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Health Hazards of Exposures to Radioiodine

Iodine is a chemical element with atomic number 53. Iodine-127 is stable (non-radioactive) and commonly found in nature. Elemental iodine is a purple-colored solid at room temperature and pressure, but spontaneously sublimates (turns into vapor). Iodine is an essential element for life, and is required for proper functioning of the thyroid. Iodine is present in many foods, and is readily absorbed by the body and concentrated in the thyroid gland. A fraction of iodine ingested or inhaled is rapidly removed by the kidneys. The rest of the inhaled or ingested iodine is absorbed the by thyroid and retained for many months. Iodine has a biological half-life of approximately 120 days in health individuals. The biological half-life can be shorter in individuals with hyperthyroidism, and longer in individuals with hypothyroidism. Iodine has a number of radioactive isotopes, most of which have relatively short half-lives (days or weeks). Short half-life iodine isotopes are useful for a variety of medical applications, including imaging and cancer therapy. For example, Iodine-123 (half-life 13 hours) is commonly used for medical imaging of the thyroid, while iodine-131 (half-life 8 days) is used for suppressing thyroid function in individuals with hyperthyroidism or ablating (killing) thyroid cells to treat thyroid cancer. Iodine-125 (half-life 59 days) is produced in nuclear reactors, and has medical uses. Although iodine-125 can be used for thyroid imaging, Iodine-123 is more commonly used for that purpose because of its shorter half-life and higher-energy emissions. Iodine-125 is more commonly used for cancer treatment, and can be processed into small metal pellets (seeds) inserted directly into a tumor. Iodine-125 emits low-energy x-rays which can kill tumor cells and generally cannot escape the tumor, sparing other tissues. Medical iodine for imaging or treatment is typically administered orally in the form a pill or liquid solution. A typical adult thyroid scan using iodine-123 involves having the patient swallow between one and four 0.1 millicuries pills, with the exact dose dependent on the patient’s weight. This results in a whole-body committed effective dose of 80 – 320 mrem, and a thyroid equivalent dose of 1443 – 5772 mrem. Note that the whole-body effective dose relates to the overall cancer risk, while the larger equivalent dose to the thyroid only indicates that most of this risk is the result of exposure to the thyroid. These doses are considered safe, although the procedure is not recommended for pregnant or breastfeeding women. In contrast, the quantities of iodine-131 used for treatment of hyperthyroidism and thyroid cancers are much higher. For treatment of hyperthyroidism, 4 – 10 millicuries are administered, while for thyroid cancer the administration can range from 50 – 150 millicuries of I-131. In addition to medical exposures, large populations were exposed to radioiodine as result of the atomic bombings of Hiroshima and Nagasaki in Japan, and the Chernobyl nuclear accident. These populations have been carefully followed for many years to assess the effect of their radiation exposures on cancer risk. As a result, a great deal is known about the cancer risks associated with radioiodine exposure. Because iodine is concentrated in the thyroid, the principal risk of exposure to radioiodine is thyroid cancer. Children have the highest risk of thyroid cancer after exposure to radioactive iodine. According to a large study of Japanese atomic bomb survivors, an effective dose of one Sievert (100,000 mrem) has been observed to increase the risk of thyroid cancer by a factor of 9.5 in children aged zero to nine years old, by a factor of 3 in children aged 10 to 19 years old, and by barely detectable amounts in adults. Another way of quantifying the risk from radioiodine exposure is from risk coefficients, which provide the risk per unit intake of radionuclides in terms of both morbidity (any cancer) and mortality (death). Both morbidity (risk of cancer) and mortality (death) risks are shown in the table below. Note that because thyroid cancer is almost never fatal, the morbidity coefficients are much larger than the mortality coefficients.

61 RADIATION PROTECTION AND DOSIMETRY↗

Varied farm-level carbon intensities of corn feedstock help reduce corn ethanol greenhouse gas emissions

Abstract A reduction in the overall carbon intensity (CI) of a crop-based biofuel can be achieved by cutting down the CI of the biofuel’s feedstock, which in turn correlates significantly to agricultural management practices. Proposals are being made to incentivize low-carbon biofuel feedstocks under U.S. fuel regulatory programs to promote sustainable farming practices by individual farms. For such an incentive scheme to function properly, robust data collection and verification are needed at the farm level. This study presents our collaboration with U.S. private sector companies to collect and verify the corn production data necessary for feedstock-specific CI calculation at the farm level, through a carefully designed questionnaire, to demonstrate the practicality and feasibility of data collection at scale. We surveyed 71 farms that produced 0.2 million metric tons of corn grain in 2018 in a Midwestern U.S. state to obtain information on key parameters affecting corn ethanol feedstock CI, such as grain yields, fertilizer/chemical application rates, and agronomic practices. Feedstock-specific CI was calculated in the unit of grams (g) CO 2 equivalent (CO 2 e) of greenhouse gases per kilogram (kg) of corn produced. Results showed large CI variations—from 119 to 407 g CO 2 e kg −1 of corn—due to the farm-level inventory, while the production-weighted average CI for all surveyed farms was 210 g CO 2 e kg −1 , comparable to the national average CI of 204 g CO 2 e kg −1 . The nitrogen fertilizer type applied and rate were identified as key factors contributing most to CI variations at the farm level. The estimated N 2 O emissions from fertilizer and biomass nitrogen inputs to soil accounted for 51% of the overall farm-level CI and therefore need to be better monitored at farm level with high resolution. We concluded that this feedstock-specific, farm-level CI evaluation has the potential to be used to incentivize low-carbon feedstock for biofuel production.

54 ENVIRONMENTAL SCIENCES↗

NMR Studies of Block Copolymer-Based Supramolecules in Solution

Hierarchical assemblies from block copolymer (BCP)-based supramolecules have shown immense potential as programmable materials owing to their versatility for incorporating functional molecules and provide access to arrays of hierarchical structures. However, there remains a knowledge gap on the formation of the supramolecule in solution. Here, we applied NMR techniques to investigate the solution-phase behavior of the most studied supramolecular systems, polystyrene-block-poly(4-vinylpyridine)(3-pentadecylphenol) (PS-b-P4VP(PDP) r ). The results show that the supramolecule likely adopts a coil-comb conformation, despite the small molecule's (PDP) rapid exchange between the bonded and free states. The exchange rate (>10 4 s -1 ) exceeds the NMR time scale at the frequency of interest. The supramolecules form under dilute conditions (~2 vol %) and are attributed to the enthalpic gain of the hydrogen bonding between the PDP and 4VP. As the solute concentration increases (>10 vol %), the supramolecule forms micelle-like aggregates with PDP accumulated within the comb-block's pervaded volume based on analysis of the apparent molecular weight, viscosity, and chain dynamics. Overall, this work sheds light on the long-standing question regarding the evolution of the constituents in the BCP-based supramolecule in solution and provides valuable guidance toward their solution-based processing and morphological control.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coupled Biotic-Abiotic Processes Control Biogeochemical Cycling of Dissolved Organic Matter in the Columbia River Hyporheic Zone

A critical component of assessing the impacts of climate change on watershed ecosystems involves understanding the role that dissolved organic matter (DOM) plays in driving whole ecosystem metabolism. The hyporheic zone—a biogeochemical control point where ground water and river water mix—is characterized by high DOM turnover and microbial activity and is responsible for a large fraction of lotic respiration. Yet, the dynamic nature of this ecotone provides a challenging but important environment to parse out different DOM influences on watershed function and net carbon and nutrient fluxes. We used high-resolution Fourier-transform ion cyclotron resonance mass spectrometry to provide a detailed molecular characterization of DOM and its transformation pathways in the Columbia river watershed. Samples were collected from ground water (adjacent unconfined aquifer underlying the Hanford 300 Area), Columbia river water, and its hyporheic zone. The hyporheic zone was sampled at five locations to capture spatial heterogeneity within the hyporheic zone. Our results revealed that abiotic transformation pathways (e.g., carboxylation), potentially driven by abiotic factors such as sunlight, in both the ground water and river water are likely influencing DOM availability to the hyporheic zone, which could then be coupled with biotic processes for enhanced microbial activity. The ground water profile revealed high rates of N and S transformations via abiotic reactions. The river profile showed enhanced abiotic photodegradation of lignin-like molecules that subsequently entered the hyporheic zone as low molecular weight, more degraded compounds. While the compounds in river water were in part bio-unavailable, some were further shown to increase rates of microbial respiration. Together, river water and ground water enhance microbial activity within the hyporheic zone, regardless of river stage, as shown by elevated putative amino-acid transformations and the abundance of amino-sugar and protein-like compounds. This enhanced microbial activity is further dependent on the composition of ground water and river water inputs. Our results further suggest that abiotic controls on DOM should be incorporated into predictive modeling for understanding watershed dynamics, especially as climate variability and land use could affect light exposure and changes to ground water essential elements, both shown to impact the Columbia river hyporheic zone.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Exploring Changes in Quasar Spectral Energy Distributions across C IV Parameter Space

We examine the UV/X-ray properties of 1378 quasars in order to link empirical correlations to theoretical models of the physical mechanisms dominating quasars as a function of mass and accretion rate. The clarity of these correlations is improved when (1) using C IV broad emission line equivalent width (EQW) and blueshift (relative to systemic) values calculated from high signal-to-noise ratio reconstructions of optical/UV spectra and (2) removing quasars expected to be absorbed based on their UV/X-ray spectral slopes. In addition to using the traditional C IV parameter space measures of C IV EQW and blueshift, we define a "C IV ∥ distance" along a best-fit polynomial curve that incorporates information from both C IV parameters. We find that the C IV ∥ distance is linearly correlated with both the optical-to-X-ray slope, α ox , and broad-line He II EQW, which are known spectral energy distribution indicators, but does not require X-ray or high spectral resolution UV observations to compute. The C IV ∥ distance may be a better indicator of the mass-weighted accretion rate, parameterized by L/L Edd , than the C iv EQW or blueshift alone, as those relationships are known to break down at the extrema. Conversely, there is only a weak correlation with the X-ray energy index (Γ), an alternate L/L Edd indicator. We find no X-ray or optical trends in the direction perpendicular to the C IV distance that could be used to reveal differences in accretion disk, wind, or corona structure that could be widening the C IV EQW–blueshift distribution. A different parameter (such as metallicity) not traced by these data must come into play.

79 ASTRONOMY AND ASTROPHYSICS↗

Isoflavone supplementation, via red clover hay, alters the rumen microbial community and promotes weight gain of steers grazing mixed grass pastures

Biochanin A, an isoflavone present in the pasture legume red clover (Trifloium pratense L.), alters fermentation in the rumen of cattle and other ruminants. Biochanin A inhibits hyperammonia-producing bacteria and promotes cellulolytic bacteria and fiber catalysis in vitro and ex vivo. Consequently, biochanin A supplementation improves weight gain in grazing steers. Red clover contains biologically active isoflavones that may act synergistically. Therefore, the objective was to evaluate the effect of two levels of red clover hay on growth performance and the microbial community in growing steers grazing mixed grass pastures. A grazing experiment was conducted over 2 early growing seasons (2016 and 2017) with 36 cross-bred steers and twelve rumen-fistulated, growing Holstein steers for evaluation of average daily gain and rumen microbiota, respectively. Steers were blocked by body weight and assigned to pastures with one of four treatments: 1) pasture only, 2) pasture + dry distillers’ grains (DDG), 3) pasture + DDG + low level of red clover hay (~15% red clover diet), or 4) pasture + DDG + high level of red clover hay (~30% red clover diet). DDG were added to treatments to meet protein requirements and to balance total protein supplementation between treatments. All supplementation strategies (DDG ± red clover hay) increased average daily gains in comparison to pasture-only controls (P < 0.05), with a low level of red clover supplementation being the most effective (+0.17 kg d-1 > DDG only controls; P < 0.05). Similarly, hyper-ammonia-producing bacteria inhibition (10–100-fold; P < 0.05), fiber catalysis (+10–25%; P < 0.05) and short chain fatty acid concentrations were greatest with the low red clover supplement (+~25%; P < 0.05). These results provide evidence that lower levels or red clover supplementation may be optimal for maximizing overall microbial community function and animal performance in grazing steers.

54 ENVIRONMENTAL SCIENCES↗

Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

The multi-criteria decision analysis (MCDA) framework provides a systematic evaluation of the diverse preferences and performance metrics associated with alternative solutions. This approach is advantageous over a single-criterion methodology, which are only valid under conditions that assume ceteris paribus or an "apples-to-apples" comparison. However, selecting suitable technologies for integrated energy systems (IES) can be likened to an "apples-to-oranges" comparison, given the heterogeneous factors at stake. These factors include economics and performance parameters, geological compatibility, and environmental impacts. Consequently, past research has often employed a mixture of qualitative and quantitative criteria tailored to the specific interests of each study. While the method proves effective in handling the intricate interplay of criteria, the resulting rankings and scores can vary from study to study. This inconsistency is introduced from the use of subjectively defined thresholds and weights. As a result, decision-makers frequently find it challenging to establish clear connections between specific criteria and the resulting scores, as the transformation of criteria into ordinal scores results in a substantial loss of information. To address this challenge, we introduce a data-informed IES evaluation framework that offers comprehensive, interpretable, and traceable evaluations backed by quantifiable rationale. First, we identified key IES evaluation criteria from a decade of literature, focusing on relevant IES applications in power, process heat, and hydrogen production. We leveraged state-of-the-art cost estimates from the Idaho National Laboratory (INL) and technical data from 78 reactor designs from the International Atomic Energy Agency (IAEA) and the Organization for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA). Lastly, we established thresholds by analyzing the mean, variance, root mean square, and slope of values across alternatives, categorizing the preferences of decision-makers into distinct utility functions, such as linear, saturating, exponential, and stepwise. Our approach yielded two main outcomes: (1) it provided consistent assessments across different stakeholder groups and (2) it visualized uncertainties in the decision-making context via comprehensive sensitivity analysis. To demonstrate the impact of our framework, we conducted case studies on 6 reactor designs (AP1000, NuScale, BWRX-300, Xe-100, eVinci, iMSR) for the three applications. Our data-driven framework proved to be highly effective in addressing heterogenous uncertainties faced by varied decision-makers? preferences and IES applications, as well as cost and technical estimates of advanced reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

The multi-criteria decision analysis (MCDA) framework provides a systematic evaluation of the diverse preferences and performance metrics associated with alternative solutions. This approach is advantageous over a single-criterion methodology, which are only valid under conditions that assume ceteris paribus or an "apples-to-apples" comparison. However, selecting suitable technologies for integrated energy systems (IES) can be likened to an "apples-to-oranges" comparison, given the heterogeneous factors at stake. These factors include economics and performance parameters, geological compatibility, and environmental impacts. Consequently, past research has often employed a mixture of qualitative and quantitative criteria tailored to the specific interests of each study. While the method proves effective in handling the intricate interplay of criteria, the resulting rankings and scores can vary from study to study. This inconsistency is introduced from the use of subjectively defined thresholds and weights. As a result, decision-makers frequently find it challenging to establish clear connections between specific criteria and the resulting scores, as the transformation of criteria into ordinal scores results in a substantial loss of information. To address this challenge, we introduce a data-informed IES evaluation framework that offers comprehensive, interpretable, and traceable evaluations backed by quantifiable rationale. First, we identified key IES evaluation criteria from a decade of literature, focusing on relevant IES applications in power, process heat, and hydrogen production. We leveraged state-of-the-art cost estimates from the Idaho National Laboratory (INL) and technical data from 78 reactor designs from the International Atomic Energy Agency (IAEA) and the Organization for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA). Lastly, we established thresholds by analyzing the mean, variance, root mean square, and slope of values across alternatives, categorizing the preferences of decision-makers into distinct utility functions, such as linear, saturating, exponential, and stepwise. Our approach yielded two main outcomes: (1) it provided consistent assessments across different stakeholder groups and (2) it visualized uncertainties in the decision-making context via comprehensive sensitivity analysis. To demonstrate the impact of our framework, we conducted case studies on 6 reactor designs (AP1000, NuScale, BWRX-300, Xe-100, eVinci, iMSR) for the three applications. Our data-driven framework proved to be highly effective in addressing heterogenous uncertainties faced by varied decision-makers? preferences and IES applications, as well as cost and technical estimates of advanced reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Constraining primordial non-Gaussianity from the large scale structure two-point and three-point correlation functions

Surveys of cosmological large-scale structure (LSS) are sensitive to the presence of local primordial non-Gaussianity (PNG), and may be used to constrain models of inflation. Local PNG, characterized by f NL ⁠, the amplitude of the quadratic correction to the potential of a Gaussian random field, is traditionally measured from LSS two-point and three-point clustering via the power spectrum and bi-spectrum. We propose a framework to measure f NL using the configuration space two-point correlation function (2pcf) monopole and three-point correlation function (3pcf) monopole of survey tracers. Our model estimates the effect of the scale-dependent bias induced by the presence of PNG on the 2pcf and 3pcf from the clustering of simulated dark matter haloes. We describe how this effect may be scaled to an arbitrary tracer of the cosmological matter density. The 2pcf and 3pcf of this tracer are measured to constrain the value of f NL ⁠. In LSS surveys, the effect of imaging systematics on two-point statistics is often degenerate with the PNG signal. Our proposed model employs three-point statistics primarily to break this degeneracy. Using simulations of luminous red galaxies observed by the Dark Energy Spectroscopic Instrument (DESI), we demonstrate the accuracy and constraining power of our method. Our forecast indicates the ability to constrain f NL to a precision of σf NL ≈ 22 with one year of DESI survey data, as well as the ability to constrain the imaging systematic weights in situ.

early Universe↗

Effective medium approximation for the refractive index of stratified metal oxide composites synthesized by atomic layer deposition

Atomic layer deposition (ALD) is a unique method for synthesizing conformal layers with precise composition. It is especially useful for the synthesis of mixed metal oxides for functional materials. One application of interest is the use of ALD for tailoring the refractive index of coatings. In homogeneously distributed composites of metal oxides, the refractive properties can be approximated as the average of the indices of the components. This is known as an effective medium approximation (EMA) and can be used to design the macroscopic properties of composites. ALD produces layered, anisotropic films, so the validity of an EMA in describing these films is not clear. Here, we use optical simulations and experimental characterization of stratified composites of TiO 2 and Al 2 O 3 to study the application of an EMA to the transmission and reflection behavior of ALD-prepared mixed metal oxide thin films. We found that when the characteristic layer thickness is smaller than roughly 10 nm, the optical spectra of theoretical and experimental ALD films match the equivalent theoretical spectra for a material with a refractive index calculated from a simple, compositionally weighted EMA. Hence, this EMA could describe the transmission and reflectance spectra in ALD-derived TiO2–Al 2 O 3 nanolaminates when the films were sufficiently stratified even without thorough characterization of the real layers in the films. As a result, we demonstrated that ALD can be used to prepare effectively homogenous mixed metal oxide films with a predictable, tailorable refractive index of any value between those of the TiO 2 and Al 2 O 3 component materials.

42 ENGINEERING↗

Developing Technology Performance Level Assessments for Early-Stage Wave Energy Converter Technologies: Preprint

The advantage of using Technology Performance Level (TPL) in conjunction with Technology Readiness Level (TRL) assessments in guiding technology development trajectories to successful outcomes in less time, at less overall cost, and with less encountered risk has been well articulated in the literature. In partnership with industry and international collaborators, a TPL assessment methodology for grid-connected applications has been developed through the application of the systems engineering approach. Metrics under seven different categories have been developed, weighted based on their relative relevance, and combined to yield a composite score. The methodology has been implemented in a spreadsheet tool plus a web application specifically aimed at assessing early stage (TRL 1-3) concepts. The target use cases are (a) technology developers improving their design, to find fatal flaws early, to get feedback on current design, to identify areas of improvement that will yield the highest return on investment, (b) reviewers assessing technologies in competitions or for making funding decisions, (c) investor or project developer doing due diligence, (d) policy makers landscaping the technology domain for formulating R&D strategy. The methodology and the tools are undergoing continuous improvement based on the experience and lessons learnt from applying it to internal and external marine energy technology development projects. The methodology is also being adapted for assessing WECs servicing markets outside the continental grid - broadly categorized as Powering the Blue Economy (PBE) applications. Such applications have vastly different functional requirements entailing a modification of the methodology to account for their higher risk tolerance, reduced price sensitivities, lower power needs, different permitting protocols, etc. This paper presents the latest status of the TPL assessment methodology and tools, describes its adaptation to select PBE markets, and explores its extension to other domains where it could provide a comprehensive and holistic measure of a nascent or disruptive technology's technoeconomic performance potential.

metrics↗

Developing Technology Performance Level Assessments for Early-Stage Wave Energy Converter Technologies

The advantage of using Technology Performance Level (TPL) in conjunction with Technology Readiness Level (TRL) assessments in guiding technology development trajectories to successful outcomes in less time, at less overall cost, and with less encountered risk has been well articulated in the literature. In partnership with industry and international collaborators, a TPL assessment methodology for grid-connected applications has been developed through the application of the systems engineering approach. Metrics under seven different categories have been developed, weighted based on their relative relevance, and combined to yield a composite score. The methodology has been implemented in a spreadsheet tool plus a web application specifically aimed at assessing early stage (TRL 1-3) concepts. The target use cases are (a) technology developers improving their design, to find fatal flaws early, to get feedback on current design, to identify areas of improvement that will yield the highest return on investment, (b) reviewers assessing technologies in competitions or for making funding decisions, (c) investor or project developer doing due diligence, (d) policy makers landscaping the technology domain for formulating R&D strategy. The methodology and the tools are undergoing continuous improvement based on the experience and lessons learnt from applying it to internal and external marine energy technology development projects. The methodology is also being adapted for assessing WECs servicing markets outside the continental grid - broadly categorized as Powering the Blue Economy (PBE) applications. Such applications have vastly different functional requirements entailing a modification of the methodology to account for their higher risk tolerance, reduced price sensitivities, lower power needs, different permitting protocols, etc. This paper presents the latest status of the TPL assessment methodology and tools, describes its adaptation to select PBE markets, and explores its extension to other domains where it could provide a comprehensive and holistic measure of a nascent or disruptive technology's technoeconomic performance potential.

metrics↗

Measurements of inclusive J/ψ production at midrapidity and forward rapidity in Pb–Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV

The measurements of the inclusive J/ψ yield at midrapidity (|y| < 0.9) and forward rapidity (2.5 < y < 4) in Pb–Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV with the ALICE detector at the LHC are reported. The inclusive J/ψ production yields and nuclear modification factors, R AA , are measured as a function of the collision centrality, J/ψ transverse momentum (p T ), and rapidity. The J/ψ average transverse momentum and squared transverse momentum ($\langle$p T $\rangle$ and $\langle$$p^{2}_{T}$$\rangle$) are evaluated as a function of the centrality at midrapidity. Compared to the previous ALICE publications, here the entire Pb–Pb collisions dataset collected during the LHC Run 2 is used, which improves the precision of the measurements and extends the p T coverage. The p T -integrated R AA shows a hint of an increasing trend towards unity from semicentral to central collisions at midrapidity, while it is flat at forward rapidity. The p T -differential R AA shows a strong suppression at high p T with less suppression at low p T where it reaches a larger value at midrapidity compared to forward rapidity. The ratio of the p T -integrated yields of J/ψ to those of D 0 mesons is reported for the first time for the central and semicentral event classes at midrapidity. Model calculations implementing charmonium production via the coalescence of charm quarks and antiquarks during the fireball evolution (transport models) or in a statistical approach with thermal weights are in good agreement with the data at low p T . At higher p T , the data are well described by transport models and a model based on energy loss in the strongly-interacting medium produced in nuclear collisions at the LHC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Enhanced transport of bacteria along root systems by protists can impact plant health

ABSTRACT Soil protists have been shown to contribute to the structure and function of the rhizosphere in a variety of ways. Protists are key contributors to nutrient cycling through the microbial loop, where biomass is digested by protists and otherwise stored nutrients are returned to the environment. Protists have also been shown to feed on plant pathogenic bacteria and alter root microbiomes in ways that may benefit plants. Recently, a mechanism involving bacterial transport, facilitated by protists, has been hypothesized to contribute to the spatial distribution of bacteria in the rhizosphere. Here, we observe the differential abilities of three soil protists: a ciliate (Colpodasp.), a flagellate (Cercomonassp.), and a naked amoeba (Acanthamoeba castellanii) to transport nitrogen-fixingSinorhizobium melilotito infectible root tips. Co-inoculation of protists plusS. melilotiresulted in the movement of bacteria, as measured by the presence of nitrogen-fixing nodules, up to 15 cm farther down the root systems when compared to plants inoculated withS. melilotialone. Co-inoculation of the ciliate, Colpodasp., withS. meliloti, resulted in shoot weights that were similar to plants that grew in nitrogen-replete potting mix.Colpodasp.-feeding style and motility likely contributed to their success at transporting bacteria through the rhizosphere. We observed that the addition of protists alone without the co-inoculum ofS. melilotiresulted in plants with larger shoot weights than control plants. Follow-up experiments showed that protists plus their associated microbiomes were aiding in plant health, likely through means of nutrient cycling. IMPORTANCE Protists represent a significant portion of the rhizosphere microbiome and have been shown to contribute to plant health, yet they are understudied compared to their bacterial and fungal counterparts. This study elucidates their role in the rhizosphere community and suggests a mechanism by which protists can be used to move bacteria along plant roots. We found that the co-inoculation of protists with nitrogen-fixing beneficial bacteria,Sinorhizobium meliloti, resulted in nodules farther down the roots when compared to plants inoculated with S.melilotialone, and shoot weights similar to plants that received nitrogen fertilizer. These data illustrate the ability of protists to transport viable bacteria to uninhabited regions of the root system.

Biotechnology & Applied Microbiology↗

High‐order symmetric cubature rules for tetrahedra and pyramids

Abstract In this article, we present an algorithm to construct high‐order fully symmetric cubature rules for tetrahedral and pyramidal elements, with positive weights and integration points that are in the interior of the domain. Cubature rules are fully symmetric if they are invariant to affine transformations of the domain. We divide the integration points into symmetry orbits where each orbit contains all the points generated by the permutation stars. These relations are represented by equality constraints. The construction of symmetric cubature rules require the solution of nonlinear polynomial equations with both inequality and equality constraints. For higher orders, we use an algorithm that consists of five sequential phases to produce the cubature rules. In the literature, symmetric numerical integration rules are available for the tetrahedron for orders p = 1 – 10, 14 , and for the pyramid up to p = 10 . We have obtained fully symmetric cubature rules for both of these elements up to order p = 20 . Numerical tests are presented that verify the polynomial‐precision of the cubature rules. Convergence studies are performed for the integration of exponential, weakly singular, and trigonometric test functions over both elements with flat and curved faces. With increase in p , improvements in accuracy is realized, though nonmonotonic convergence is observed.

Jaśkowiec, Jan↗

Targeting hydroxycinnamoyl CoA: shikimate hydroxycinnamoyl transferase for lignin modification in Brachypodium distachyon

Abstract Background Hydroxycinnamoyl CoA: shikimate hydroxycinnamoyl transferase (HCT) is a central enzyme of the so-called “esters” pathway to monolignols. As originally envisioned, HCT functions twice in this pathway, to form coumaroyl shikimate and then, in the “reverse” direction, to convert caffeoyl shikimate to caffeoyl CoA. The discovery of a caffeoyl shikimate esterase (CSE) that forms caffeic acid directly from caffeoyl shikimate calls into question the need for the reverse HCT reaction in lignin biosynthesis. Loss of function of HCT gives severe growth phenotypes in several dicot plants, but less so in some monocots, questioning whether this enzyme, and therefore the shikimate shunt, plays the same role in both monocots and dicots. The model grass Brachypodium distachyon has two HCT genes, but lacks a classical CSE gene. This study was therefore conducted to evaluate the utility of HCT as a target for lignin modification in a species with an “incomplete” shikimate shunt. Results The kinetic properties of recombinant B. distachyon HCTs were compared with those from Arabidopsis thaliana , Medicago truncatula , and Panicum virgatum (switchgrass) for both the forward and reverse reactions. Along with two M. truncatula HCTs, B. distachyon HCT2 had the least kinetically unfavorable reverse HCT reaction, and this enzyme is induced when HCT1 is down-regulated. Down regulation of B. distachyon HCT1, or co-down-regulation of HCT1 and HCT2, by RNA interference led to reduced lignin levels, with only modest changes in lignin composition and molecular weight. Conclusions Down-regulation of HCT1, or co-down-regulation of both HCT genes, in B. distachyon results in less extensive changes in lignin content/composition and cell wall structure than observed following HCT down-regulation in dicots, with little negative impact on biomass yield. Nevertheless, HCT down-regulation leads to significant improvements in biomass saccharification efficiency, making this gene a preferred target for biotechnological improvement of grasses for bioprocessing.

09 BIOMASS FUELS↗

BSMV-mediated genome editing exhibits host-specific heritability: germline transmission in barley and somatic edits in Nicotiana benthamiana

Plant RNA virus–mediated guide RNA (gRNA) delivery represents a transformative advance in genome editing technologies. Unlike conventional transformation methods that rely on labor-intensive tissue culture and regeneration for each individual gRNA delivery, viral vectors can rapidly and systemically transmit gRNAs into pre-established Cas-expressing plants, providing an accelerated route for functional genomics and trait discovery directly in planta . However, key design parameters, including subgenomic promoter choice, transcript architecture, and their effects on viral fitness and editing outcomes, remain to be elucidated for most viral platforms. We developed five Barley stripe mosaic virus (BSMV) vectors, each with distinct subgenomic promoter elements to drive single gRNA expression. These were initially evaluated in Cas9-expressing transgenic Nicotiana benthamiana plants targeting the Phytoene desaturase ( PDS ) gene to compare their editing efficiencies. Single gRNAs expressed under the duplicated γb subgenomic promoter or when fused directly to the γb genome achieved the highest mutation frequencies (up to 90% at 60 days post-inoculation), whereas β1- and β2-driven sgRNAs produced delayed and reduced editing. Thus, promoter selection critically determines gRNA accumulation and the efficacy of BSMV-mediated genome editing. The top-performing design was then applied to Cas9-expressing barley ( Hordeum vulgare ) targeting HvCMF7 (conferring green-white variegation) and HvGW2.1 (impacts grain width and weight). BSMV spread systemically throughout barley, inducing somatic and heritable mutations at frequencies up to 100%, with virus-free edited progeny. In contrast, despite robust somatic editing in N. benthamiana, no heritable mutations were detected indicating species-dependent limitations in germline transmission. Our systematic comparison of subgenomic promoter architectures establishes clear design principles for optimizing viral vector–mediated delivery. Promoter choice and transcript structure critically shape editing efficiency and viral stability. The host-specific boundary for germline editing, defined by efficient heritable editing in barley but not N. benthamiana , highlights where BSMV offers advantages and where alternative vectors or hybrid strategies are required, guiding rational platform selection for diverse crop species and applications. Collectively, these findings establish BSMV as a promising next-generation vector for rapid, tissue culture–free, and transformation-independent genome editing in cereals and other recalcitrant monocots.

barley↗

Data and scripts associated with a manuscript investigating dissolved organic matter and microbial community linkages across seven globally distributed rivers

This data package is associated with the publication “Meta-metabolome ecology reveals that geochemistry and microbial functional potential are linked to organic matter development across seven rivers” submitted to Science of the Total Environment. This data package includes the data necessary to replicate the analyses presented within the manuscript to investigate dissolved organic matter (DOM) development across broad spatial distances and within divergent biomes. Specifically, we included the Fourier transform ion cyclotron mass spectrometry (FTICR-MS) data, geochemistry data, annotated metagenomic data, and results from ecological null modeling analyses in this data package. Additionally, we included the scripts necessary to generate the figures from the manuscript. Complete metagenomic data associated with this data package can be found at the National Center for Biotechnology (NCBI) under Bioproject PRJNA946291. This dataset consists of (1) four folders; (2) a file-level metadata (flmd) file; (3) a data dictionary (dd) file; (4) a factor sheet describing samples; and (5) a readme. The FTICR Data folder contains (1) the processed Fourier transform ion cyclotron mass spectrometry (FTICR-MS) data; (2) a transformation-weighted characteristics dendrogram generated from the FTICR-MS data; and (3) the script used to generate all FTICR-MS related figures. The Geochemical Data folder contains (1) the single geochemistry data file and (2) the R script responsible for generating associated figures. The Metagenomic Data folder contains (1) annotation information across different levels; (2) carbohydrate active enzyme (CAZyme) information from the dbCAN database (Yin et al., 2012); (3) phylogenetic tree data (FASTAs, alignments, and tree file); and (4) the scripts necessary to analyze all of these data and generate figures. The Null Modeling Data folder contains (1) data generated during null modeling for each river and all rivers combined and (2) the R scripts necessary to process the data. All files are .csv, .pdf, .tsv, .tre, .faa, .afa, .tree, or .R.

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