Radionuclide transport in fractured chalk under abrupt changes in salinity.

Internationally, it has been agreed that geologic repositories for spent fuel and radioactive waste are considered the internationally agreed upon solution for intermediate and long-term disposal. In countries where traditional nuclear waste repository host rocks (e.g., clay, salt, granite) are not available, other low permeability lithologies must be studied. Here, chalk is considered to determine its viability for disposal. Despite chalk's low bulk permeability, it may contain fracture networks that can facilitate radionuclide transport. In arid areas, groundwater salinity may change seasonally due to the mixing between brackish groundwater and fresh meteoric water. Such salinity changes may impact the radionuclides' mobility. In this study, radioactive U(VI) and radionuclide simulant tracers (Sr, Ce and Re) were injected into a naturally fractured chalk core. The mobility of tracers was investigated under abrupt salinity variations. Two solutions were used: a low ionic strength (IS) artificial rainwater (ARW; IS ∼0.002) and a high IS artificial groundwater (AGW; IS ∼0.2). During the experiments, the tracers were added to ARW, then the carrier was changed to AGW, and vice versa. Ce was mobile only in colloidal form, while Re was transported as a conservative tracer. Both Re and Ce demonstrated no change in mobility due to salinity changes. In contrast, U and Sr showed increased mobility when AGW was introduced and decreased mobility when ARW was introduced into the core. These experimental results, supported by reactive transport modeling, suggest that saline groundwater solutions promote U and Sr release via ion-exchange and enhance their migration in fractured chalk. The study emphasizes the impact of salinity variations near spent fuel repositories and their possible impact on radionuclide mobility.

Improved net carbon budgets in the US Midwest through direct measured impacts of enhanced weathering.

Terrestrial enhanced weathering (EW) through the application of Mg- or Ca-rich rock dust to soil is a negative emission technology with the potential to address impacts of climate change. The effectiveness of EW was tested over 4 years by spreading ground basalt (50 t ha-1 year-1 ) on maize/soybean and miscanthus cropping systems in the Midwest US. The major elements of the carbon budget were quantified through measurements of eddy covariance, soil carbon flux, and biomass. The movement of Mg and Ca to deep soil, released by weathering, balanced by a corresponding alkalinity flux, was used to measure the drawdown of CO2 , where the release of cations from basalt was measured as the ratio of rare earth elements to base cations in the applied rock dust and in the surface soil. Basalt application stimulated peak biomass and net primary production in both cropping systems and caused a small but significant stimulation of soil respiration. Net ecosystem carbon balance (NECB) was strongly negative for maize/soybean (-199 to -453 g C m-2 year-1 ) indicating this system was losing carbon to the atmosphere. Average EW (102 g C m-2 year-1 ) offset carbon loss in the maize/soybean by 23%-42%. NECB of miscanthus was positive (63-129 g C m-2 year-1 ), indicating carbon gain in the system, and EW greatly increased inorganic carbon storage by an additional 234 g C m-2 year-1 . Our analysis indicates a co-deployment of a perennial biofuel crop (miscanthus) with EW leads to major wins-increased harvested yields of 29%-42% with additional carbon dioxide removal (CDR) of 8.6 t CO2 ha-1 year-1 . EW applied to maize/soybean drives a CDR of 3.7 t CO2 ha-1 year-1 , which partially offsets well-established carbon losses from soil from this crop rotation. EW applied in the US Midwest creates measurable improvements to the carbon budgets perennial bioenergy crops and conventional row crops.

Application of community data to surface complexation modeling framework development: Iron oxide protolysis.

This study presents a comprehensive community data-driven surface complexation modeling framework for simulating potentiometric titration of mineral surfaces. Compiled community data for ferrihydrite, goethite, hematite, and magnetite are fit to produce representative protolysis constants that can reproduce potentiometric titration data collected from multiple literature sources. Using this framework, the impact of surface complexation model type and surface site density (SSD) on the fit quality and protolysis constants can be readily evaluated. For example, the non-electrostatic model yielded a poor data fit compared to diffuse double layer model and constant capacitance models due to the absence of known surface charge effects. Regardless of the choice of iron oxide mineral, pKa1 decreased with increasing SSD while the opposite tendency was observed for pKa2. This newly developed framework demonstrates a method to reconcile community data-wide potentiometric titration data using Findable, Accessible, Interoperable, Reusable data principles to produce mineral protolysis constants that improve robustness of surface complexation models for applications in metal sorption and reactive transport modeling. The framework is readily expandable (as community data increase) and extensible (as the number of minerals increase). The framework provides a path forward for developing self-consistent, comprehensive, and updateable surface complexation databases for surface complexation and reactive transport modeling.

High-affinity amide-lanthanide adsorption to gram-positive soil bacteria.

The gram-positive soil bacterium, Arthrobacter nicotianae, uses multiple organic acid functional groups to adsorb lanthanides onto its cell surface. At relevant soil pH conditions of 4.0-6.0, many of these functional groups are de-protonated and available for cation sorption and metal immobilization. However, among the plethora of naturally occurring site types, A. nicotianae is shown to possess high-affinity amide and phosphate sites that disproportionately affect lanthanide adsorption to the cell wall. We quantify neodymium (Nd)-selective site types, reporting an amide-Nd stability constant of log10 K = 6.41 ± 0.23 that is comparable to sorption via phosphate-based moieties. These sites are two to three orders of magnitude more selective for Nd than the adsorption of divalent metals to ubiquitous carboxyl-based moieties. This implies the importance of lanthanide biosorption in the context of metal transport in subsurface systems despite trace concentrations of lanthanides found in the natural environment.

Proposed bone health screening protocol to identify total knee arthroplasty patients for preoperative DXA.

This study evaluates a novel, simple bone health screening protocol composed of patient sex, age, fracture history, and FRAX risk to identify total knee arthroplasty patients for preoperative DXA. Findings supported effectiveness, with sensitivity of 1.00 (CI 0.92-1.00) and specificity of 0.54 (CI 0.41-0.68) when evaluating for clinical osteoporosis. PURPOSE: Bone health optimization is a process where osteoporotic patients are identified, evaluated via modalities such as dual-energy X-ray absorptiometry (DXA), and treated when indicated. There are currently no established guidelines to determine who needs presurgical DXA. This study evaluates the effectiveness of a simple screening protocol to identify TKA patients for preoperative DXA. METHODS: This prospective cohort study began on September 1, 2019, and included 100 elective TKA patients. Inclusion criteria were ≥ 50 years and primary TKA. All patients obtained routine clinical DXA. The screening protocol defining who should obtain DXA included meeting any of the following: female ≥ 65, male ≥ 70, fracture history after age 50, or FRAX major osteoporotic fracture risk without bone mineral density (BMD) adjustments ≥ 8.4%. Osteoporosis was defined by the World Health Organization (WHO) criteria (T-score ≤ - 2.5) or clinically (T-score ≤ - 2.5, elevated BMD-adjusted FRAX risk, or prior hip/spine fracture). Sensitivity and specificity were calculated. RESULTS: The study included 68 females and 32 males, mean age 67.2 ± 7.7. T-score osteoporosis was observed in 16 patients while 43 had clinical osteoporosis. Screening criteria recommending DXA was met by 69 patients. Screening sensitivity was 1.00 (CI 0.79-1.00) and specificity was 0.37 (CI 0.27-0.48) for identifying patients with T-score osteoporosis. Similar sensitivity of 1.00 (CI 0.92-1.00) and specificity of 0.54 (CI 0.41-0.68) were found for clinical osteoporosis. CONCLUSIONS: A simple screening protocol identifies TKA patients with T-score and clinical osteoporosis for preoperative DXA with high sensitivity in this prospective cohort study.

A Novel Osteoporosis Screening Protocol to Identify Orthopedic Surgery Patients for Preoperative Bone Health Optimization.

Introduction: Osteoporosis is highly prevalent in elective orthopedic surgery. While preoperative bone health optimization decreases osteoporosis-related complications, there is an unmet need to establish who may benefit from preoperative dual-energy x-ray absorptiometry (DXA). This study assesses a novel, simple screening protocol to identify orthopedic surgical patients for preoperative DXA. Materials/Methods: This retrospective cohort study included 628 patients undergoing total knee, hip, or shoulder arthroplasty or thoracolumbar spine fusion. Inclusion criteria were ≥40 years undergoing primary elective surgery. Screening criteria defining who should obtain DXA due to high osteoporosis risk included: female ≥65, male ≥70, fracture history when ≥50 years, or FRAX major osteoporotic fracture risk (without bone mineral density [BMD]-adjustments) ≥8.4%. Osteoporosis was defined by World Health Organization criteria [T-score ≤ -2.5], clinical National Osteoporosis Foundation (NOF) criteria [T-score ≤ -2.5, elevated BMD-adjusted FRAX risk, or prior hip/spine fracture], and modified clinical criteria [NOF criteria simplified to include any non-traumatic prior fracture and FRAX without BMD]. Results: The study included 100 TKAs, 100 THAs, 251 TSAs, and 177 spine fusions, average age 65.6 ± 9.8. DXA was available for 209 patients. Screening criteria recommending DXA was met by 362 patients. For those with DXA, screening sensitivity was .96 (CI: .78 to .99) and specificity was .19 (CI: .14 to .25) for identifying T-score osteoporosis. Similar sensitivity of .99 (CI: .91 to .99) and specificity of .61 (CI: .56 to .66) were found for modified clinical osteoporosis. For modified clinical osteoporosis, 192 patients with osteoporosis met criteria (true pos.), 1 patient with osteoporosis did not meet criteria (false neg.), 170 patients without osteoporosis met criteria (false pos.), and 265 patients without osteoporosis did not meet criteria (true neg.). Discussion/Conclusion: A simple screening protocol identifies orthopedic surgical candidates at risk of T-score or clinical osteoporosis for preoperative DXA with high sensitivity.

Community Data Mining Approach for Surface Complexation Database Development.

This paper presents a comprehensive data-to-model workflow, including a findable, accessible, interoperable, reusable (FAIR) community sorption database (newly developed LLNL Surface Complexation/Ion Exchange (L-SCIE) database) along with a data fitting workflow to efficiently optimize surface complexation reaction constants with multiple surface complexation model (SCM) constructs. This workflow serves as a universal framework to mine, compile, and analyze large numbers of published sorption data as well as to estimate reaction constants for parameterizing reactive transport models. The framework includes (1) data digitization from published papers, (2) data unification including unit conversions, and (3) data-model integration and reaction constant estimation using geochemical software PHREEQC coupled with the universal parameter estimation code PEST. We demonstrate our approach using an analysis of U(VI) sorption to quartz based on a first L-SCIE implementation, concluding that a multisite SCM construct with carbonate surface species yielded the best fit to community data. Surface complexation reaction constants extracted from this approach captured all available sorption data available in the literature and provided insight into previously published reaction constants and surface complexation model constructs. The L-SCIE sorption database presented herein allows for automating this approach across a wide range of metals and minerals and implementing novel machine learning approaches to reactive transport in the future.

Magnesium isotope fractionation during microbially enhanced forsterite dissolution.

Bacillus subtilis endospore-mediated forsterite dissolution experiments were performed to assess the effects of cell surface reactivity on Mg isotope fractionation during chemical weathering. Endospores present a unique opportunity to study the isolated impact of cell surface reactivity because they exhibit extremely low metabolic activity. In abiotic control assays, 24 Mg was preferentially released into solution during forsterite dissolution, producing an isotopically light liquid phase (δ26 Mg = -0.39 ± 0.06 to -0.26 ± 0.09‰) relative to the initial mineral composition (δ26 Mg = -0.24 ± 0.03‰). The presence of endospores did not have an apparent effect on Mg isotope fractionation associated with the release of Mg from the solid into the aqueous phase. However, the endospore surfaces preferentially adsorbed 24 Mg from the dissolution products, which resulted in relatively heavy aqueous Mg isotope compositions. These aqueous Mg isotope compositions increased proportional to the fraction of dissolved Mg that was adsorbed, with the highest measured δ26 Mg (-0.08 ± 0.07‰) corresponding to the highest degree of adsorption (~76%). The Mg isotope composition of the adsorbed fraction was correspondingly light, at an average δ26 Mg of -0.49‰. Secondary mineral precipitation and Mg adsorption onto secondary minerals had a minimal effect on Mg isotopes at these experimental conditions. Results demonstrate the isolated effects of cell surface reactivity on Mg isotope fractionation separate from other common biological processes, such as metabolism and organic acid production. With further study, Mg isotopes could be used to elucidate the role of the biosphere on Mg cycling in the environment.

Microbe Encapsulation for Selective Rare-Earth Recovery from Electronic Waste Leachates.

Rare earth elements (REEs) are indispensable components of many green technologies and of increasing demand globally. However, refining REEs from raw materials using current technologies is energy intensive and enviromentally damaging. Here, we describe the development of a novel biosorption-based flow-through process for selective REE recovery from electronic wastes. An Escherichia coli strain previously engineered to display lanthanide-binding tags on the cell surface was encapsulated within a permeable polyethylene glycol diacrylate (PEGDA) hydrogel at high cell density using an emulsion process. This microbe bead adsorbent contained a homogenous distribution of cells whose surface functional groups remained accessible and effective for selective REE adsorption. The microbe beads were packed into fixed-bed columns, and breakthrough experiments demonstrated effective Nd extraction at a flow velocity of up to 3 m/h at pH 4-6. The microbe bead columns were stable for reuse, retaining 85% of the adsorption capacity after nine consecutive adsorption/desorption cycles. A bench-scale breakthrough curve with a NdFeB magnet leachate revealed a two-bed volume increase in breakthrough points for REEs compared to non-REE impurities and 97% REE purity of the adsorbed fraction upon breakthrough. These results demonstrate that the microbe beads are capable of repeatedly separating REEs from non-REE metals in a column system, paving the way for a biomass-based REE recovery system.

Recovery of Rare Earth Elements from Geothermal Fluids through Bacterial Cell Surface Adsorption.

The increasing demand for rare earth elements (REEs) in the modern economy motivates the development of novel strategies for cost-effective REE recovery from nontraditional feedstocks. We previously engineered E. coli to express lanthanide binding tags on the cell surface, which increased the REE biosorption capacity and selectivity. Here we examined how REE adsorption by the engineered E. coli is affected by various geochemical factors relevant to geothermal fluids, including total dissolved solids (TDS), temperature, pH, and the presence of specific competing metals. REE biosorption is robust to TDS, with high REE recovery efficiency and selectivity observed with TDS as high as 165,000 ppm. Among several metals tested, U, Al, and Pb were found to be the most competitive, causing >25% reduction in REE biosorption when present at concentrations ∼3- to 11-fold higher than the REEs. Optimal REE biosorption occurred between pH 5-6, and sorption capacity was reduced by ∼65% at pH 2. REE recovery efficiency and selectivity increased as a function of temperature up to ∼70 °C due to the thermodynamic properties of metal complexation on the bacterial surface. Together, these data define the optimal and boundary conditions for biosorption and demonstrate its potential utility for selective REE recovery from geofluids.

Context-Dependent Roles for SIRT2 and SIRT3 in Tumor Development Upon Calorie Restriction or High Fat Diet.

Calorie restriction (CR) is considered one of the most robust ways to extend life span and reduce the risk of age-related diseases, including cancer, as shown in many different organisms, whereas opposite effects have been associated with high fat diets (HFDs). Despite the proven contribution of sirtuins in mediating the effects of CR in longevity, the involvement of these nutrient sensors, specifically, in the diet-induced effects on tumorigenesis has yet to be elucidated. Previous studies focusing on SIRT1, do not support a critical role for this sirtuin family member in CR-mediated cancer prevention. However, the contribution of other family members which exhibit strong deacetylase activity is unexplored. To fill this gap, we aimed at investigating the role of SIRT2 and SIRT3 in mediating the anti and pro-tumorigenic effect of CR and HFD, respectively. Our results provide strong evidence supporting distinct, context-dependent roles played by these two family members. SIRT2 is indispensable for the protective effect of CR against tumorigenesis. On the contrary, SIRT3 exhibited oncogenic properties in the context of HFD-induced tumorigenesis, suggesting that SIRT3 inhibition may mitigate the cancer-promoting effects of HFD. Given the different functions regulated by SIRT2 and SIRT3, unraveling downstream targets/pathways involved may provide opportunities to develop new strategies for cancer prevention.

Improved removal of volatile organic compounds for laser-based spectroscopy of water isotopes.

RATIONALE: Volatile organic compounds (VOCs) such as methanol and ethanol in water extracted from plants cause spectral interference in isotope ratio infrared spectroscopy (IRIS). This contamination degrades the accuracy of measurements, limiting the use of IRIS. In response, this study presents a new decontamination method of VOCs for enhanced IRIS measurements. METHODS: The isotopic compositions of water from laboratory-made and field-collected plant samples pre- and post-treatment were analyzed using IRIS. Traditional treatment methods of activated charcoal and commercial pre-combustion systems (MCM) were compared with our new treatment method that implements solid-phase extraction (SPE). The absolute concentrations of contaminants pre- and post-treatment were determined using (1)H and (13)C nuclear magnetic resonance to assess the effectiveness of the different treatments. RESULTS: SPE removes an average of 86.7% and 78.8% ethanol and methanol, respectively, significantly reducing spectral interference. SPE reduces errors to within instrumental noise for both ethanol and methanol at concentrations found in nature (<3.0% and 0.08%, respectively). Activated charcoal minimally affected alcohol concentrations. MCM significantly worsened ethanol-contaminated water isotope measurements by producing primary alcohol oxidation products such as formic acid, another compound that interferes with IRIS absorption. CONCLUSIONS: SPE is an effective, low-cost method for eliminating errors in ethanol-contaminated samples. For samples where methanol is prevalent, combining SPE and MCM is more effective than the use of SPE alone. Hence, SPE treatment alone or in conjunction with MCM is recommended as an effective pre-analysis purification method for water extracted from plants.