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At least 865 records · Page 48

Discovery of Proteoforms Associated With Alzheimer's Disease Through Quantitative Top-Down Proteomics

The complex nature of Alzheimer's disease (AD) and its heterogenous clinical presentation has prompted numerous large-scale - omic analyses aimed at providing a global understanding of the pathophysiological processes involved. AD involves isoforms, proteolytic products, and posttranslationally modified proteins such as amyloid beta (Aβ) and microtubule-associated protein tau. Top-down proteomics directly measures these species and thus, offers a comprehensive view of pathologically relevant proteoforms that are difficult to analyze using traditional proteomic techniques. Here, we broadly explored associations between proteoforms and clinicopathological traits of AD by deploying a quantitative top-down proteomics approach across frontal cortex of 103 subjects selected from the ROS and MAP cohorts. The approach identified 1213 proteins and 11,782 proteoforms, of which 154 proteoforms had at least one significant association with a clinicopathological phenotype. One important finding included identifying Aβ C-terminal truncation state as the key property for differential association between amyloid plaques and cerebral amyloid angiopathy. Furthermore, various N-terminally truncated forms of Aβ had noticeably stronger association with amyloid plaques and global cognitive function. Additionally, we discovered six VGF neuropeptides that were positively associated with cognitive function independent of pathological burden. The database of brain cortex proteoforms provides a valuable context for functional characterization of the proteins involved in AD and other late-onset brain pathologies.

60 APPLIED LIFE SCIENCES↗

Sustainable Critical Minerals: Mining, Production, and Legacy

Critical minerals (CMs) are required in renewable energy systems, electric vehicles, electronics, and national defense. Global demand has increased rapidly due to energy and digital transitions, and the United States has become increasingly reliant on vulnerable supply chains. Geological scarcity, trade barriers, environmental hurdles, and processing challenges impede domestic CM production growth. Emerging strategies, including circular economy practices and advanced sustainable mining and processing techniques, can mitigate supply chain and economic risks. To advance these approaches, consistent research priorities, policy revisions, and technology investments are required to develop a resilient CM supply. Doing so with a focus on sustainability goals can simultaneously advance domestic economic and technological goals while limiting environmental impacts and supporting global environmental goals.

biomining↗

Magic Diamond: Covalent Bond Formation of Melamine and Other Amines on Nanodiamond Surfaces

High-temperature, high-pressure (HPHT) nanodiamond (ND) hosts nitrogen-vacancy (NV) centers, solid-state qubits that enable room-temperature quantum sensing by all-optical magnetometry, electrometry, and thermometry. However, the covalent surface functionalization of nanoscale diamond remains largely limited to carboxylate-based chemistries. Amine termination is particularly attractive because theoretical studies predict suppression of midgap states and extended electron-spin coherence times. Recently, chemical activation of alcohol-terminated NDs to alkyl bromides (ND-Br) using SOBr2 has enabled nucleophilic substitution through a carbocation intermediate, allowing formation of simple amine terminations. Here, we evaluate whether sterically demanding amines can form covalent diamond−nitrogen bonds on ND-Br surfaces. ND-Br was reacted with branched, linear, and cyclic amines, including polyethylenimine, diethylenetriamine, and melamine. X-ray spectroscopies were used to confirm successful and to probe the resulting electronic structure at the diamond−amine interface. These results expand the chemical toolbox for tuning diamond surface dipoles and electron affinity, providing new pathways for engineering nanodiamond surfaces for quantum sensing and photocatalysis applications.

Amines↗

Anisotropic Melt Inclusions as a Confounding Signal for Ice‐Penetrating Radar Observations

Ice-penetrating radar is a powerful geophysical tool for understanding the subsurfaces of Earth, Mars, and icy moons. Radar reflectivity, attenuation, and birefringence are used to infer subsurface hydrology, englacial temperature, water content, and crystal orientation fabric. However, conventional radar sounding analyses either ignore melt or use classical mixing models which assume spherical melt inclusions, obscuring anisotropic contributions of melt. Here, we use geometric mixing models to calculate the reflectivity, attenuation, and birefringence of temperate ice containing anisotropic melt. We find that anisotropic melt can introduce significant deviations in radar measurements. For instance, melt anisotropy may impact reflectivity-based estimates of water content by up to 30% volume fraction, while attenuation-based estimates may vary by up to 43%. Critically, a melt volume fraction of just $f$ ~ 10 -5 can reproduce birefringence signals previously attributed to ice fabric. We conclude that melt anisotropy may significantly impact analyses of englacial hydrology, subglacial hydrology, and ice fabric.

58 GEOSCIENCES↗

Future increase in compound soil drought-heat extremes exacerbated by vegetation greening

Compound soil drought and heat extremes are expected to occur more frequently with global warming, causing wide-ranging socio-ecological repercussions. Vegetation modulates air temperature and soil moisture through biophysical processes, thereby influencing the occurrence of such extremes. Global vegetation cover is broadly expected to increase under climate change, but it remains unclear whether vegetation greening will alleviate or aggravate future increases in compound soil drought-heat events. Here, using a suite of state-of-the-art model simulations, we show that the projected vegetation greening will increase the frequency of global compound soil drought-heat events, equivalent to 12-21% of the total increment at the end of 21st century. This increase is predominantly driven by reduced albedo and enhanced transpiration associated with increased leaf area. Although greening-induced transpiration enhancement has counteracting cooling and drying effects, the excessive water loss in the early growing season can lead to later soil moisture deficits, amplifying compound soil drought-heat extremes during the subsequent warm season. These changes are most pronounced in northern high latitudes and are dominated by the warming effect of CO 2 . Our study highlights the necessity of integrating vegetation biophysical effects into mitigation and adaptation strategies for addressing compound climate risks.

54 ENVIRONMENTAL SCIENCES↗

Science acceleration and accessibility with self-driving labs

In the evolving landscape of scientific research, the complexity of global challenges demands innovative approaches to experimental planning and execution. Self-Driving Laboratories (SDLs) automate experimental tasks in chemical and materials sciences and the design and selection of experiments to optimize research processes and reduce material usage. This perspective explores improving access to SDLs via centralized facilities and distributed networks. We discuss the technical and collaborative challenges in realizing SDLs’ potential to enhance human–machine and human–human collaboration, ultimately fostering a more inclusive research community and facilitating previously untenable research projects.

Canty, Richard B. [North Carolina State University↗

Cholesterol modulates membrane elasticity via unified biophysical laws

Cholesterol and lipid unsaturation underlie a balance of opposing forces that features prominently in adaptive cell responses to diet and environmental cues. These competing factors have resulted in contradictory observations of membrane elasticity across different measurement scales, requiring chemical specificity to explain incompatible structural and elastic effects. Here, we demonstrate that – unlike macroscopic observations – lipid membranes exhibit a unified elastic behavior in the mesoscopic regime between molecular and macroscopic dimensions. Using nuclear spin techniques and computational analysis, we find that mesoscopic bending moduli follow a universal dependence on the lipid packing density regardless of cholesterol content, lipid unsaturation, or temperature. Our observations reveal that compositional complexity can be explained by simple biophysical laws that directly map membrane elasticity to molecular packing associated with biological function, curvature transformations, and protein interactions. The obtained scaling laws closely align with theoretical predictions based on conformational chain entropy and elastic stress fields. These findings provide unique insights into the membrane design rules optimized by nature and unlock predictive capabilities for guiding the functional performance of lipid-based materials in synthetic biology and real-world applications.

Kumarage, Teshani [Virginia Polytechnic Inst. and ↗

A global dataset of terrestrial biological nitrogen fixation

Biological nitrogen fixation (BNF) is the main natural source of new nitrogen inputs in terrestrial ecosystems, supporting terrestrial productivity, carbon uptake, and other Earth system processes. We assembled a comprehensive global dataset of field measurements of BNF in all major N-fixing niches across natural terrestrial biomes derived from the analysis of 376 BNF studies. The dataset comprises 32 variables, including site location, biome type, N-fixing niche, sampling year, quantification method, BNF rate (kg N ha −1 y −1 ), the percentage of nitrogen derived from the atmosphere (%N dfa ), N fixer or N-fixing substrate abundance, BNF rate per unit of N fixer abundance, and species identity. Overall, the dataset combines 1,207 BNF rates for trees, shrubs, herbs, soil, leaf litter, woody litter, dead wood, mosses, lichens, and biocrusts, 152 herb %N dfa values, 1,005 measurements of N fixer or N-fixing substrate abundance, and 762 BNF rates per unit of N fixer abundance for a total of 424 species across 66 countries. This dataset facilitates synthesis, meta-analysis, upscaling, and model benchmarking of BNF fluxes at multiple spatial scales.

Reis Ely, Carla R. [Oregon State Univ., Corvallis,↗

Single-atom molybdenum doping induces nickel oxide-to-hydroxide transformation for enhanced alkaline hydrogen evolution

NiMoO x compounds are widely regarded as among the most efficient non-noble metal catalysts for the hydrogen evolution reaction (HER). Nevertheless, understanding the structural evolution under in situ conditions and further enhancing their performance remain key challenges. Herein, we report that single-atom Mo doping in NiO significantly enhances its HER activity, reducing the overpotential to 131 mV at 10 mA cm −2 compared to undoped NiO. In situ X-ray absorption spectroscopy and Raman spectroscopy reveal that under catalytic conditions, Mo single atoms remain structurally stable, while Ni 2+ species in NiO are converted to Ni(OH) 2 in alkaline media under the applied working potential for HER. Notably, this transformation is absent in undoped NiO, indicating that Mo doping promotes the formation of active Ni(OH) 2 sites, which, in turn, accelerate the rate-limiting water dissociation step. These findings provide critical mechanistic insights into the structural evolution of NiMoO x during alkaline HER and highlight the importance of in situ studies in the development of highly efficient catalysts.

58 GEOSCIENCES↗

Pedestal formation via different trajectories in the stability space in response to the timing scan of neutral beam heating in DIII-D

The frequency of type-I ELMs decreases as the initiation of the neutral beam injection (NBI) heating is delayed with respect to the time when plasma current (I p ) reaches flat-top in the ITER Baseline Scenario discharges in DIII-D. Henceforth, the time gap between the NBI initiation and I p flat-top will be referred to as “heating delay.” As the heating delay is modified, pedestal formation follows different trajectories in the edge current density–pedestal pressure gradient (j edge -∇p e ped ) space from the L-H transition toward the first ELM event. During the stationary phase after the first ELM, the ELM frequency (f ELM ) decreases by a factor of ~2 as the heating delay is increased. A longer pedestal recovery time in the inter-ELM period is observed for the low f ELM discharges as compared to the high f ELM discharges. Both low and high f ELM discharges show nearly identical profiles of electron density and temperature and have a similar MHD stability just before an ELM crash. However, a marked difference is observed in the magnetic spectrogram of the high and low f ELM discharges in response to the variation in the heating delay. The main difference is in the 200–400 kHz range of the magnetic spectra. A quasi-coherent mode (QCM) at 220 kHz and weaker broadband fluctuations are observed in the high f ELM discharges, while only strong broadband fluctuations are prevalent in the low f ELM discharges. ELM-synchronized analysis shows that the time evolution of these modes is different for the high and low f ELM discharges. The localization of both these modes is confirmed at the maximum gradient region of the pedestal. We hypothesize that these modes cause important pedestal transport and that the difference in the pedestal recovery of the high and low f ELM discharges is a result of the difference in transport driven by these modes, as they change with changes in the heating delay. It is demonstrated experimentally for the first time that discharges with similar pedestal parameters can carry the history of the heating delay into the stationary phase and that changes in turbulent-driven transport are a likely cause of changes in f ELM observed with variations of heating delay.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

High temperature melting of dense molecular hydrogen from machine-learning interatomic potentials trained on quantum Monte Carlo

We present results and discuss methods for computing the melting temperature of dense molecular hydrogen using a machine learned model trained on quantum Monte Carlo data. In this newly trained model, we emphasize the importance of accurate total energies in the training. We integrate a two phase method for estimating the melting temperature with estimates from the Clausius–Clapeyron relation to provide a more accurate melting curve from the model. We make detailed predictions of the melting temperature, solid and liquid volumes, latent heat, and internal energy from 50 to 180 GPa for both classical hydrogen and quantum hydrogen. At pressures of roughly 173 GPa and 1635 K, we observe molecular dissociation in the liquid phase. Here, we compare with previous simulations and experimental measurements.

08 HYDROGEN↗

Verification of the Shafranov shift in free-boundary VMEC, DESC, and SPEC calculations with elliptical geometry

Here, given a set of current-carrying filaments that create a magnetic field with rotating elliptical flux surfaces, we present verification calculations using the VMEC, DESC, and SPEC free-boundary magnetohydrostatic equilibrium codes for both the “vacuum” equilibrium, for which there is no plasma pressure and no plasma currents, and for a non-zero pressure, zero toroidal current equilibrium. For the vacuum case, these codes are quantitatively compared to the magnetic field produced by the coils. For the non-zero pressure case, they are compared to each other. As the stepped pressure profile used in SPEC approaches the continuous profile used in VMEC and DESC, the SPEC magnetic axis approaches the VMEC and DESC axes. To within an error given by the difference between the pressure profiles, the VMEC, DESC, and SPEC calculations give the same pressure-induced geometric shift of the magnetic axis, known as the Shafranov shift.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Neural operator transformers capture bifurcating drift-wave turbulence in fusion plasma simulations

Self-consistent modeling of turbulence-driven transport is critical for optimizing confinement in magnetically confined fusion plasmas, such as tokamaks and stellarators. In particular, capturing the long-term co-evolution of turbulence, flow, and background plasma profiles remains computationally challenging. Direct numerical simulation of these multiscale, highly nonlinear processes is often demanding and impractical for real-time control or design optimization. To address this bottleneck, we investigate transformer-based neural operator partial differential equation surrogates for emulating the dynamics of drift-wave turbulence bifurcation mediated by zonal flows, using the modified Hasegawa–Wakatani (MHW) model as a prototypical system. We find that the finetuned neural operator model has excellent performance in capturing the multi-spatiotemporal-scales of MHW turbulence bifurcation and is robust to testing on rare and out-of-distribution dynamics. Specifically, we demonstrate that a single unified model accurately predicts both quasi-steady-state turbulence and a wide range of dynamical transition processes, such as nonlinear saturation, spontaneous suppression of turbulence, and the emergence of macroscopic zonal flows, over time horizons vastly exceeding the local turbulence correlation time. This computationally efficient approach establishes a strong foundation for fast, AI-based modeling of complex, multiscale phenomena in magnetized fusion plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Error field measurements and correction on MUSE permanent magnet stellarator

The magnetic field topology and error fields are measured in the MUSE permanent magnet stellarator with an electron beam and fluorescent rod. The effective magnetization of the magnets is determined by measuring rational flux surface locations. Electron magnetic drift effects must be considered self-consistently due to the small magnetic shear on MUSE. Error fields are characterized by flux surface shape deviation and magnetic island chain width and phase. Error fields are then corrected by adjusting the permanent magnet (PM) holders as rigid bodies. Resonant error fields are on the order of or smaller than 3 x 10 -6 of the toroidal field after correction and surface shape matches well with the design. Resonant components of the quasi-symmetry deviation are estimated, using a novel magnetic drift measurement, to be in the 10 −4 range. The PM approach is validated as a low-cost and precise way to build optimized stellarators.

electron beam mapping↗

Editorial for the 28th Workshop on Magnetohydrodynamic (MHD) Stability Control

This special issue contains four papers which were presented at the 28th Workshop on Magnetohydrodymanic (MHD) Stability Control. The workshop was held at Auburn University and on Zoom from 3–5 October 2024. Furthermore, this annual workshop covers the active and passive control of MHD instabilities such as kink, tearing and edge-localized modes in tokamaks, reversed field pinches, spherical tori or other magnetic confinement devices.

Yang, J. [Princeton Plasma Physics Laboratory (PPP↗

N 2 Onet: a global collaborative network facilitating advances in measurement, modeling, and mitigation of agricultural soil nitrous oxide emissions

Nitrogen (N) fertilizer supports global food production, but its use and overuse drive emissions of nitrous oxide (N 2 O), a potent and long-lived greenhouse gas. Understanding the drivers of N 2 O fluxes remains elusive, making it difficult to predict emissions in time and space and to develop and evaluate ways to lower emissions through management. Major scientific uncertainties underlying the understanding of the drivers of N 2 O fluxes identified in a workshop of N 2 O emissions experts include poor process-based understanding of controls on soil N 2 O emissions in the field; insufficient data to reduce uncertainty in N 2 O budgets from the field to regional scales, including N 2 O emission measurements and importantly, field-scale N balances; and high uncertainty in model predictions of soil N 2 O emissions across environmental and management conditions. To reduce these uncertainties, we present the concept of N 2 Onet, a global collaborative initiative to accelerate advances in N 2 O measurement, analyses, and mitigation. N 2 Onet will serve as an observational network of supersites with multi-scale measurements; a database hub for N 2 O flux and ancillary data; and a catalyst for community building, information sharing, and training. By coalescing and coordinating the global community of researchers, N 2 Onet will provide a roadmap for reducing N 2 O emissions from agriculture worldwide.

54 ENVIRONMENTAL SCIENCES↗

Do We Really Need All That Data: From Data to Agency in Automated Microscopy

Microscopy is entering an era of automated laboratories and AI-enabled instruments, often justified by a simple narrative of automating experiments to collect more data and train better models. In this work, we argue that, for microscopy, this framing is incomplete and can be counterproductive.

97 MATHEMATICS AND COMPUTING↗

Toward a Robust Confirmation or Refutation of the Sterile-Neutrino Explanation of Short-Baseline Anomalies

The sterile neutrino interpretation of the LSND and MiniBooNE neutrino anomalies is currently being tested at three liquid argon detectors: MicroBooNE, SBND, and ICARUS. It has been argued that a degeneracy between 𝜈 𝜇 → 𝜈 𝑒 and 𝜈 𝑒 → 𝜈 𝑒 oscillations significantly degrades their sensitivity to sterile neutrinos. Through an independent study, we show two methods to eliminate this concern. First, we resolve this degeneracy by including external constraints on 𝜈𝑒 disappearance from the PROSPECT reactor experiment. Second, by properly analyzing the full three-dimensional parameter space, we demonstrate that the stronger-than-sensitivity exclusion from MicroBooNE alone already covers the entire 2⁢𝜎 preferred regions of MiniBooNE at the level of 2−3⁢𝜎. We show that upcoming searches at SBND and ICARUS can improve on this beyond the 4⁢𝜎 level, thereby providing a rigorous test of short-baseline anomalies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗