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At least 181 records · Page 10

A stable 15-member bacterial SynCom promotes Brachypodium growth under drought stress

Introduction: Rhizosphere microbiomes are known to drive soil nutrient cycling and influence plant fitness during adverse environmental conditions. Field-derived robust Synthetic Communities (SynComs) of microbes mimicking the diversity of rhizosphere microbiomes can greatly advance a deeper understanding of such processes. However, assembling stable, genetically tractable, reproducible, and scalable SynComs remains challenging. Methods: Here, we present a systematic approach using a combination of network analysis and cultivation-guided methods to construct a 15-member SynCom from the rhizobiome of Brachypodium distachyon. This SynCom incorporates diverse strains from five bacterial phyla. Genomic analysis of the individual strains was performed to reveal encoded plant growth-promoting traits, including genes for the synthesis of osmoprotectants (trehalose and betaine) and Na+/K+ transporters, and some predicted traits were validated by laboratory phenotypic assays. Results: The SynCom demonstrates strong stability both in vitro and in planta. Most strains encoded multiple plant growth-promoting functions, and several of these were confirmed experimentally. The presence of osmoprotectant and ion transporter genes likely contributed to the observed resilience of Brachypodium to drought stress, where plants amended with the SynCom recovered better than those without. We further observed preferential colonization of SynCom strains around root tips under stress, likely due to active interactions between plant root metabolites and bacteria. Discussion: Our results demonstrate that trait-informed construction of synthetic communities can yield stable, functionally diverse consortia that enhance plant resilience under drought. Preferential colonization near root tips points to active, localized plant-microbe signaling as a component of stress-responsive recruitment. This stable SynCom provides a scalable platform for probing mechanisms of plant-microbe interaction and for developing microbiome-based strategies to improve soil and crop performance in variable environments.

Yadav, Archana↗

Tetracene Functionalized Si(111) Achieves Enhanced Solar-to-Chemical Energy Conversion via Molecular Acceptor States

The properties of semiconductor|liquid interfaces play a critical role in determining the efficiency of solar-to-hydrogen (STH) conversion. Here, we investigate how molecular functionalization of Si(111) and Si(111)|TiO 2 surfaces impacts photoelectrochemical (PEC) hydrogen production efficiency. We find that functionalization of ∼3% of the atop sites of Si(111) with either 9-anthracene (Anth) or 5-tetracene (Tet), with the remaining sites passivated by methyl groups, provides substrates with high electronic quality and low surface oxide densities, as determined by X-ray photoelectron spectroscopy (XPS) measurements. Surface photovoltage (SPV) spectroscopy shows that surfaces modified with Anth or Tet exhibit an increased photovoltage, with Tet-functionalized surfaces yielding an additional 192 meV relative to methyl-terminated Si(111), indicating improved charge separation for Si-Tet. Further improvement in onset potential was achieved by replacing a nitrogen-containing TiO 2 atomic layer deposition (ALD) precursor (TDMAT) with a precursor lacking nitrogen (TTIP), which eliminates the parasitic defect band in the TiO 2 overlayer (p-Si(111)-Tet|TTIP-TiO 2 |Pt: V OC = +0.283 ± 0.041 V vs RHE). Density functional theory (DFT) analysis demonstrates that compared with Anth-modified Si(111), the Tet-modified surface exhibits more hybridized Si(111)-Tet states closer to the silicon band edges. Mercury contact current–voltage (I–V, dark) measurements quantified the relative interfacial density of states of Si-Tet, Si-Anth and Si-Me surfaces─revealing that the interfacial state density was highest for Si-Tet. This suggests that such hybridized interfaces serve to capture better photoexcited charge, which enables facile electron transfer to molecular acceptors in solution. Altogether, the data indicate that beneficial hybrid molecular LUMO surface states interacting with the Si conduction band edge results in improved hydrogen evolution (HER) performance for p-Si devices.

Group theory↗

Optical properties of intact leaves for estimating chlorophyll concentration

Changes in leaf chlorophyll content can serve as relative indicators of plant vigor and environmental quality. This study identified reflectance, transmittance, and absorptance wavebands and band ratios within the 400- to 850-nm range for intact leaves that could be used to estimate extracted leaf chlorophyll per unit leaf area (areal concentration) with minimal error. Leaf optical properties along with chlorophyll a, b, and a + b concentrations were measured for the planar-leaved sweetgum (Liquidambar styraciflua L.), red maple (Acer rubrum L.), wild grape (Vitis rotundifolia Michx.), and switchcane [Arundinaria gigantea (Walter) Muhl.], and for needles of longleaf pine (Pinus palustris Miller). Generally, reflectance, transmittance, and absorptance corresponded most precisely with chlorophyll concentrations at wavelengths near 700 nm, although regressions were also strong in the 550- to 625-nm range. A power function was superior to a simple linear function in yielding low standard deviations of the estimate (s). When data were combined among the planar-leaved species, s values were low at approximately 50 mumol/m2 out of a 940 mumol/m2 range in chlorophyll a + b at best-fit wavelengths of 707 to 709 nm. Minimal s values for chlorophyll a + b ranged from 32 to 62 mumol/m2 across species when band ratios having numerator wavelengths of 693 to 720 nm were used with the application of a power function. Optimal denominator wavelengths for the band ratios were 850 nm for reflectance and transmittance and 400 nm for absorptance. This information can be applied in designing field portable chlorophyll meters and in the landscape-scale remote sensing of plant responses to the environment.

Chlorophyll/analysis↗

Potential Carbon Negative Commercial Aviation through Land Management

Brazilian terra preta soil and char-enhanced soil agricultural systems have demonstrated both enhanced plant biomass and crop yield and functions as a carbon sink. Similar carbon sinking has been demonstrated for both glycophyte and halophyte plants and plant roots. Within the assumption of 3.7 t-C/ha/yr soils and plant root carbon sinking, it is possible to provide carbon neutral U.S. commercial aviation using about 8.5% of U.S. arable lands. The total airline CO2 release would be offset by carbon credits for properly managed soils and plant rooting, becoming carbon neutral for carbon sequestered synjet processing. If these lands were also used to produce biomass fuel crops such as soybeans at an increased yield of 60 bu/acre (225gal/ha), they would provide over 3.15 10(exp 9) gallons biodiesel fuel. If all this fuel were refined into biojet it would provide a 16% biojet-84% synjet blend. This allows the U.S. aviation industry to become carbon negative (carbon negative commercial aviation through carbon credits). Arid land recovery could yield even greater benefits.

Hendricks, Robert C.↗

Modeling the physisorption of graphene on metals

Many processes of technological and fundamental importance occur on surfaces. Adsorption is one of these phenomena that has received the most attention. However, it presents a great challenge to conventional density functional theory. By starting with the Lifshitz-Zaremba-Kohn second-order perturbation theory, we develop a long-range van der Waals (vdW) correction for physisorption of graphene on metals. The model importantly includes quadrupole-surface interaction and screening effects. The results show that, when the vdW correction is combined with the Perdew-Burke-Enzerhof functional, it yields adsorption energies in good agreement with the random-phase approximation, significantly improving upon other vdW methods. We also find that, compared with the leading-order interaction, the higher-order quadrupole-surface correction accounts for about 25$\%$ of the total vdW correction, suggesting the importance of the higher-order term.

36 MATERIALS SCIENCE↗

Input Shaping to Reduce Solar Array Structural Vibrations

Structural vibrations induced by actuators can be minimized using input shaping. Input shaping is a feedforward method in which actuator commands are convolved with shaping functions to yield a shaped set of commands. These commands are designed to perform the maneuver while minimizing the residual structural vibration. In this report, input shaping is extended to stepper motor actuators. As a demonstration, an input-shaping technique based on pole-zero cancellation was used to modify the Solar Array Drive Assembly (SADA) actuator commands for the Lewis satellite. A series of impulses were calculated as the ideal SADA output for vibration control. These impulses were then discretized for use by the SADA stepper motor actuator and simulated actuator outputs were used to calculate the structural response. The effectiveness of input shaping is limited by the accuracy of the knowledge of the modal frequencies. Assuming perfect knowledge resulted in significant vibration reduction. Errors of 10% in the modal frequencies caused notably higher levels of vibration. Controller robustness was improved by incorporating additional zeros in the shaping function. The additional zeros did not require increased performance from the actuator. Despite the identification errors, the resulting feedforward controller reduced residual vibrations to the level of the exactly modeled input shaper and well below the baseline cases. These results could be easily applied to many other vibration-sensitive applications involving stepper motor actuators.

Doherty, Michael J.↗

Batch Effect Correction Methods for NASA GeneLab Transcriptomic Datasets

RNA sequencing (RNA-seq) data from space biology experiments promise to yield invaluable insights into the effects of spaceflight on terrestrial biology. However, sample numbers from each study are low due to limited crew availability, hardware, and space. To increase statistical power, spaceflight RNA-seq datasets from different missions are often aggregated together. However, this can introduce technical variation or "batch effects", often due to differences in sample handling, sample processing, and sequencing platforms. Several computational methods have been developed to correct for technical batch effects, thereby reducing their impact on true biological signals. In this study, we combined 7 mouse liver RNA-seq datasets from NASA GeneLab (part of the NASA Open Science Data Repository) to evaluate several common batch effect correction methods (ComBat and ComBat-seq from the sva R package, and Median Polish, Empirical Bayes, and ANOVA from the MBatch R package). We quantitatively evaluated the ability of these methods to correct for technical batch variables in space biology RNA-seq data using the following criteria: BatchQC, principal component analysis, dispersion separability criterion, log fold change correlation, and differential gene expression analysis. Each batch variable / correction method combination was then assessed using a custom scoring approach to identify the optimal correction method for the combined dataset, by geometrically probing the space of all allowable scoring functions to yield an aggregate volume-based scoring measure. Finally, we describe the way in which the GeneLab multi-study analysis and visualization portal will allow users to examine the presence or absence of batch effects using multiple metrics. If the user chooses to perform batch effect correction, the scoring approach described here can be implemented to identify the optimal correction method to use for their specific combined dataset prior to analysis.

Lauren M. Sanders↗

A matheuristic for design and dispatch of a utility-connected distributed energy system

Modeling distributed power generation systems often requires complicated mathematical expressions that present challenges for commercial optimization solvers. Here, this paper presents a matheuristic to solve a mixed-integer optimization model that informs decisions regarding the design and dispatch of a utility-connected microgrid. We deploy a genetic algorithm to search the system design space and a linear program to solve the economic dispatch problem. The model is a component of a web tool that requires solutions within a few minutes. Our method yields objective function values within 5% of an exogenously produced optimal in fewer than 30 seconds for 90% of our test cases compared to only 10% of our test cases by a traditional optimization solver in the same amount of time.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Large-scale production of 88 Y and 88 Zr/ 88 Y generators: A proof of concept study for a 70 MeV H – cyclotron

Here, the large-scale production of 88 Y with proton-induced reactions has been investigated from the perspective of new generation 70 MeV H – cyclotrons. Tandem target configurations are presented for both the direct production of 88 Y as well as for producing 88 Zr/ 88 Y generators. Based on the relevant excitation functions, physical yields have been derived for 88 Y production with Y 2 O 3 /SrCO 3 tandem targets and 88 Zr production with Zr/Y 2 O 3 tandem targets. Yields are presented for optimized targets (i.e. optimum yield) as well as for balanced thermal loads on the individual targets. Liquid 88 Zr/ 88 Y generators have been produced using both natural Zr and Nb target materials, the former for dedicated productions and the latter as a byproduct by processing spent irradiated Nb capsules which normally would constitute radioactive waste. These stock solutions, which contain both the target material and 88 Zr precursor, are retained virtually unchanged after processing except for the removal of 88 Y on AG MP-50 macroporous cation-exchange resin. Methods are presented for the preparation of Nb stock solutions in hydrofluoric acid and Zr stock solutions in sulfuric acid. It is shown that multi-Ci productions of 88 Y are feasible at a 70 MeV cyclotron facility, suitable for the needs of fracking applications. In addition, 88 Zr/ 88 Y generators can provide 88 Y with very high specific activity, suitable for labelling of biomolecules.

07 ISOTOPE AND RADIATION SOURCES↗

Proteomics-Based Tools for Evaluation of Cell-Free Protein Synthesis

Cell-free protein synthesis (CFPS) has the potential to produce enzymes, therapeutic agents, and other proteins, while circumventing difficulties associated with in vivo heterologous expression. However, the contents of the cell-free extracts used to carry out synthesis are generally not characterized, which hampers progress toward enhancing yield or functional activity of the target protein. Here we explored the utility of mass spectrometry (MS)-based proteomics for characterizing the bacterial extracts used for transcribing and translating gene sequences into proteins as well as the products of CFPS reactions. Full proteome experiments identified over 1000 proteins per reaction. The complete set of proteins necessary for transcription and translation were found, demonstrating the ability to define potential metabolic capabilities of the extract. Further, MS-based techniques allowed characterization of the CFPS product and provided insight into the synthesis reaction and potential functional activity of the product. These capabilities were demonstrated using two different CFPS products, the commonly used standard green fluorescent protein (GFP, 27 kDa) and the polyketide synthase DEBS1 (394 kDa). For the large, multidomain DEBS1, substantial premature termination of protein translation was observed. Additionally, MS/MS analysis, as part of a conventional full proteomics workflow, identified post-translational modifications, including the chromophore in GFP, as well as the three phosphopantetheinylation sites in DEBS1. A hypothesis-driven approach focused on these three sites identified that all were correctly modified for DEBS1 expressed in vivo but with less complete coverage for protein expressed in CFPS reactions. These post-translational modifications are essential for functional activity, and the ability to identify them with mass spectrometry is valuable for judging the success of the CFPS reaction. Collectively, the use of MS-based proteomics will prove advantageous for advancing the application of CFPS and related techniques.

59 BASIC BIOLOGICAL SCIENCES↗

Solving the Trivial Crossing Problem While Preserving the Nodal Symmetry of the Wave Function

In an adiabatic mixed quantum-classical simulation, the avoided crossing of weakly coupled eigenstates can lead to unphysical discontinuities in wave function dynamics, otherwise known as the trivial crossing problem. A standard solution to the trivial crossing problem eliminates spatial discontinuities in wave function dynamics by imposing changes to the eigenstate of the wave function. In this paper, we show that this solution has the side effect of introducing transient discontinuities in the nodal symmetry of the wave function. We present an alternative solution to the trivial crossing problem that preserves both the spatial and nodal structure of the adiabatic wave function. By considering a model of exciton dynamics on conjugated polymer systems, we show that failure to preserve wave function symmetry yields exciton dynamics that depends unphysically on polymer system size. We demonstrate that our symmetry-preserving solution to the trivial crossing problem yields more realistic dynamics and can thus improve the accuracy of simulations of larger systems that are prone to the trivial crossing problem.

74 ATOMIC AND MOLECULAR PHYSICS↗

Baseflow Identification via Explainable AI With Kolmogorov‐Arnold Networks

Abstract Hydrological models often involve constitutive laws that may not be optimal in every application. We propose to replace such laws with the Kolmogorov‐Arnold networks (KANs), a class of neural networks designed to identify symbolic expressions. We demonstrate KAN's potential on the problem of baseflow identification, a notoriously challenging task plagued by significant uncertainty. KAN‐derived functional dependencies of the baseflow components on the aridity index outperform their original counterparts; they demonstrate that water availability, rather than potential evapotranspiration, drives baseflow by constraining actual evapotranspiration under arid conditions. On a test set, they increase the Nash‐Sutcliffe efficiency (NSE) by 65%, decrease the root mean squared error by 29%, and increase the Kling‐Gupta efficiency by 34%. This superior performance is achieved while reducing the number of fitting parameters from three to two. Next, we use data from 378 catchments across the continental United States to refine the water‐balance equation at the mean‐annual scale. The KAN‐derived equations based on the refined water balance outperform both the current aridity index model, with up to a 105% increase in NSE, and the KAN‐derived equations based on the original water balance. While the performance of our model and tree‐based machine learning methods is similar, KANs offer the advantage of simplicity and transparency and require no specific software or computational tools. This case study focuses on the aridity index formulation, but the approach is flexible and transferable to other hydrological processes. Plain Language Summary Equations used in hydrologic model are often suboptimal, resulting in reduced prediction accuracy and efficiency. We implemented Kolmogorov‐Arnold networks (KAN), a machine learning algorithm for deriving symbolic formulations, to estimate groundwater recharge and showed that it outperforms an existing state‐of‐the‐art semi‐empirical formulation. In hydrology, Nash‐Sutcliffe efficiency (NSE), root mean squared error (RMSE), and Kling‐Gupta efficiency (KGE) are commonly used to evaluate model performance. Higher NSE and KGE values indicate better performance, while lower RMSE values are preferable. Our results show that NSE increased by 71%, RMSE decreased by 32%, and KGE improved by 25%. In addition, KAN identifies an optimal functional form and can be used to derive new analytical formulas using the prior knowledge. The KAN‐inspired equation outperformed the original formulation and reduced the fitting parameters. Furthermore, we refined the water‐balance equation at the mean‐annual scale and showed that, based on the new water‐balance equation, KAN can derive new formulations that are superior to the original aridity index formulations (up to 105% increase in NSE) and KAN‐derived equations based on the original water balance. These findings highlight the significant potential of KAN to advance the scientific understanding of a wide range of hydrologic processes. Key Points Kolmogorov‐Arnold networks (KANs) enhance interpretability of machine‐learned hydrological models KAN‐derived symbolic formulations outperform state‐of‐the‐art semi‐empirical aridity indices KAN‐identified functional form yields an analytical index with fewer fitting parameters and improved performance

baseflow↗

SuFExable polymers with helical structures derived from thionyl tetrafluoride

Sulfur(VI) fluoride exchange (SuFEx) is a category of click chemistry that enables covalent linking of modular units through sulfur(VI) connective hubs. The efficiency of SuFEx and the stability of the resulting bonds have led to polymer chemistry applications. Now, we report the SuFEx click chemistry synthesis of several structurally diverse SOF 4 -derived copolymers based on the polymerization of bis(iminosulfur oxydifluorides) and bis(aryl silyl ethers). This polymer class presents two key characteristics. First, the [-N=S(=O)F-O-] polymer backbone linkages are themselves SuFExable and undergo precise SuFEx-based post-modification with phenols or amines to yield branched functional polymers. Second, studies of individual polymer chains of several of these new materials indicate helical polymer structures. The robust nature of SuFEx click chemistry offers the potential for post-polymerization modification, enabling the synthesis of materials with control over composition and conformation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mechanism of NMDA receptor channel block by MK-801 and memantine

The NMDA (N-methyl-d-aspartate) receptor transduces the binding of glutamate and glycine, coupling it to the opening of a calcium-permeable ion channel. Owing to the lack of high-resolution structural studies of the NMDA receptor, the mechanism by which ion-channel blockers occlude ion permeation is not well understood. Here we show that removal of the amino-terminal domains from the GluN1–GluN2B NMDA receptor yields a functional receptor and crystals with good diffraction properties, allowing us to map the binding site of the NMDA receptor blocker, MK-801. Here, this crystal structure, together with long-timescale molecular dynamics simulations, shows how MK-801 and memantine (a drug approved for the treatment of Alzheimer’s disease) bind within the vestibule of the ion channel, promote closure of the ion channel gate and lodge between the M3-helix-bundle crossing and the M2-pore loops, physically blocking ion permeation.

59 BASIC BIOLOGICAL SCIENCES↗

Targeting colorectal cancer with small-molecule inhibitors of ALDH1B1

Aldehyde dehydrogenases (ALDHs) are promising cancer drug targets, as certain isoforms are required for the survival of stem-like tumor cells. We have discovered selective inhibitors of ALDH1B1, a mitochondrial enzyme that promotes colorectal and pancreatic cancer. We describe bicyclic imidazoliums and guanidines that target the ALDH1B1 active site with comparable molecular interactions and potencies. Both pharmacophores abrogate ALDH1B1 function in cells; however, the guanidines circumvent an off-target mitochondrial toxicity exhibited by the imidazoliums. Our lead isoform-selective guanidinyl antagonists of ALDHs exhibit proteome-wide target specificity, and they selectively block the growth of colon cancer spheroids and organoids. Finally, we have used genetic and chemical perturbations to elucidate the ALDH1B1-dependent transcriptome, which includes genes that regulate mitochondrial metabolism and ribosomal function. Our findings support an essential role for ALDH1B1 in colorectal cancer, provide molecular probes for studying ALDH1B1 functions and yield leads for developing ALDH1B1-targeting therapies.

36 MATERIALS SCIENCE↗

An assessment of low-lying excitation energies and triplet instabilities of organic molecules with an ab initio Bethe-Salpeter equation approach and the Tamm-Dancoff approximation

The accurate prediction of singlet and triplet excitation energies is an area of intense research of significant fundamental interest and critical for many applications. Most calculations of singlet and triplet energies use time-dependent density functional theory (TDDFT) in conjunction with an approximate exchange-correlation functional. In this work, we examine and critically assess an alternative method for predicting low-lying neutral excitations with similar computational cost, the ab initio Bethe-Salpeter equation (BSE) approach, and compare results against high-accuracy wavefunction-based methods. We consider singlet and triplet excitations of 27 prototypical organic molecules, including members of Thiel’s set, the acene series, and several aromatic hydrocarbons exhibiting charge-transfer-like excitations. Analogous to its impact in TDDFT, we find that the Tamm-Dancoff approximation (TDA) overcomes triplet instabilities in the BSE approach, improving both triplet and singlet energetics relative to higher level theories. Lastly, we find that BSE-TDA calculations built on effective DFT starting points, such as those utilizing optimally tuned range-separated hybrid functionals, can yield accurate singlet and triplet excitation energies for gas-phase organic molecules.

74 ATOMIC AND MOLECULAR PHYSICS↗

An analytic and complete equation of state for condensed phase materials

Analytic equations of state (EOS) are intended to reproduce theoretical and experimental data in a single phase portion of the thermodynamic space. We devise a complete and thermodynamically consistent model with four distinct features: (1) a reference isotherm that remains thermodynamically stable, (2) a flexible specific heat model based on a fourth-order rational polynomial, (3) a Grüneisen parameter that depends on specific volume and temperature, and (4) pressure and internal energy functions that can be inverted analytically in temperature. The model aims to improve the accuracy of existing equations of state while remaining computationally efficient. To demonstrate its features, we include calibrations for single-crystal pentaerythritol tetranitrate (PETN), liquid nitromethane (NM), and hexagonal close-packed beryllium (Be) metal. The parameter optimization uses the specific heat capacity, Grüneisen parameter, and static compression curves obtained from density functional theory for the crystalline solids and molecular dynamics simulations for liquid NM. We also present a velocity autocorrelation function that yields accurate phonon densities of states for the EOS calibration from the molecular dynamics trajectories. Each of the three calibrations is constrained to enforce the ambient state from experimental measurements and validated against experimental Hugoniot data from multiple sources. We also include one-dimensional hydrodynamic simulations of the isentropic compression experiments for beryllium conducted at the Z facility.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗