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At least 55 records · Page 3

Mass spectrometry-based technologies for probing the 3D world of plant proteins

Abstract Over the past two decades, mass spectrometric (MS)-based proteomics technologies have facilitated the study of signaling pathways throughout biology. Nowhere is this needed more than in plants, where an evolutionary history of genome duplications has resulted in large gene families involved in posttranslational modifications and regulatory pathways. For example, at least 5% of the Arabidopsis thaliana genome (ca. 1,200 genes) encodes protein kinases and protein phosphatases that regulate nearly all aspects of plant growth and development. MS-based technologies that quantify covalent changes in the side-chain of amino acids are critically important, but they only address one piece of the puzzle. A more crucially important mechanistic question is how noncovalent interactions—which are more difficult to study—dynamically regulate the proteome’s 3D structure. The advent of improvements in protein 3D technologies such as cryo-electron microscopy, nuclear magnetic resonance, and X-ray crystallography has allowed considerable progress to be made at this level, but these methods are typically limited to analyzing proteins, which can be expressed and purified in milligram quantities. Newly emerging MS-based technologies have recently been developed for studying the 3D structure of proteins. Importantly, these methods do not require protein samples to be purified and require smaller amounts of sample, opening the wider proteome for structural analysis in complex mixtures, crude lysates, and even in intact cells. These MS-based methods include covalent labeling, crosslinking, thermal proteome profiling, and limited proteolysis, all of which can be leveraged by established MS workflows, as well as newly emerging methods capable of analyzing intact macromolecules and the complexes they form. In this review, we discuss these recent innovations in MS-based “structural” proteomics to provide readers with an understanding of the opportunities they offer and the remaining challenges for understanding the molecular underpinnings of plant structure and function.

Plant Sciences↗

Randomized Federated Learning Methods for Nonsmooth, Nonconvex, and Hierarchical Optimization (Final Technical Report)

This final technical report summarizes the outcomes of a DOE-funded project on federated scientific machine learning (FL) under nonsmooth, nonconvex, and hierarchical optimization settings. The project develops new mathematical models, algorithms, and theoretical guarantees for decentralized stochastic, bilevel, and minimax optimization problems arising in DOE mission-relevant applications. A unified framework of randomized and zeroth-order federated optimization methods is introduced, providing provable convergence, communication efficiency, and sample-complexity guarantees. The report documents algorithmic design, theoretical analysis, and empirical validation of the proposed federated learning methods. The project also contributes to workforce development through graduate training and dissemination of results via publications and seminars.

97 MATHEMATICS AND COMPUTING↗

Hierarchical Phenomena in Multicomponent Liquids: Simulation Methods, Analysis, Chemistry

Complex, multicomponent, solutions have often been studied solely through the lens of specific applications of interest. Yet advances to both simulation methodologies (enhanced sampling, etc.) and analysis techniques (network analysis algorithms and others), are creating a trove of data that reveal transcending characteristics across vast compositional phase space. This perspective discusses technical considerations of the reliable and accurate simulations of complex solutions, followed by the advances to analysis algorithms that elucidate coupling of different length and timescale behavior (hierarchical phenomena). The different manifestations of hierarchical phenomena are presented across an array of solution environments, emphasizing fundamental and ongoing science questions. With a more advanced molecular understanding in hand, a quintessential application (solvent extraction) is discussed, where significant opportunities exist to re-imagine the technical scope of an established technology.

Servis, Michael J.↗

Ultrahigh performance LC/FT-MS non-targeted screening for biomass burning organic aerosol with MZmine2 and MFAssignR

In recent years, ultrahigh performance liquid chromatography Fourier transform mass spectrometry (LC/FT-MS) based non-targeted screening (NTS) methods have become increasingly popular for comprehensive analysis of complex organic mixtures. However, applying these methods for environmental complex mixture analysis is challenging due to the extreme complexity of natural samples and a lack of standard samples or surrogates for environmental complex mixtures. Furthermore, limited molecular markers in the databases and insufficient data processing software workflows make the application of these methods more challenging for environmental complex mixtures. In this work, we implement a new NTS data processing workflow to process data collected from ultrahigh performance liquid chromatography and Fourier transform Orbitrap Elite Mass Spectrometry (LC/FT-MS) by combining MZmine2 and MFAssignR, two opensource data processing tools and commercial Mesquite liquid smoke as a surrogate for biomass burning organic aerosol. MZmine2.53 data extraction followed MFAssignR molecular formula assignment offered noise free and highly accurate 1733 individual molecular formulas presented in liquid smoke with 4906 molecular species, including isomers. The results of this new approach were consistent with the results of direct infusion FT-MS analysis confirming its reliability. Over 90% of the molecular formulas presented in mesquite liquid smoke were matched with the molecular formulas of ambient biomass burning organic aerosol. This suggests the potential use of commercial liquid smoke as a surrogate for biomass burning organic aerosol research. Furthermore, the presented method significantly improves the identification of the molecular composition of biomass burning organic aerosol by successfully addressing some of the limitations related to the data analysis and giving a semi quantitative insight into the analysis.

54 ENVIRONMENTAL SCIENCES↗

Observational window effects on multi-object reverberation mapping

ABSTRACT Contemporary reverberation mapping campaigns are employing wide-area photometric data and high-multiplex spectroscopy to efficiently monitor hundreds of active galactic nuclei (AGNs). However, the interaction of the window function(s) imposed by the observation cadence with the reverberation lag and AGN variability time-scales (intrinsic to each source over a range of luminosities) impact our ability to recover these fundamental physical properties. Time dilation effects due to the sample source redshift distribution introduce added complexity. We present comprehensive analysis of the implications of observational cadence, seasonal gaps, and campaign baseline duration (i.e. the survey window function) for reverberation lag recovery. We find that the presence of a significant seasonal gap dominates the efficacy of any given campaign strategy for lag recovery across the parameter space, particularly for those sources with observed-frame lags above 100 d. Using the Australian Dark Energy Survey as a baseline, we consider the implications of this analysis for the 4MOST/Time-Domain Extragalactic Survey campaign providing concurrent follow-up of the Legacy Survey of Space and Time deep-drilling fields, as well as upcoming programmes. We conclude that the success of such surveys will be critically limited by the seasonal visibility of some potential field choices, but show significant improvement from extending the baseline. Optimizing the sample selection to fit the window function will improve survey efficacy.

79 ASTRONOMY AND ASTROPHYSICS↗

High-resolution ion mobility based on traveling wave structures for lossless ion manipulation resolves hidden lipid features

Abstract High-resolution ion mobility (resolving power > 200) coupled with mass spectrometry (MS) is a powerful analytical tool for resolving isobars and isomers in complex samples. High-resolution ion mobility is capable of discerning additional structurally distinct features, which are not observed with conventional resolving power ion mobility (IM, resolving power ~ 50) techniques such as traveling wave IM and drift tube ion mobility (DTIM). DTIM in particular is considered to be the “gold standard” IM technique since collision cross section (CCS) values are directly obtained through a first-principles relationship, whereas traveling wave IM techniques require an additional calibration strategy to determine accurate CCS values. In this study, we aim to evaluate the separation capabilities of a traveling wave ion mobility structures for lossless ion manipulation platform integrated with mass spectrometry analysis (SLIM IM-MS) for both lipid isomer standards and complex lipid samples. A cross-platform investigation of seven subclass-specific lipid extracts examined by both DTIM-MS and SLIM IM-MS showed additional features were observed for all lipid extracts when examined under high resolving power IM conditions, with the number of CCS-aligned features that resolve into additional peaks from DTIM-MS to SLIM IM-MS analysis varying between 5 and 50%, depending on the specific lipid sub-class investigated. Lipid CCS values are obtained from SLIM IM ( TW(SLIM) CCS) through a two-step calibration procedure to align these measurements to within 2% average bias to reference values obtained via DTIM ( DT CCS). A total of 225 lipid features from seven lipid extracts are subsequently identified in the high resolving power IM analysis by a combination of accurate mass-to-charge, CCS, retention time, and linear mobility-mass correlations to curate a high-resolution IM lipid structural atlas. These results emphasize the high isomeric complexity present in lipidomic samples and underscore the need for multiple analytical stages of separation operated at high resolution. Graphical abstract

Reardon, Allison R. (ORCID:0000000165830134)↗

Measuring Nd(III) Solution Concentration in the Presence of Interfering Er(III) and Cu(II) Ions: A Partial Least Squares Analysis of Ultraviolet–Visible Spectra

Optical spectroscopy is a powerful characterization tool with applications ranging from fundamental studies to real-time process monitoring. However, it can be difficult to apply to complex samples that contain interfering analytes which are common in processing streams. Multivariate (chemometric) analysis has been examined for providing selectivity and accuracy to the analysis of optical spectra and expanding its potential applications. Here we will discuss chemometric modeling with an in-depth comparison to more simplistic analysis approaches and outline how chemometric modeling works while exploring the limits on modeling accuracy. Understanding the limitations of the chemometric model can provide better analytical assessment regarding the accuracy and precision of the analytical result. This will be explored in the context of UV–Vis absorbance of neodymium (Nd 3+ ) in the presence of interferents, erbium (Er 3+ ) and copper (Cu 2+ ) under conditions simulating the liquid–liquid extraction approach used to recycle plutonium (Pu) and uranium (U) in used nuclear fuel worldwide. Finally, the selected chemometric model, partial least squares regression, accurately quantifies Nd 3+ with a low percentage error in the presence of interfering analytes and even under conditions that the training set does not describe.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The influence of point defects on the thermal conductivity of AlN crystals

Here, the average bulk thermal conductivity of free-standing physical vapor transport and hydride vapor phase epitaxy single crystal AlN samples with different impurity concentrations is analyzed using the 3ω method in the temperature range of 30–325K. AlN wafers grown by physical vapor transport show significant variation in thermal conductivity at room temperature with values ranging between 268W/m K and 339W/m K. AlN crystals grown by hydride vapor phase epitaxy yield values between 298W/m K and 341W/m K at room temperature, suggesting that the same fundamental mechanisms limit the thermal conductivity of AlN grown by both techniques. All samples in this work show phonon resonance behavior resulting from incorporated point defects. Samples shown by optical analysis to contain carbon-silicon complexes exhibit higher thermal conductivity above 100K. Lastly, phonon scattering by point defects is determined to be the main limiting factor for thermal conductivity of AlN within the investigated temperature range.

36 MATERIALS SCIENCE↗

Enabling generalized phage therapy to treat secondary infections in COVID-19 (CRADA Final Report)

COVID-19 is a global health threat, with 32 millions infected and more than 500,000 deaths in the U.S. alone. A key aspect of COVID-19 deaths is bacterial secondary infections, with Staphylococcus aureus, Acinetobacter baumannii, and Pseudomonas aeruginosa identified as some of the major causative pathogens. Phage therapy, i.e., the administration of bacteriophages (viruses infecting these bacterial pathogens) to patients offers a complementary solution to antibiotics with multiple key advantages. Felix Biotechnology’s is developing a high-throughput platform to identify phages that not only kill pathogens, but also drive targeted trade-off of pathogenic phenotypes such as reduced virulence and antibiotic resistance, at a fraction of the time and R&D cost of any competitor. In this project, collaboration with scientists from the Lawrence Berkeley National Laboratory enabled Felix Biotechnology to establish robust analysis pipeline to investigate phage-host interactions in complex samples. These should enable a quick and robust identification of promising phages and key genetic determinants for therapy applications, paving the way towards a streamlined and safe use of phages in the clinic.

59 BASIC BIOLOGICAL SCIENCES↗

Investigations of Association Among Atmospheric Radionuclide Measurements

Large networks producing frequent atmospheric radionuclide measurements have additional power in characterizing and localizing radionuclide release events over the analysis done with four or fewer samples. However, adding unrelated samples to an analysis dilutes that advantage, unless models are extended to account for this complexity. A key steppingstone to obtaining network power is to select a group of related sample measurements that are associated with a release event. Such collections of measurements can be assembled by an analyst, or perhaps they can be selected by algorithm. The authors explore, using a year of atmospheric transport calculations and realistic sensor sensitivities, the potential for a computed radionuclide association tool.

Eslinger, Paul W.↗

Rapid Assessment of Contaminants and Interferences in Mass Spectrometry Data Using Skyline

Proper sample preparation in proteomic workflows is essential to the success of modern mass spectrometry experiments. Complex workflows often require reagents which are incompatible with MS analysis (e.g., detergents) necessitating a variety of sample cleanup procedures. Efforts to understand and mitigate sample contamination are a continual source of disruption with respect to both time and resources. To improve the ability to rapidly assess sample contamination from a diverse array of sources, I developed a molecular library in Skyline for rapid extraction of contaminant precursor signals using MS1 filtering. This contaminant template library is easily managed and can be modified for a diverse array of mass spectrometry sample preparation workflows. Utilization of this template allows rapid assessment of sample integrity and indicates potential sources of contamination. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Rapid paper spray mass spectrometry characterization of uranium and exemplar molecular species

The ability to detect and quantify the presence of specific inorganic elements and complexes is essential for environmental monitoring and nuclear safeguards applications. In this work, paper spray ionization mass spectrometry (PSI–MS) was used for the rapid chemical and isotopic characterization of trace inorganic species collected on cotton swipe substrates. Here, the direct analysis of cotton swipes using this ambient ionization technique led to fast sample analysis that retained original chemical information of the source material with minimal sample preparation. Mass spectra were collected on an atmospheric pressure ionization, high–resolution mass spectrometer for solutions containing uranyl acetate, uranyl chloride, uranyl nitrate, and uranyl tri– n –butylphosphate (uranyl–TBP) complexes. Gadolinium nitrate was used as an internal standard for the quantitative analysis of uranium. To demonstrate the ability to characterize inorganic contaminants in the presence of uranium, a multi–element inorganic standard containing U, Bi, Pb, Cd, Fe, and Zn was deposited onto cotton substrates and directly analyzed without purification. All elements doped on the cotton substrate were detected with strong signal–to–noise (S/N) ratios (S/N~1000 for UO 2 + on multi–element doped swipes) and high integrated intensities (>10 5 counts) from collection periods of approximately 1 min. Limits of detection were determined to be approximately 94 ng for UO 2 + and uranyl acetate through the measurement of ppb level solutions. The rapid analysis of uranium and other inorganic–containing samples while still retaining original chemical information (e.g. uranyl complexation) was demonstrated. Qualitative detection and speciation were achieved in less than 1 min of analysis. For uranium isotopic quantitation, longer accumulations (>15 min) can be sustained to improve the accuracy of minor 235 U isotopic abundance measurements to approximately 1% error.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The Geology of The Mt. Simon Sandstone Storage Complex at the Wabash #1 Well, Vigo Co., Indiana (Subtask 7.2, Technical Report)

The Wabash CarbonSAFE project drilled the Wabash #1 stratigraphic test well (ID# 168045) at the Wabash Valley Resources (WVR) IGCC facility in Vigo County, Indiana, to characterize and evaluate the basal Cambrian Mt. Simon Sandstone for commercial-scale CO 2 storage near the site. This report presents an extensive geologic characterization of the Mt. Simon storage complex and relevant data collected from the Wabash #1 well, such as lithologic data collected from cuttings and core, geophysical logging, geomechanical analysis of core samples, and well testing and fluid sampling within the Mt. Simon Sandstone. The Mt. Simon storage complex comprises two major sections: the Mt. Simon Sandstone as the potential reservoir and the overlying Eau Claire Formation as its primary seal. Within the report, an extensive depositional, sedimentological, and geochronologic characterization of the Mt. Simon is included with supportive chapters on the regional geology and the geophysical, petrophysical, and petrologic data collected during the project. An overview of 2D seismic reflection data collected from and around the test well is presented. Also presented are chapters on the characterization of the sealing Eau Claire Formation, including a chapter on the capacity of the primary and secondary seals to the Mt. Simon as well as a chapter on geomechanical testing results of the Eau Claire Formation and Mt. Simon Sandstone. Some of the information discussed in this report was used in the development of static and dynamic geologic models of the Mt. Simon Sandstone storage complex. The static and dynamic modeling of CO 2 injection in the Mt. Simon Sandstone are discussed in a separate report (Dessenberger et al., 2022) under the Wabash CarbonSAFE project.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Historical Data Analysis Supporting the Data Quality Objectives for the INL Site Environmental Soil Monitoring Program

This document represents the initial evaluation and soil monitoring proposed by Battelle Energy Alliance, LLC (BEA) in 2015. The evaluation included analyses of historical soil monitoring data and soil inventories, current emission estimates, and modeled potential deposition/accumulation patterns. The initially proposed monitoring included a 5-year rotation of in-situ gamma measurements augmented by soil sampling with laboratory analyses near each major active and some inactive facilities. It also proposed rotational in-situ gamma measurements and soil sampling at two centrally located onsite air monitoring locations coinciding with sampling at the traditional offsite soil monitoring locations. The chosen alternative includes only physical soil sampling with laboratory analysis and only at the Radioactive Waste Management Complex (RWMC), the two air monitors and the offsite locations as documented in Data Quality Objectives Supporting the Environmental Soil Monitoring Program for the Idaho National Laboratory (INL) Site, INL/EXT-15-34909, Revision 0, February 2016. The data and evaluations in this document are valid for comparisons with future soil data that may be collected in many INL site locations.

54 ENVIRONMENTAL SCIENCES↗

Atom Probe Tomography for Catalysis Applications: A Review

Atom probe tomography is a well-established analytical instrument for imaging the 3D structure and composition of materials with high mass resolution, sub-nanometer spatial resolution and ppm elemental sensitivity. Thanks to recent hardware developments in Atom Probe Tomography (APT), combined with progress on site-specific focused ion beam (FIB)-based sample preparation methods and improved data treatment software, complex materials can now be routinely investigated. From model samples to complex, usable porous structures, there is currently a growing interest in the analysis of catalytic materials. APT is able to probe the end state of atomic-scale processes, providing information needed to improve the synthesis of catalysts and to unravel structure/composition/reactivity relationships. This review focuses on the study of catalytic materials with increasing complexity (tip-sample, unsupported and supported nanoparticles, powders, self-supported catalysts and zeolites), as well as sample preparation methods developed to obtain suitable specimens for APT experiments.

36 MATERIALS SCIENCE↗

High-Field One-Dimensional and Two-Dimensional 27Al Magic-Angle Spinning Nuclear Magnetic Resonance Study of ?-, d-, and ?-Al2O3 Dominated Aluminum Oxides: Toward Understanding the Al Sites in ?-Al2O3

Herein, a detailed analysis was carried out using high-field (19.9 T) 27Al magic-angle spinning (MAS) nuclear magnetic resonance (NMR) on three specially prepared aluminum oxide samples where the ?-, d-, and ?-Al2O3 phases are dominantly expressed through careful control of the synthesis conditions. Specifically, two-dimensional (2D) multiquantum (MQ) MAS 27Al was used to obtain high spectral resolution, which provided a guide for analyzing quantitative 1D 27Al NMR spectra. Six aluminum sites were resolved in the 2D MQ MAS NMR spectra, and seven aluminum sites were required to fit the 1D spectra. A set of octahedral and tetrahedral peaks with well-defined quadrupolar line shapes was observed in the ?-phase dominant sample and was unambiguously assigned to the ?-Al2O3 phase. The distinct line shapes related to the ?-Al2O3 phase provided an opportunity for effectively deconvoluting the more complex spectrum obtained from the d-Al2O3 dominant sample, allowing the peaks/quadrupolar parameters related to the d-Al2O3 phase to be extracted. The results show that the d-Al2O3 phase contains three distinct AlO sites and three distinct AlT sites. This detailed Al site structural information offers a powerful way of analyzing the most complex ?-Al2O3 spectrum. It is found that the ?-Al2O3 phase consists of Al sites with local structures similar to those found in the d-Al2O3 and ?-Al2O3 phases albeit with less ordering. Spin–lattice relaxation time measurement further confirms the disordering of the lattice. Collectively, this study uniquely assigns 27Al features in transition aluminas, offering a simplified method to quantify complex mixtures of aluminum sites in transition alumina samples.

Xu, Suochang↗

Novel data analysis method for obtaining better performance from a complex 3D-printed collimator

Additively manufactured scattered beam collimators are increasingly being employed to boost the sample to cell peak signal ratio in high pressure neutron diffraction studies because of manufacturing versatility and performance improvements. We study how the measured diffraction pattern is affected by the presence of a collimator downstream of the sample, and develop a novel protocol that provides more effective background rejection. This protocol takes into account critical performance-determinants that were identified in this study, namely: (i) effectively identifying the collimator pattern on the detector; (ii) understanding the dependence of this pattern on sample and cell composition; and (iii) accurately identifying and differentiating the different regions of the pattern on the detector based on the dependency of the cell or sample and finally (iv) resolving the intensities at regions of the detector where neutrons scattered from the sample are preferentially represented, in order to boost the sample to cell peak signal ratio. Application of this novel analysis protocol is shown to increase the collimator performance over the traditional method.

3D printing↗

Using Numba for GPU acceleration of Neutron Beamline Digital Twins

Digital twins of neutron instruments using Monte Carlo ray tracing have proven to be useful in neutron data analysis and verifying instrument and sample designs. However, these simulations can become quite complex and computationally demanding with tens of billions of neutrons. In this paper, we present a GPU accelerated version of MCViNE using Python and Numba to balance user extensibility with performance. Numba is an open-source just-in-time (JIT) compiler for Python using LLVM to generate efficient machine code for CPUs and GPUs with NVIDIA CUDA. The JIT nature of Numba allowed complex instrument kernels to be generated easily. Initial simulations have shown a speedup between 200-1000x over the original CPU implementation. The performance gain with Numba enables more sophisticated data analysis and impacts neutron scattering science and instrument design.

Kendrick, Coleman↗