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Neutral rhenium(i) tricarbonyl complexes with sulfur-donor ligands: anti-proliferative activity and cellular localization

Rhenium(I) tricarbonyl complexes are widely studied for their cell imaging properties and anticancer and anti-microbial activities, but the complexes with S-donor ligands remain relatively unexplored. A series of six fac-[Re(NN)(CO) 3 (SR)] complexes, where (NN) is 2,2'-bipyridyl (bipy) or 1,10-phenanthroline (phen), and RSH is a series of thiocarboxylic acid methyl esters, have been synthesized and characterized. Cellular uptake and anti-proliferative activities of these complexes in human breast cancer cell lines (MDA-MB-231 and MCF-7) were generally lower than those of the previously described fac-[Re(NN)(CO) 3 (OH 2 )] + complexes; however, one of the complexes, fac-[Re(CO) 3 (phen)(SC(Ph)CH 2 C(O)OMe))] (3b), was active (IC 50 ~ 10 μM at 72 h treatment) in thiol-depleted MDA-MB-231 cells. Moreover, unlike fac- [Re(CO) 3 (phen)(OH 2 )] + , this complex did not lose activity in the presence of extracellular glutathione. Taken together these properties show promise for further development of 3b and its analogues as potential anti-cancer drugs for co-treatment with thiol-depleting agents. Conversely, the stable and non-toxic complex, fac-[Re(bipy)(CO) 3 (SC(Me)C(O)OMe)] (1a), predominantly localized in the lysosomes of MDA-MB-231 cells, as shown by live cell confocal microscopy (λ ex = 405 nm, λ em = 470-570 nm). It is strongly localized in a subset of lysosomes (25 μM Re, 4 h treatment), as shown by co-localization with a Lysotracker dye. Longer treatment times with 1a (25 μM Re for 48 h) resulted in partial migration of the probe into the mitochondria, as shown by co-localization with a Mitotracker dye. These properties make complex 1a an attractive target for further development as an organelle probe for multimodal imaging, including phosphorescence, carbonyl tag for vibrational spectroscopy, and Re tag for X-ray fluorescence microscopy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Low Count and Background Radionuclides Analysis - 20488

The US Department of Energy (DOE) is often faced with the need to evaluate radionuclides at low concentrations. When site sample data are likely to be close to threshold activity concentrations of interest, then the means by which the radiochemical analysis is performed and reported is critical. This situation can occur when differentiating from zero (presence/absence) for radionuclides that do not occur naturally, close comparison with environmental background for naturally occurring radionuclides, close comparison with a risk- or dose-based threshold concentrations of interest, or even comparisons across studies. There are several analytical issues that are of concern, but the two that appear to cause incorrect decisions to be made most often involve establishing detection limits and subtracting ambient background conditions in the laboratory. These issues are not critical when radionuclide activity concentrations are large relative to thresholds of concern, but they seem to be poorly understood when it matters. When the comparisons are important and are likely to be close to a threshold of interest, then the general contract with the analytical laboratories needs to be changed so that the right or appropriate data are obtained. The concern is that important decisions are made incorrectly more often as greater scrutiny is placed on DoE's radionuclide cleanup or monitoring decisions by the public and other stakeholders. Examples are presented of problems that have been observed for different projects, both within and outside the realm of DOE and NRC remediation and radioactive waste disposal problems, and solutions are offered that should lead to better data from which important decisions need to be made. The first example is from Los Alamos National Laboratory (LANL) and involves radionuclide concentrations in soil and rock beneath LANL's Material Disposal Area (MDA) G. An initial review of the data led to a conclusion that americium and plutonium are a long way present beneath MDA G. A more thorough review of the data that accounted properly for ambient background and the detection limits that had been established led to the opposite conclusion. Another example is from the Nevada National Security Site where tritium results from one of the wells were unexpectedly high. Proper understanding and analysis of ambient background led to the conclusion that the increased concentrations were not so obvious, and that a different contract with the analytical laboratory was needed to provide more appropriate data to support a better determination. Other examples are used from regulatory review of projects in Nevada, where background levels and secular equilibrium for naturally occurring radionuclides are not established correctly because of analytical issues. The same basic issues have also been found to create difficulties analyzing historical data from the West Valley Demonstration Project. There is evidence in the data that the apparent lack of secular equilibrium where it is expected to exist is related to ambient background subtraction or other analytical issues. A final example is presented for analysis of Tc-99 in samples of depleted uranium. In this case, two different studies that were performed only three months apart provide quite different results. The US Environmental Protection Agency (EPA) established the data quality objectives (DQO) process in the mid-1980's to establish decision performance criteria for data collection. EPA guidance (EPA G-4, for example) clearly distinguishes between DQOs and measurement performance objectives (MQOs) that should be addressed for laboratory analysis of samples. The language of DQOs and MQOs has become confused over time it seems, and the subsequent effects seem to include a lack of attention to decision performance and a routine approach to measurement quality. In order to better address radionuclide sample analysis when the concentrations are close to thresholds of concern, which might be zero for some radionuclides, background for others, and risk-based thresholds for yet others, it is important that routine laboratory analysis methods are adjusted, and that the project team and the laboratory work closely together to ensure that the data meets the MQO requirements of laboratory analysis and reporting of results, and that the MQOs effectively support project-specific DQOs. This basic approach will be applied in Los Alamos in the coming year to the collection of moisture data from underneath MDA T that will be analyzed for americium and neptunium isotopes. Proper understanding of the radiochemistry methods and reporting, and of appropriate statistical methods is critical to the success of such projects, ensuring that the right decisions are made. (authors)

07 ISOTOPE AND RADIATION SOURCES↗

Alpha/beta-gated gamma–gamma spectroscopy of mixed fission products for trace analysis

This experiment demonstrated that some hard-to-detect fission products can be quantified directly from mixed fission product samples using advanced radio-emission spectroscopy techniques. A gamma/gamma coincidence detector was combined with a custom liquid scintillation counter to evaluate the benefits of alpha and beta coincident and anti-coincident analysis of mixed fission product samples. Reduction factors in the minimum detectable activity (MDA) relative to traditional gamma counting were quantified for a set of radionuclides. For isotopes like 91Y, 144Ce, 147Nd, and 153Sm MDA reductions of factors of 1-2 were observed using optimized beta thresholds. Using beta anti-coincidence counting reductions of factors 3-5 were observed for isotopes like 89Sr, 95mNb, 115Cd, and 137Cs and factors of 5-7 for isotopes like 235U using alpha coincidence counting. The selectivity of gamma/gamma coincidence and reduction in backgrounds using beta gating were also demonstrated with 136Cs and 153Sm. The improvements observed in the detection sensitivity of fission products and actinides achieved by combining time-correlated radiation signatures is significant and of value to applications such as nuclear fission physics, environmental monitoring for nuclear waste, reactor accidental releases, and nuclear forensics.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Development of 52Mn Labeled Trastuzumab for Extended Time Point PET Imaging of HER2

Abstract Purpose Due to their long circulation time in the blood, monoclonal antibodies (mAbs) such as trastuzumab, are usually radiolabeled with long-lived positron emitters for the development of agents for Positron Emission Tomography (PET) imaging. Manganese-52 ( 52 Mn, t 1/2 = 5.6 d, β + = 29.6%, E(β ave ) = 242 keV) is suitable for imaging at longer time points providing a complementary technique to Zirconium-89 ( 89 Zr, t 1/2 = 3.3 d, β + = 22.7%, E(β ave ) = 396 keV)) because of its long half-life and low positron energy. To exploit these properties, we aimed to investigate suitable bifunctional chelators that could be readily conjugated to antibodies and labeled with 52 Mn under mild conditions using trastuzumab as a proof-of-concept. Procedures Trastuzumab was incubated with S-2-(4-isothiocyanatobenzyl)-1,4,7,10-tetraazacyclododecane tetraacetic acid (p-SCN-Bn-DOTA), 1-Oxa-4,7,10-tetraazacyclododecane-5-S-(4-isothiocyantobenzyl)-4,7,10-triacetic acid (p-SCN-Bn-Oxo-DO3A), and 3,6,9,15-tetraazabicyclo[9.3.1] pentadeca-1(15),11,13-triene-4-S-(4-isothiocyanatobenzyl)-3,6,9-triacetic acid (p-SCN-Bn-PCTA) at a tenfold molar excess. The immunoconjugates were purified, combined with [ 52 Mn]MnCl 2 at different ratios, and the labeling efficiency was assessed by iTLC. The immunoreactive fraction of the radiocomplex was determined through a Lindmo assay. Cell studies were conducted in HER2 + (BT474) and HER2- (MDA-MB-468) cell lines followed by in vivo studies. Results Trastuzumab-Oxo-DO3A was labeled within 30 min at 37 °C with a radiochemical yield (RCY) of 90 ± 1.5% and with the highest specific activity of the chelators investigated of 16.64 MBq/nmol. The labeled compound was purified with a resulting radiochemical purity of > 98% and retained a 67 ± 1.2% immunoreactivity. DOTA and PCTA immunoconjugates resulted in < 50 ± 2.5% (RCY) with similar specific activity. Mouse serum stability studies of [ 52 Mn]Mn-Oxo-DO3A-trastuzumab showed 95% intact complex for over 5 days. Cell uptake studies showed higher uptake in HER2 + (12.51 ± 0.83% /mg) cells compared to HER2- (0.85 ± 0.10%/mg) cells. PET images of mice bearing BT474 tumors showed high tumor uptake that was consistent with the biodistribution (42.02 ± 2.16%ID/g, 14 d) compared to MDA-MB-468 tumors (2.20 ± 0.80%ID/g, 14 d). Additionally, both models exhibited low bone uptake of < 1% ID/g. Conclusion The bifunctional chelator p-SCN-Bn-Oxo-DO3A is promising for the development of 52 Mn radiopharmaceuticals as it was easily conjugated, radiolabeled at mild conditions, and illustrated stability for a prolonged duration both in vitro and in vivo . High-quality PET/CT images of [ 52 Mn]Mn-Oxo-DO3A-trastuzumab were obtained 14 d post-injection. This study illustrates the potential of [ 52 Mn]Mn-Oxo-DO3A for the evaluation of antibodies using PET imaging.

Omweri, James M.↗

Ultra-High Resolution Elemental/Isotopic Mass Spectrometry (m/?m> 1,000,000): Coupling of the Liquid Sampling-Atmospheric Pressure Glow Discharge with an Orbitrap Mass Spectrometer for Applications in Biological Chemistry and Environmental Analysis

Many fundamental questions of astrophysics, biochemistry, and geology rely on the ability to accurately and precisely measure the mass and abundance of isotopes. Taken a step further, the capacity to perform such measurements on intact molecules provides insights into processes in diverse biological systems. Described here is the coupling of a combined atomic and molecular (CAM) ionization source, the liquid sampling-atmospheric pressure glow discharge (LS-APGD) microplasma, with a commercially available ThermoScientific Fusion Lumos mass spectrometer. Demonstrated for the first time is the ionization and isotopically-resolved fingerprinting of a long-postulated, but never mass-spectrometrically observed, bi-metallic complex Hg:Se-cysteine. Such a complex has been implicated as having a role in observations of Hg detoxification by selenoproteins/amino acids. Demonstrated as well is the ability to mass spectrometrically-resolve the geochronologically important isobaric 87Sr and 87Rb species (?m ~ 0.3 mDa, mass resolution m/?m ? 1,700,000). The mass difference in this case reflects the beta-decay of the 87Rb to the stable Sr isotope. These two demonstrations highlight what may be a significant change in bioinorganic and atomic mass spectrometry, with impact expected across a broad spectrum of the physical, biological and geological sciences.

Hoegg, Edward D.↗

CO 2 storage site characterization using ensemble-based approaches with deep generative models

Estimating spatially distributed properties such as permeability from available sparse measurements is a great challenge in efficient subsurface CO 2 storage operations. In this paper, a deep generative model that can accurately capture complex subsurface structure is tested with an ensemble-based inversion method for accurate and accelerated characterization of CO 2 storage sites. We chose Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP) for its realistic reservoir property representation and Ensemble Smoother with Multiple Data Assimilation (ES-MDA) for its robust data fitting and uncertainty quantification capability. WGAN-GP are trained to generate high-dimensional permeability fields from a low-dimensional latent space and ES-MDA then updates the latent variables by assimilating available measurements. Several subsurface site characterization examples including Gaussian, channelized, and fractured reservoirs are used to evaluate the accuracy and computational efficiency of the proposed method and the main features of the unknown permeability fields are characterized accurately with reliable uncertainty quantification. Furthermore, the estimation performance is compared with a widely-used variational, i.e., optimization-based, inversion approach, and the proposed approach outperforms the variational inversion method in several benchmark cases. We explain such superior performance by visualizing the objective function in the latent space: because of nonlinear and aggressive dimension reduction via generative modeling, the objective function surface becomes extremely complex while the ensemble approximation can smooth out the multi-modal surface during the minimization. This suggests that the ensemble-based approach works well over the variational approach when combined with deep generative models at the cost of forward model runs unless convergence-ensuring modifications are implemented in the variational inversion.

42 ENGINEERING↗

Enhancing membrane performance for CO 2 capture from flue gas with ultrahigh MW polyvinylamine

Membranes for post-combustion CO 2 capture are required to have a high CO 2 permeance due to the limited driving force. For facilitated transport membranes synthesized with polyvinylamine (PVAm), a defect-free selective layer of <200 nm is usually required to render sufficient permeance with high CO 2 /N 2 selectivity. In order to meet such a demand through the knife-coating process, the coating solution needs to have a high viscosity at a relatively low concentration to minimize its penetration into the substrate. The demand was met by synthesizing PVAm with an ultrahigh molecular weight (MW) via inverse emulsion polymerization (IEP) in this study. Compared to solution polymerization, IEP isolates the reaction in inverse micelles suspended in a continuous organic phase, which allows excellent dissipation of the heat generated by the reaction and reduces gel formation drastically. The polymerization parameters, including monomer concentration, initiator concentration, and reaction temperature, were investigated to obtain the optimal MW of PVAm for membrane performance. As compared to solution polymerization, IEP enhanced the MW of PVAm from 1.2 to 12.7 MDa, which minimized the penetration of the coating solution into the substrate and hence the extra mass transfer resistance. The effect of MW and degree of hydrolysis of PVAm on the membrane transport properties were studied. Furthermore, by employing PVAm with a MW of 12.7 MDa to strengthen the polymer matrix, the loading of piperazine glycinate in the membrane was increased up to 85 wt.%. In conclusion, the resultant membrane achieved a CO 2 permeance of 839 GPU and a CO 2 /N 2 selectivity of 161 at the typical flue gas temperature of 57°C.

20 FOSSIL-FUELED POWER PLANTS↗

Gas-phase surface modification to control catalyst structure and yields in methane dehydroaromatization

Methane dehydroaromatization (MDA) is a promising approach for direct methane transformation to aromatics and hydrogen. The benchmark catalyst Mo/H-ZSM-5 struggles to find commercial adoption because of thermodynamically-limited yields and rapid coking on Brønsted acid and molybdenum carbide species, especially on zeolite external surfaces. Here, gas-phase atomic layer deposition (ALD) overcoats H-ZSM-5 external surfaces with SiO 2 or Al 2 O 3 . NH 3 -TPD, HRTEM, and textural properties show that these overcoats exclusively passivate zeolite external surfaces. Under MDA conditions, SiO 2 gives softer coke and increases cumulative benzene yields by 25%, while Al 2 O 3 strongly decreases yields. H 2 -TPR and UV-visible and Raman spectroscopy show how the overcoats redisperse the MoO x precatalysts, especially over multiple deactivation and isothermal oxidative regeneration cycles. Combined with 27 Al-MAS NMR, MoO x redistribution and dealumination are seen as the causes of long-term deactivation over multiple regeneration cycles, and this process continues to occur regardless of the overcoat. Altogether, the deposition of a small amount of silica on the outer surface of Mo/H-ZSM-5 reduces the formation of hard coke, which could be regenerated by milder methods such as hydrogen treatment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analysis of spin frustration in an Fe III 7 cluster using a combination of computational, experimental, and magnetostructural correlation methods

The synthesis, structure, and magnetic properties are reported for [Fe 7 O 3 (O 2 C t Bu) 9 (mda) 3 (H 2 O) 3 ] ( 1 ), where mdaH 2 is N -methyldiethanolamine. 1 was prepared from the reaction of [Fe 3 O(O 2 C t Bu) 6 (H 2 O) 3 ](NO 3 ) with mdaH 2 in a 1:~3 ratio in MeCN. The core of 1 consists of a central octahedral Fe III ion held within a non-planar Fe 6 loop by three μ 3 -O 2- and three μ 2 -RO - arms from the three mda 2- chelates. Variable-temperature dc and ac magnetic susceptibility studies revealed dominant antiferromagnetic coupling, leading to a ground state spin of S = 5 / 2 . The ground state was confirmed by a fit of magnetization data collected in the 0.1–7.0 T and 1.8–10.0 K ranges. The four Fe 2 pairwise exchange parameters ( J 1 - J 4 ) were estimated by independent methods: theoretical calculations using either broken symmetry energy differences (-46.3, -16.2, -3.9, and - 28.1 cm -1 , respectively) or Green’s function approximation methods (-41.4, -14.8, -13.2, and - 24.7 cm -1 ), and a magnetostructural correlation (MSC) previously developed for high nuclearity Fe III /O complexes (-39.5, -13.8, -6.7, and - 23.5 cm -1 ). Additionally, the J 1 - J 4 obtained from the MSC and theoretical methods were used with the program PHI to both simulate χ M T vs T as well as to serve as reasonable input values to fit the experimental data (-41.0, -11.4, -5.0, and - 27.3 cm -1 ). Analysis of the J ij led to identification of the spin frustration effects operative and the resultant spin vector alignments at each Fe III ion, thus allowing for the rationalization of the experimental ground state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Organotypic platform for studying cancer cell metastasis

Highlights: • Liver and brain slices can be stable, realistic in vitro 3D models. • Cell stiffness and adhesion to the tissue play determinant roles in cellular invasion in 3D. • MEK inhibitors can lead to increased cell stiffness and adhesion forces, and consequently reduced cancer cell invasion. • MDA-MB-231 breast cancer cells migrate faster and deeper into brain tissue compared to liver tissue. Metastasis is the leading cause of mortality in cancer patients. To migrate to distant sites, cancer cells would need to adapt their behaviour in response to different tissue environments. Thus, it is essential to study this process in models that can closely replicate the tumour microenvironment. Here, we evaluate the use of organotypic liver and brain slices to study cancer metastasis. Morphological and viability parameters of the slices were monitored daily over 3 days in culture to assess their stability as a realistic 3D tissue platform for in vitro metastatic assays. Using these slices, we evaluated the invasion of MDA-MB-231 breast cancer cells and of a subpopulation that was selected for increased motility. We show that the more aggressive invasion of the selected cells likely resulted not only from their lower stiffness, but also from their lower adhesion to the surrounding tissue. Different invasion patterns in the brain and liver slices were observed for both subpopulations. Cells migrated faster in the brain slices (with an amoeboid-like mode) compared to in the liver slices (where they migrated with mesenchymal or collective migration-like modes). Inhibition of the Ras/MAPK/ERK pathway increased cell stiffness and adhesion forces, which resulted in reduced invasiveness. These results illustrate the potential for organotypic tissue slices to more closely mimic in vivo conditions during cancer cell metastasis than most in vitro models.

60 APPLIED LIFE SCIENCES↗

Understanding the Control of Speciation of Molybdenum Oxides in MFI-Type Zeolites

Metal oxide-impregnated zeolites are employed in a wide variety of catalytic reactions, including methane dehydroaromatization (MDA). The most studied catalysts for MDA are Mo carbides supported on H-ZSM-5, formed through the carburization of Mo-oxide-loaded H-ZSM-5. A complete structural understanding of these materials has not yet been achieved, limiting the potential for rational catalyst design for improved performance. We hereby pursue experimental and theoretical investigations of these catalyst precursors to uncover rational design principles. We employ temperature-programmed oxidation and extended X-ray absorption fine-structure experiments, density functional theory calculations, and QuantEXAFS analysis to unveil Mo-oxide speciation in H-ZSM-5. Finally, we demonstrate that Mo-oxides exist within these systems as a combination of various motifs, and the relative abundance of these species is controlled through tailored preparation methods. The synergies exploited in this work may be leveraged in other related catalysts. The conclusions drawn are applicable to other relevant applications of zeolite-supported metal oxides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Deactivation of Mo/H-ZSM-5 in Microwave-Assisted and Thermal-Driven Methane Dehydroaromatization

A better understanding of catalyst deactivation is needed to improve catalyst design and performance in microwave-enhanced methane dehydroaromatization (MDA). Here, this study investigates the deactivation of a molybdenum supported H-ZSM-5 zeolite (Mo/H-ZSM-5) catalyst in MDA under microwave-heated conditions, comparing its performance to that of the same catalyst under conventional heating. While the microwave-assisted (MW) process achieved higher benzene yields, the catalyst experienced faster deactivation due to the selective and rapid deposition of coke within the pores of the zeolite, as confirmed through Brunauer–Emmett–Teller (BET), X-ray diffraction (XRD), ammonia-temperature programmed desorption (NH 3 -TPD), thermal gravimetric analysis (TGA), temperature programmed oxidation (TPO), and X-ray photoelectron spectroscopy (XPS) analyses. The quantification of total coke content via TGA/TPO and surface carbon (XPS) revealed that nearly twice as much coke was deposited on the catalyst under MW conditions compared to that on the conventionally heated material, and the coke exhibited a more conductive and graphitic nature. The accelerated deactivation rates were attributed to the formation of hot spots in the MW system, leading to enhanced coupling with coke formed in situ during the reaction and resulting in increased Mo reduction. Observations indicated that the CO activation used to carburize the catalyst prior to the reaction is not advantageous in the MW heating environment. The presence of large amounts of Mo oxides at elevated temperatures (through hot spots) exposed to methane leads to instability under the reaction conditions. Optimizing the activation environment and improvement of the Mo dispersion within the pores are potential strategies to improve catalyst stability.

Mo/H-ZSM-5 zeolite↗

Quantifying the Impact of Metal Population Distribution in MFI-Supported Mo Catalysts for Methane Dehydroaromatization

Precise evaluation of intrinsic kinetic behavior in Mo/MFI catalysts for methane dehydroaromatization (MDA) is confounded by variations in Mo dispersion and speciation, which are influenced by metal loading and zeolite acidity. This work advances the utility of H 2 -temperature programmed reduction (H 2 -TPR) for characterizing Mo/MFI catalysts by enabling quantitative comparison of MoO x populations distinguished by reduction behavior and linked to initial catalytic performance. A comprehensive H 2 reduction pathway is established through systematic H 2 - TPR studies varying catalyst composition (1–10 wt % Mo, Si/Al = 15, 40, ∞), supplemented by UV-Raman spectroscopy, X-ray powder diffraction, N 2 physisorption, NH 3 -TPD, and advanced spectroscopic analysis (in situ XAS with principal component analysis/multivariate curve resolution—alternating least squares). Two low-temperature H 2 -TPR regions capture distinct Mo populations undergoing initial Mo(VI)→Mo(IV) reduction: a lower-temperature population (Mo-RI) associated primarily with highly dispersed, anchored MoO x species expected to predominantly reside within MFI channels, and a higher-temperature population (Mo-RII) corresponding to a broader set of MoO x species that becomes increasingly bulk-like/extrazeolitic at higher Mo loading. Quantification of these populations provides practical, kinetically relevant descriptors for comparing initial MDA rates across catalysts with varying Mo loading, Si/Al ratio, and MoO x heterogeneity. Application of lower-temperature Mo-RI estimates to kinetic measurements reveals a minimum threshold of ∼0.12 × 10 –3 mol Mo-RI/g cat , above which initial forward benzene rates normalized to this population converge despite differences in metal loading and zeolite Brønsted acidity. This threshold coincides with a transition toward a common C 2 -mediated benzene-forming regime, as indicated by approach-to-equilibrium analysis of methane-to-ethane, ethane-to-ethylene, and ethylene-to-benzene reaction steps. Above this threshold, normalized initial benzene rates are nearly invariant with increasing Mo-RII/Mo-RI population ratio, indicating that excess Mo-RII populations, including bulk-like/extrazeolitic MoO x domains present at higher loading, do not measurably suppress benzene formation associated with anchored and mostly channel-confined Mo population under the initial-rate conditions examined.

Mo/MFI↗

A Near-Real-Time Model for Predicting Electricity Disruptions in Texas During Winter Storms

There has been an increase in extreme weather events, posing a threat to power grid systems, potentially influenced by factors such as population growth, changes in ecosystems, land cover, and land use in the service area, as well as the growth of certain vegetation types. This research seeks to develop a predictive model to mitigate potential damages caused by future winter storms. This research utilizes the Light Gradient Boosting Machine (LightGBM), incorporating the number of power outages experienced at the county level, geographic details, weather information, and lagged outage and lagged weather data. The developed models were broadly divided into two groups, with six models in each group - one group without optimization and another with optimization, totaling 12 trained models. For model optimization, Bayesian optimization was employed using Root Mean Squared Error (RMSE) as the objective function. In results, when comparing Group 2 (the optimized group) with Group 1 (the non-optimized group), it was found that optimization did not always lead to a reduction in RMSE and Mean Absolute Error (MAE). However, in terms of Mean Directional Accuracy (MDA), while all results in Group 1 were below the baseline accuracy of 0.33, all results in Group 2 exceeded 0.33, with some cases showing an increase of more than three times the baseline. The results indicated that, in the optimized model group, Population and Pressure were the most influential factors when using current weather data and geographical information. When using lagged data, lagged recorded outages and lagged Pressure emerged as the most significant factors. Among the 12 developed models, the L-1-2-O model showed the lowest RMSE and MAE, as well as the highest accuracy, with values of 390.62 households and 168.13 households, respectively. To normalize the RMSE and MAE values, each metric was divided by the average number of households among the counties in Texas. For the L-1-2-O model, the scaled RMSE was 0.88% and the scaled MAE was 0.38%. In terms of MDA, which indicates the accuracy of the prediction direction, the L-1-O model achieved the highest score of 0.41. Although this study focused on Texas, which suffered the greatest impact from the winter storms in 2021, with additional validation, the methodology used in this research could be applied to other regions.

Lee, Jangjae [Texas A & M Univ., College Station, ↗

Astragaloside IV improved antioxidative stress capacity and related gene expression of the Keap1‐Nrf2 pathway in grass carp ( Ctenopharyngodon idella ) hepatocytes under heat stress

Abstract This study aims to investigate the protective effects of astragaloside IV (AS‐IV) on the hepatocytes of grass carp ( Ctenopharyngodon idella ) on heat stress. Cultured cells were treated with AS‐IV (0, 50, 100 and 200 μg/ml) at 28°C for 24 h and then exposed to heat stress by increasing the culturing temperature (32 ± 0.5°C) for 6 h. The increased temperatures significantly reduced cell viability and superoxide dismutase (SOD) activity, and increased malondialdehyde (MDA) levels in the 0 μg/ml AS‐IV treatment group at 32°C, but the grass carp hepatocytes treated with 100 and 200 μg/ml AS‐IV had significantly increased cell viability and SOD activity and decreased MDA levels. The mRNA levels of keap1a , keap1b , nrf2 , gsh‐px , cat , cu‐zn sod , mgst1 and il‐6 were significantly lower in the 0 μg/ml AS‐IV treatment group at 32°C, while those of keap1a , nrf2 , gsh‐px , cat , cu‐zn sod , gstp1 , ho‐1 and il‐6 were significantly higher in cells treated with 100 or 200 μg/ml AS‐IV. Our findings indicate that AS‐IV could enhance the antioxidative stress capacity of grass carp hepatocytes under heat stress, and its mechanism may be associated with the activation of the Keap1‐Nrf2 pathway. Thus, these results provide new insights into how to alleviate heat stress in grass carp.

Liu, Hua↗

Calculation of Moisture-Dependent, Anisotropic Parameters Supporting the Hanford Site's Composite Analysis, Cumulative Impact Evaluation, and Performance Assessments

Variable, moisture (tension) dependent anisotropy (MDA) in unsaturated soils is an effective, large-scale (macroscopic) flow property that results from media heterogeneities at a smaller scale. The purpose of this environmental calculation file (ECF) is to document the variable MDA calculations using a script routine. The accuracy of the script calculations are cross-checked against results using other software. Appendices for this ECF are Appendix A, which documents supporting script use; Appendix B, which provides supporting spreadsheet calculations; and Appendix C, which provides supporting utility calculations. The work is in support of vadose zone flow and transport models used in performance assessment (PA), composite analysis (CA), and cumulative impact evaluation (CIE) at the Hanford Site.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Stakeholder-Engaged Structured Decision Making for the Los Alamos Legacy Cleanup Mission - 20501

The Los Alamos National Laboratory (LANL) environmental legacy cleanup program requires decisions to be made for environmental remediation, decommissioning and disposal or management of radioactive waste. This legacy cleanup program was established to address groundwater contamination, material disposal areas (MDAs) that have been used to dispose of radioactive and other waste material, and 'aggregate areas' that might produce radioactive or other chemical waste as a result of remediation activities. The LANL site is regulated for environmental concerns under the Resource Conservation and Recovery Act (RCRA). However, some parts of LANL, such as material disposal area G (MDA G), have disposed of radioactive waste under DOE Order 435.1, and are subject to other regulations. For example, decommissioning the remote-handled TRU material stored in 33 shafts at MDA G falls under EPA's 40 CFR 191. Collectively, the regulations are all aimed in the same direction of finding the best solution, either through constructs such as 'as low as reasonably achievable' (ALARA), considering balancing factors as opposed to only cost and human health risk, and, under EPA regulations such as RCRA and NEPA, evaluating impact from all chemicals and both human health and ecological endpoints. Despite the basic goals and objectives of the regulations or their guidance, the main challenge is in their implementation. Arguably perhaps, but really in principle, all of these (and similar) regulations are asking for a decision analysis to be performed. Implementation challenges encountered have included lack of understanding of decision analysis in the industry, lack of effective stakeholder engagement in the decision analysis process, and lack of appreciation of the need to separate value judgments from science, the latter leading to developing conservative, or protective, science-based models. Conservative models lead to poor solutions, lack of effective stakeholder engagement leads to long drawn out protracted approaches to finding a solution (which also might never be found with this approach), and lack of understanding of decision analysis and Bayesian statistics causes poor models to be built, which creates unfortunate situations of 'garbage in, garbage out' becoming the basis for decision making. Stakeholder-engaged structured decision making (SDM) is an approach to solving problems that relies on the theory of decision science to involve stakeholders in the decision-making process. This approach incorporates stakeholder values using a scientifically rigorous methodology that separates value judgments from science in a way that helps avoid the pitfalls of biased, protective, or conservative modeling. This approach has its foundation in Keeney's 1992 treatise on value-focused thinking [1]. Keeney advocated a paradigm shift in decision making based on the idea that the standard way of thinking about decisions is backwards. The standard approach of focusing first on identifying alternatives rather than on articulating values results in a reactive approach with the emphasis on mechanics and fixed choices instead of the core values that have meaning to stakeholders. This paradigm shift effectively engages all stakeholders in the decision-making process while using a values focused thinking approach that can lead to the identification of decision opportunities and the creation of better alternatives. The intent is to be proactive and generate solutions that are related directly to values and objectives as identified by stakeholders. There are, perhaps, two overarching reasons why SDM can be used to benefit LANL's environmental legacy cleanup. Some of LANL's remaining waste management and environmental management problems are challenging and complex (for example, the Cr and RDX plumes, and MDAs) and while the traditional approach has, arguably, worked well for relatively simple risk-based problems, it cannot, or should not, be applied to more complex problems if the most effective and efficient solutions are desired. The second reason is cost. This has perhaps become more critical since publication of the Government Accountability Office (GAO) reports that DoE's environmental liability is considered a high-risk concern for the nation [2]. The focus of SDM is on structuring solutions to decision risk problems by first addressing stakeholder and decision maker values and subsequently developing decision objectives and ways to measure those objectives, preference weighting across objectives, identifying decision alternatives that best achieve those values, and characterizing uncertainty in predictions of the measures. Because a complete decision model is created using SDM, it can be evaluated to find the main elements of the model that drive, or predict, the best solution. This approach creates complete decision models that are transparent, traceable, reproducible and technically defensible. The science behind SDM, or decision analysis, is well founded, yet it is not unusual to see ad hoc approaches to decision making implemented under various environmental regulations that are pertinent to the LANL site, including NEPA, RCRA and DOE Order 435.1. Such ad hoc approaches are often not transparent or traceable, and lack reproducibility and technical defensibility. The LANL legacy cleanup program has embarked on using SDM to address the complex problems that remain. Stakeholder meetings have been held, and a prototype version of the stakeholder value system has been developed. Further meetings are expected in the future to address specific project needs. This is a long-term endeavor considering the complex environmental problems faced by DOE EM in Los Alamos (EM-LA), and careful planning, consideration of stakeholder value systems, and engagement with stakeholders throughout the SDM process is expected to lead to a successful endpoint. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Deep learning-accelerated 3D carbon storage reservoir pressure forecasting based on data assimilation using surface displacement from InSAR

Fast forecasting of the reservoir pressure distribution during geologic carbon storage (GCS) by assimilating monitoring data is a challenging problem. Due to high drilling cost, GCS projects usually have spatially sparse measurements from few wells, leading to high uncertainties in reservoir pressure prediction. To address this challenge, we use low-cost Interferometric Synthetic-Aperture Radar (InSAR) data as monitoring data to infer reservoir pressure build up. We develop a deep learning-accelerated workflow to assimilate surface displacement maps interpreted from InSAR and to forecast dynamic reservoir pressure. Employing an Ensemble Smoother Multiple Data Assimilation (ES-MDA) framework, the workflow updates three-dimensional (3D) geologic properties and predicts reservoir pressure with quantified uncertainties. We use a synthetic commercial-scale GCS model with bimodally distributed permeability and porosity to demonstrate the efficacy of the workflow. A two-step CNN-PCA approach is employed to parameterize the bimodal fields. The computational efficiency of the workflow is boosted by two residual U-Net based surrogate models for surface displacement and reservoir pressure predictions, respectively. The workflow can complete data assimilation and reservoir pressure forecasting in half an hour on a personal computer.

25 ENERGY STORAGE↗