ∼2 × 10{sup −3} cm{sup 2}V{sup −1}s{sup −1}, and lifetime in the range of 0.03-0.23 ms. SCLC measurements give hole mobility of 1.12 × 10{sup −5} cm{sup 2}V{sup −1}s{sup −1}, and electron mobility of 8.7 × 10{sup −4} cm{sup 2}V{sup −1}s{sup −1}.

36 MATERIALS SCIENCE↗

Structural and functional analysis of the human cone‐rod homeobox transcription factor

Abstract The cone‐rod homeobox (CRX) protein is a critical K50 homeodomain transcription factor responsible for the differentiation and maintenance of photoreceptor neurons in the vertebrate retina. Mutant alleles in the human gene encoding CRX result in a variety of distinct blinding retinopathies, including retinitis pigmentosa, cone‐rod dystrophy, and Leber congenital amaurosis. Despite the success of using in vitro biochemistry, animal models, and genomics approaches to study this clinically relevant transcription factor over the past 25 years since its initial characterization, there are no high‐resolution structures in the published literature for the CRX protein. In this study, we use bioinformatic approaches and small‐angle X‐ray scattering (SAXS) structural analysis to further understand the biochemical complexity of the human CRX homeodomain (CRX‐HD). We find that the CRX‐HD is a compact, globular monomer in solution that can specifically bind functional cis‐regulatory elements encoded upstream of retina‐specific genes. This study presents the first structural analysis of CRX, paving the way for a new approach to studying the biochemistry of this protein and its disease‐causing mutant protein variants.

59 BASIC BIOLOGICAL SCIENCES↗

Multibody Based Digital Astronaut Dynamics Simulation

BACKGROUND: This study provides the Software, Robotics, & Simulation Division at the NASA Johnson Space Center with a verification tool for multibody dynamics simulation requiring human motion. The motivation stems from current studies of several Vibration Isolation & Stabilization(VIS)system designs that attenuate the moments and forces which would be transmitted to a spacecraft during an exercise. A multibody dynamics model for a proposed VIS was available previously[1], therefore modeling of the VIS was not needed for this work. The interest here is in creating the multibody dynamics model of an astronaut in motion which may be utilized independently or while attached to a mechanism. An existing simulation [2] that utilizes OpenSim [3,4] and an in-house multibody dynamics package (MBDyn) [5] is used in order to verify the astronaut model. The main advantage this model will have over the existing simulation is that everything will be processed in one tool. METHODS AND RESULTS: Creating the simulation required; estimation of Body Segment Inertial Parameters (BSIP),a multibody model of the human-VIS system, joint acceleration profiles, and input files for MBDyn, which is used for this analysis. The scaling factors provided by Dumas et al. [6] are utilized in estimating the BSIP. Anthropometric data are used for estimating these parameters, the Anthropometric Survey of US Army Personnel (ANSUR II) [7] was the source. The astronaut model consists of 15 bodies, 14 joints and 32 degrees of freedom, with the dynamics topology generated using the center of mass locations and anthropometric data. MBDyn has an option for prescribed joint motion (PJM), which requires joint acceleration data as input. The joint angle data is first obtained from a motion capture system and then processed through code that has been created to generate approximate joint acceleration profiles. The topology tree for the astronaut model begins at the right foot up to the pelvis where there is one branch for going down the left leg and another for the torso. The torso branch leads to branches for the arms and a leaf body for the head/neck segment. For attachment to the VIS, the heel of the right foot is connected to the VIS platform through a fixed joint, resembling a foot restraint. The left foot does not attach to the platform in order to prevent a system with a closed loop. Topology and symmetry of the astronaut model were verified through kinematic analysis. Further verification of the forces and moments transmitted to the VIS were verified against the existing simulation. There was a satisfactory level of agreement when testing a simple motion, for example, rocking back and forth. Full exercise motions are to be tested soon. The main outcome has been a novel application of MBDyn for biomechanics modeling that is now available for dynamic simulations involving human motion. The estimation of BSIP was another useful result of this study, requiring only 15 inputs for generating mass properties of a theoretical astronaut model. Expansion on this work is possible by going through an alternative route in obtaining the joint motion data. Instead of high-tech and often expensive motion capture systems, an individual may watch videos with high focus and at a slow motion for each individual segment in order to determine the initial and final time and angle for that specific degree of freedom. Synthetic trajectories may also be created if there is no video reference available.

F N Matari↗

Microalgae Commodities from Coal-Fired Power Plant Flue Gas CO 2 (Draft Final Report, October 1, 2015 to June 30, 2018)

The Orlando Utilities Commission (OUC) operates an approximately 900-MWe coal fired-power plant at Stanton Energy Center (SEC), which was the site for this project to develop an integrated process for microalgae utilization of flue gas CO 2 for the production of biofuels and animal feeds. Microalgae have both potentially high yields (tons biomass/acre-year) and can be used for biofuels or high value animal feeds. The high biomass yields of microalgae cultures allows efficient use of land and water resources. They can also use wastewaters, recycle fertilizers, and have lower overall greenhouse gas emissions than conventional biofuels or animal feeds. However, many technical issues and technology gaps related to large-scale algae biomass production still must be resolved before such a process can be scaled-up. In this project, techno-economic analyses (TEAs) and life cycle assessments (LCAs) were carried out, projecting the costs and impacts of large-scale algae biomass cultivation for production of biofuels and animal feeds using OUC-SEC flue gas CO 2 . In addition, 3.5-m 2 (~ 40-ft 2 ) experimental raceway ponds were used for the cultivation of microalgae at OUC-SEC and also at the University of Florida. A large-scale algae farm was designed for a 1,300-acre site (~500-ha) located near the OUC-SEC plant, consisting of 400 hectares (1,000 acres) of paddle wheel mixed raceway ponds (each 4 ha), receiving flue gas piped approximately 3 km (2 miles) from the SEC plant. In the first year of this project (Budget Period 1, BP1), the TEA and LCA studies focused on the production of biogas produced from algae biomass and its use to replace coal at the power plant. However, due to the resulting very high cost of CO 2 mitigation, the process was modified to produce compressed natural gas (‘renewable natural gas’, RNG) for transportation fuel from the biogas, in conjunction with wastewater treatment by the algae cultures. During Budget Period 2 (BP2), the TEA and LCA studies focused on the production of animal feeds by the algae farm, using fresh water and agricultural fertilizers. In this case, CO 2 mitigation costs would be entirely covered if the algal biomass could be sold at between a two to three-fold premium above soybean feed, based on a higher nutritional value for the algal biomass. In support of the above analyses, microalgae cultivation experiments were carried out for over two years during this project in small 3.5-m 2 ponds at both SEC and the University of Florida. The most important results were the demonstration at SEC of the cultivation, on flue gas CO 2 , of filamentous algae biomass, which can be harvested at much lower cost than processes required for the colloidal algae species, as currently used by almost all algal mass culture biofuels and animal feeds projects. The yield of biogas production from the algal biomass was investigated by the University of Florida, and the value of the algal biomass as animal feed was projected based on biochemical analysis of the SEC ad UF biomasses. The conclusion from TEA/LCA carried out for the biogas case in BP1 was that a 400-ha algae system producing biomethane for co-firing at OUC-SEC could generate 27,500 MWh/yr of renewable power, offsetting 28,400 Mg CO 2eq /yr, which amounted to less than 1% of the CO 2 emitted by the SEC plant. (Mg = metric ton = 1.10 short tons). The overall cost was projected at $820/Mg of CO 2eq reduction, making this process unfeasible under any possible scenario. More favorable economics were projected when the biogas was converted to higher value transportation fuel, RNG, which also would benefit from renewable fuel (RINs) and possibly other credits. However, only by combining RNG production with municipal wastewater treatment in the algal ponds would CO 2 utilization result in no net cost or even be economically beneficial (i.e., generate income to the power plant). However, in that case the amount of CO 2 utilization would be even lower than that in the biogas case, because a large fraction of the carbon required would be supplied from the wastewater and CO 2 recovered during biogas upgrading to RNG. In brief, use of power plant CO 2 emissions for algal biofuels production was not favorable, even with optimistic assumptions about biomass productivity and biogas yields. For the animal feed case, developed during BP2, algal biomass would replace soybean feeds. The same scale 400-ha algal production plant was projected to produce 26,280 Mg per year of animal feed with a utilization of 45,300 Mg flue gas CO 2 taken up by the algal biomass. However, the process would result in a projected reduction of 112,500 Mg CO 2eq emissions per year, or roughly 1.9% of OUC-SEC emissions, mainly due to the large CO 2eq emissions from conventional soybean production. A major factor in this analysis were greenhouse gas emissions from land use changes. The cost of CO 2 utilization was projected at $116/Mg if the biomass sold for the same price as soybean meal, but if sold as a premium feed (e.g., based on high omega-3 fatty acid and carotenoid content), the power plant could actually charge for the CO 2 utilized. These economic projections are sensitive to assumptions underlying the TEA and LCA models, including biomass composition and the financial models used to project CAPEX and OPEX. Further development of an algal animal feed production using coal-fired power plant flue gas CO 2 is recommended based on the TEA and LCA, as well as experimental results. The required research and development is detailed in a technology gap analysis (Section 11), which focuses on the demonstrations of the cultivation of higher value filamentous algal biomass at OUC-SEC.

01 COAL, LIGNITE, AND PEAT↗

Total Protein Content Determination of Microalgal Biomass by Elemental Nitrogen Analysis and a Dedicated Nitrogen-to-Protein Conversion Factor

Accurately determining protein content is important in the valorization of algal biomass in food, feed, and fuel markets, where these values are used for component balance calculations. Conversion of elemental nitrogen to protein is a well-accepted and widely practiced method, but depends on developing an applicable nitrogen-to-protein conversion factor. The methodology reported here covers the quantitative assessment of the total nitrogen content of algal biomass and a description of the methodology that underpins the accurate de novo calculation of a dedicated nitrogen-to-protein conversion factor.

09 BIOMASS FUELS↗

Lunar Equator Regenerative Fuel Cell System Efficiency Analysis

It is expected that future NASA mission energy storage requirements can be adequately met by regenerative fuel cells (RFCs). Aerospace RFCs are likely to package proton exchange membrane electrochemical conversion devices based on hydrogen, oxygen, and water. To optimize system designs and direct further development, the most useful system metric is round-trip efficiency (RTE). Improving RTE generally increases specific energy and reduces system mass. The following analysis models the impact of several factors on RTE for RFCs scaling from 0.1 to 50 kW. The analysis demonstrates that higher electrolyzer (EZ) operational pressure most negatively impacts both RFC RTE and specific energy. Reactant storage heating and power management losses are significant for RFCs of any scale, but solenoid valve power becomes a noticeable parasitic load for smaller RFCs. Spherical gas storage vessels benefit RTE by only 2 to 4 percentage points but increase specific energy by ~50 percent. Cryogenic reactant storage is shown to depress RTE to below 15 percent in all cases. For a given RFC scale, there is an RTE benefit to specifying larger EZs and recharging at higher rates—if the RFC can be coupled with a corresponding power source. Although fuel cell (FC) operation is less impactful on RTE than EZ factors, efficiency is maximized by sizing the FCs relatively large and keeping current density low. RFC design is a balance of many interrelated factors, but this analysis provides a starting point for difficult decisions that must be made when designing a lunar equator RFC.

regenerative fuel cell↗

Success Probability Analysis for Shuttle Based Microgravity Experiments

Presented in this report are the results of data analysis of shuttle-based microgravity flight experiments. Potential factors were identified in the previous grant period, and in this period 26 factors were selected for data analysis. In this project, the degree of success was developed and used as the performance measure. 293 of the 391 experiments in Lewis Research Center Microgravity Database were assigned degrees of success. The frequency analysis and the analysis of variance were conducted to determine the significance of the factors that effect the experiment success.

Liou, Ying-Hsin Andrew↗

The Origin of Improved Performance in Boron‐Alloyed Silicon Nanoparticle‐Based Anodes for Lithium‐Ion Batteries

Stabilizing the solid electrolyte interphase (SEI) remains a key challenge for silicon‐based lithium‐ion battery anodes. Alloying silicon with secondary elements like boron has emerged as a promising strategy to improve the cycle life of silicon anodes, yet the underlying mechanism remains unclear. To address this knowledge gap, how boron concentration influences battery performance is systematically investigated. These results show a near‐monotonic increase in cycle lifetime with higher boron content, with boron‐rich electrodes significantly outperforming pure silicon. Additionally, silicon‐boron alloy anodes exhibit nearly three times longer calendar life than pure silicon. Through detailed mechanistic analysis, alternative contributing factors are systematically ruled out, and it is proposed that improved passivation arises from a strong permanent dipole at the nanoparticle surface. This dipole, formed by undercoordinated and highly Lewis acidic boron, creates a static, ion‐dense layer that stabilizes the electrochemical interface, reducing parasitic electrolyte decomposition and enhancing long‐term stability. These findings suggest that, within the SEI framework, the electric double layer is an important consideration in surface passivation. This insight provides an underexplored parameter space for optimizing silicon anodes in next‐generation lithium‐ion batteries.

25 ENERGY STORAGE↗

Effect of Iron Phase Evolution on Copper Separation from Slag Via Coal-Based Reduction

Copper slag, a by-product of copper pyrometallurgy, inevitably contains a certain amount of copper. Oxygen-enriched smelting technologies increase the copper content in slag indirectly because of the production of higher-grade matte. The effect of iron phase evolution on the copper content in slag during the slag cleaning process in an electric furnace was investigated using the method of combining theory with experiments. Based on the analysis, the main factors that impede the separation of slag and copper/matte were determined. Subsequently, the properties of slag were analyzed after decreasing the magnetite content within the slag. The experimental results showed that decreases in magnetite content were beneficial for the separation of copper and slag because of the decrease of slag viscosity. Nevertheless, Cu-Fe alloys formed when magnetite was completely reduced to metallic iron, and the foaming slag was formed at 1250 °C. Furthermore, the distribution of copper in the reduced slags was studied in detail.

36 MATERIALS SCIENCE↗

Removable coatings: Thermal stability and decontamination of steel surfaces from 241 Am

This study presents a comparative analysis of several strippable materials for decontamination of steel surfaces from 241 Am. The strippable coatings were chosen to have a history of application, to be commercially available, easily handled and have different composition and formulation. Carbon steel and stainless steel surfaces (coupons) were utilized as the most representative industrial materials, and the experimental series were expanded to include the rusting treatment of these surfaces as it is common for decommissioned old nuclear facilities. The experiments followed the path of pre-screening of the strippable materials (easiness of application, peeling etc.), their characterization with Fourier-transform infrared (FTIR) spectroscopy and thermogravimetric analysis (TGA), decontamination factors (DF) or removal efficiencies for different types of steel surfaces, and enhancement of the removal efficiencies of the select strippable coatings via amendment with EDTA. As a result, DF and removal efficiencies for stainless steel (both pristine and with rusting treatment) are higher than for pristine carbon steel, and decontamination factors and removal efficiencies are higher for pristine than for rusted carbon steel across all the coatings. It is also shown that EDTA amendment can improve DF and removal efficiency for a strippable coating (i.e., CC Strip), however other factors should also be considered. Thus, the coating CC Strip exhibited easiness in handling and high DF (up to 97% when EDTA-amended), but its drying period was the longest among the rest of the materials and its thermal decomposition indicates on a risk of intense release of heat in case of a fire event.

36 MATERIALS SCIENCE↗

A machine learning model for predicting the minimum miscibility pressure of CO 2 and crude oil system based on a support vector machine algorithm approach

CO 2 enhanced oil recovery (EOR) is a potential way for carbon capture, utilization and storage (CCUS). Though, the effect of CO 2 injection is greatly influenced by the reservoir conditions. Typically, Minimum miscible pressure (MMP) is selected as one of the key parameters for the screening and evaluation of prospective CO 2 flooding. Conventional slim tube test is both accurate and widely accepted but it is inefficient. Existing empirical formulas for MMPs are easy to be used but have been proved inaccurate and unreliable. Machine learning-based methods have great advantages in predicting MMP. However, only predication accuracy is discussed for most models without the screening of the main control factors and further validation of the model reliability. In this paper, a new prediction model based on support vector machine (SVM) was developed for pure/impure CO 2 and crude oil system. This study was based on 147 sets of MMP data from the literature with full information on reservoir temperature, oil composition and gas composition. The main control factors were screened by several statistical methods. Unlike the conventional prediction models that verified by only prediction accuracy, learning curve and single factor control variable analysis are further validated to obtain the optimum model.

02 PETROLEUM↗

Performance optimization of CO 2 heat pump water heater

A preliminary analysis was conducted to analyze the performance of a heat pump water heater (HPWH) that uses CO 2 as the refrigerant. A model to predict the performance was developed and calibrated based on the experimental data for an existing HPWH using a CO 2 refrigerant. The calibrated model was then used to run a parametric analysis in which factors such as water supply temperature, water circulation rate, tank stratification, and condenser configuration were considered. The performance of a commercial CO 2 system was compared with that of a similar system using R-134a as the refrigerant. It was found that CO 2 HPWH performance was comparable to that of an R-134a HPWH, more so for a separated gas cooler configuration. For comparable performance, the compressor size and the tube-in-tube heat exchanger (condenser/gas cooler) size were compared for CO 2 - and R-134a-based systems. Finally, the impact of the water circulation rate on the water temperature stratification in the tank, an essential requirement for higher performance for CO 2 HPWH systems was also investigated.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

MicroRNA-140-5p attenuated oxidative stress in Cisplatin induced acute kidney injury by activating Nrf2/ARE pathway through a Keap1-independent mechanism

Oxidative stress was predominantly involved in the pathogenesis of acute kidney injury (AKI). Recent studies had reported the protective role of specific microRNAs (miRNAs) against oxidative stress. Hence, we investigated the levels of miR140-5p and its functional role in the pathogenesis of Cisplatin induced AKI. A mice Cisplatin induced-AKI model was established. We found that miR-140-5p expression was markedly increased in mice kidney. Bioinformatics analysis revealed nuclear factor erythroid 2-related factor (Nrf2) was a potential target of miR-140-5p, We demonstrated that miR-140-5p did not affect Kelch-like ECH-associated protein 1 (Keap1) level but directly targeted the 3′-UTR of Nrf2 mRNA and played a positive role in the regulation of Nrf2 expression which was confirmed by luciferase activity assay and western blot. What was more, consistent with miR140-5p expression, the mRNA and protein levels of Nrf2, as well as antioxidant response element (ARE)-driven genes Heme Oxygenase-1 (HO-1) and NAD(P)H:quinone oxidoreductase l (NQO1) were significantly increased in mice kidney tissues. In vitro study, Enforced expression of miR-140-5p in HK2 cells significantly attenuated oxidative stress by decreasing ROS level and increasing the expression of manganese superoxide dismutase (MnSOD). Simultaneously, miR-140-5p decreased lactate dehydrogenase (LDH) leakage and improved cell vitality in HK2 cells under Cisplatin-induced oxidative stress. However, HK2 cells transfected with a siRNA targeting Nrf2 abrogated the protective effects of miR-140-5p against oxidative stress. These results indicated that miR-140-5p might exert its anti-oxidative stress function via targeting Nrf2. Our findings showed the novel transcriptional role of miR140-5p in the expression of Nrf2 and miR-140-5p protected against Cisplatin induced oxidative stress by activating Nrf2-dependent antioxidant pathway, providing a potentially therapeutic target in acute kidney injury. - Highlights: • miR-140-5p expression was up-regulated in Cisplatin induced AKI. • miR-140-5p directly targeted the 3′-UTR of Nrf2 mRNA. • miR-140-5p activated the Nrf2/ARE signaling pathway and served as an early protective response against oxidative stress.

60 APPLIED LIFE SCIENCES↗

Mapping the Complete Reaction Energy Landscape of a Metal–Organic Framework Phase Transformation

Crystalline materials undergo valuable phase transformations, and the energetic processes that underlie these transformations can be fully characterized through a combination of thermodynamic and kinetic studies. Here, we report the first complete reaction energy landscape of metal–organic framework (MOF) interpenetration, specifically in the phase transformation of NU-1200 to its doubly interpenetrated counterpart, STA-26. We characterized the thermodynamics of this phase transformation by pairing experiments with density functional theory (DFT) calculations. This analysis revealed that factors such as the increase in crystal density likely drive Zr- and Hf-NU-1200 to STA-26 interpenetration, while other chemical interactions such as steric repulsions prevent Th-NU-1200 from interpenetrating. Using time-resolved in situ X-ray diffraction, we monitored phase transformation reaction profiles and extracted quantitative kinetic information using the Avrami-Erofe’ev model. As a result, we obtained activation energies for the Zr- and Hf-NU-1200 transformations to Zr- and Hf-STA-26, respectively, revealing slower phase change kinetics for MOFs with stronger bonds. Finally, we paired the kinetic data with experimental observations to classify the mechanistic model of this phase transformation as partial dissolution. Here, we anticipate that this thermodynamic, kinetic, and mechanistic understanding will broadly inform further studies on the energetics of crystallization.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗