@article{22639, abstract = {We present an abstract Dyson expansion for perturbations that are merely relatively form-bounded, and apply it to the polaron problem. For a large class of polaron-type models, including the Fröhlich and Nelson models, we prove that the vacuum expectation value of the heat semi-group is a completely monotone function of the square of the total momentum. Consequently, the ground-state energy is a concave function of the square of the momentum, a result recently proved for the Fröhlich model in [14] using a probabilistic approach via Wiener integrals.}, author = {Desio, Davide and Seiringer, Robert}, issn = {1573-0530}, journal = {Letters in Mathematical Physics}, number = {4}, publisher = {Springer Nature}, title = {{Dyson expansion for form-bounded perturbations and applications to the polaron problem}}, doi = {10.1007/s11005-026-02107-2}, volume = {116}, year = {2026}, } @article{22638, abstract = {The one-bond proton-carbon coupling constant (1JCH) is an insightful probe of carbohydrate configuration. Equatorial and axial protons at the C1 position typically exhibit distinct 1JCH values, enabling NMR measurements to distinguish α- and β-configurations in carbohydrates. In principle, such measurements could provide insights into carbohydrates in the cell walls of intact microbes. However, traditionally, these measurements are performed by solution NMR with carbohydrates that were extracted, solubilized and fractionated, leaving the biological relevance of the measurements uncertain. Here, we demonstrate that 1H-detected solid-state NMR with fast magic-angle spinning allows quantitative measurements of 1JCH couplings for mobile capsular polysaccharides, directly on submilligram amounts of pathogenic cells. Our approach is demonstrated on intact cells of the pathogenic yeast Cryptococcus neoformans. High-resolution proton-detected spectra enabled the determination of coupling constants for five mobile polysaccharide units of the cryptococcal capsule, revealing their native configurations and confirming previous solution NMR-based anomeric configuration assignments.}, author = {Lends, Alons and Lamon, Gaelle and Vallet, Alicia and Grélard, Axelle and Morvan, Estelle and Aimanianda, Vishukumar and Schanda, Paul and Loquet, Antoine}, issn = {1520-5126}, journal = {Journal of the American Chemical Society}, number = {27}, pages = {28037--28042}, publisher = {American Chemical Society}, title = {{On-cell detection of polysaccharide one-bond1Jch couplings by proton-detected solid-state NMR}}, doi = {10.1021/jacs.6c06064}, volume = {148}, year = {2026}, } @article{22644, abstract = {We analyze the average behavior of various arithmetic functions at the values of degree 𝑑 binary forms ordered by height, with probability 1. This approach yields averaged versions of the Chowla conjecture and the Bateman–Horn conjecture for random binary forms. Furthermore, we show that the rational Hasse principle holds for almost all Châtelet varieties defined by a fixed norm form of degree 𝑒 and by varying binary forms of fixed degree 𝑑, provided 𝑒 divides 𝑑. This proves an average version of a conjecture of Colliot-Thélène.}, author = {Diao, Yijie}, issn = {1469-509X}, journal = {Glasgow Mathematical Journal}, pages = {1--34}, publisher = {Cambridge University Press}, title = {{Liouville function, von Mangoldt function, and norm forms at random binary forms}}, doi = {10.1017/s0017089526101074}, year = {2026}, } @article{21923, abstract = {The appearance of simulated natural phenomena heavily depends on the way surfaces are textured. However, applying texture maps to dynamic deformable surfaces presents a significant challenge, due to ever-shifting differences in length scales involved. When these surfaces move and advect the texture along with them, their final appearance degrades as deformed regions dramatically distort their texture map. Modifications to the texture directly at the pixel level in response to the deformation may introduce ghosting artifacts and look unnatural. In the real world, the appearance of surface details on a deforming material changes through the interplay of physical processes such as rupturing, exposure of internal structure, or wrinkling. Motivated by these behaviors, in this work we explore how physical principles can guide the texturing methods based on the measure of surface deformation. We present two novel wave-based procedural texturing algorithms which reproduce common physical properties like advection and self-similarity, enabling the plausible animation of deforming objects with extreme texture map distortions. Our algorithms are fully procedural, require no actual physics simulation, and store no state or history of deformation besides the input UV map, making them highly parallelizable on the GPU and efficient enough for real-time applications. We show the versatility of the method by animating physical phenomena with extreme deformations such as flowing lava, stretching putty and outpouring sludge.}, author = {Kalinov, Aleksei and Ly, Mickaël and Hafner, Christian and Wojtan, Christopher J}, issn = {0730-0301}, journal = {ACM Transactions on Graphics}, keywords = {Procedural animation}, location = {Los Angeles, CA, United States}, number = {4}, publisher = {Association for Computing Machinery}, title = {{Physics-inspired procedural texturing of extremely deformable surfaces}}, doi = {10.1145/3811353}, volume = {45}, year = {2026}, } @article{22363, abstract = {Eukaryotic gene regulation relies on stochastic yet controlled promoter switching, in which genes transition between transcriptionally active and inactive states. Despite the molecular complexity of this process, recent studies have revealed a surprising invariance of the “switching correlation time” (TC)—the characteristic decay time of the autocorrelation function of promoter activity fluctuations—across gene expression levels in multiple genes and organisms. A biophysically plausible explanation for this invariance has so far been lacking. Here, we show that this empirical constraint imposes stringent requirements on minimal yet realistic models of transcriptional regulation. Specifically, reproducing TC–invariance requires regulatory architectures with at least four internal states and nonequilibrium dynamics that break detailed balance. Using Bayesian inference on Drosophila gap gene expression data, we demonstrate that such models i) quantitatively reproduce the observed TC–invariance, ii) remain robust to parameter perturbations, and iii) maximize information transmission from transcription factor concentration to gene expression. Remarkably, the TC-invariant modulation strategy we identify as optimal closely parallels contemporary control-theoretic results on the modulation of stochastic switching systems. Taken together, our results suggest that eukaryotic transcriptional regulation operates in a nonequilibrium regime to balance precision, reaction-rate limitations, and energy dissipation, thereby achieving near-optimal information transmission under fundamental physical constraints.}, author = {Zoller, Benjamin and Benichou, Alexis and Gregor, Thomas and Tkačik, Gašper}, issn = {1091-6490}, journal = {Proceedings of the National Academy of Sciences of the United States of America}, number = {28}, publisher = {National Academy of Sciences}, title = {{Invariant nonequilibrium dynamics in gene regulation optimize information flow}}, doi = {10.1073/pnas.2524855123}, volume = {123}, year = {2026}, } @article{22637, abstract = {The distribution of entanglement across distant qubits is a central challenge for the operation of scalable quantum computers and large-scale quantum networks. Existing approaches rely on deterministic state transfer, or probabilistic protocols that require active control or measurements and postselection. Here, we demonstrate a fundamentally different, fully autonomous process, where two remote qubits are entangled through their coupling to a quantum-correlated photonic reservoir. In our experiment, a Josephson parametric converter produces a Gaussian, continuous-variable entangled state of propagating microwave fields that drives two spatially separated superconducting transmon qubits into a stationary, discrete-variable entangled state. We also show how qubit tomography unlocks a direct and sensitive verification of two-mode squeezing in the microwave domain. These results establish networks of qubits interfaced with distributed continuous-variable entangled states as a powerful platform for foundational studies and quantum-technology applications.}, author = {Andres Juanes, Alejandro and Agustí, J. and Sett, Riya and Redchenko, Elena and Kapoor, Lucky and Hawaldar, Samarth and Rabl, P. and Fink, Johannes M}, issn = {2160-3308}, journal = {Physical Review X}, number = {3}, publisher = {American Physical Society}, title = {{Distributing stationary qubit entanglement through a nonlocal squeezed reservoir}}, doi = {10.1103/r4jt-j39w}, volume = {16}, year = {2026}, } @article{22315, abstract = {Plant tropisms enable roots to navigate complex soils by responding to directional environmental cues. Biological decay, although central to nutrient cycling, also creates microbially active and potentially hostile niches. In this work, we identified “saprotropism,” a previously unrecognized growth response that enables roots to actively bend away from decaying plant-derived matter. Fungal-driven microbial decomposition released organic acids and formed stable pH gradients in surrounding soil, allowing roots to pinpoint decay without direct contact. Root epidermal cells sensed this acidic gradient through the root meristem growth factor peptide-receptor module, converting external pH asymmetry into asymmetric abscisic acid (ABA) distribution. ABA asymmetry drove microtubule reorganization, which was decoded into decay-avoidant root bending. Together, these findings establish microbial decay–derived chemical gradients as an instructive signal for root navigation and expand the framework of microbe-soil-plant communication.}, author = {Bao, Zhulatai and Wang, Huihui and Zhang, Ai and Gao, Ruxi and Gu, Wen and Fan, Ni and Friml, Jiří and Zhang, Yuzhou}, issn = {1095-9203}, journal = {Science}, number = {6807}, publisher = {American Association for the Advancement of Science}, title = {{Roots navigate around decay regions by sensing local pH gradients}}, doi = {10.1126/science.adw6568}, volume = {393}, year = {2026}, } @article{22295, abstract = {Despite the functional diversity of over 100 causal genes1,2,3, phenotypic convergence across models may reveal common neurobiological processes in autism spectrum disorder (ASD). Here we profiled 251 samples from 11 monogenic mouse models of ASD using single-nucleus multi-omic sequencing across three developmental stages, both sexes and two brain regions. Despite genetic heterogeneity, ASD-linked mutations converged on perturbations of the radial glial cell lineage. These alterations reflect a transient developmental delay rather than lasting lineage misspecification and resolve by postnatal stages. Molecularly, the largest transcriptional differences emerged in neurons at early postnatal stages. These changes included downregulation of synaptic and ion channel-related genes, consistent with homeostatic adaptation or delayed maturation. Network analysis showed molecular convergence across models within each developmental stage, suggesting that diverse mutations linked to ASD impinge on common, stage-specific processes. Convergence becomes less pronounced by postnatal day 14, highlighting the dynamic nature of ASD-associated changes. Cross-genotype heterogeneity is superimposed on stage-specific effects. Electrophysiology corroborated this pattern: mutants generally showed altered neuronal excitability and synaptic properties with model-specific nuances. Our study also highlighted sex-specific gene expression alterations, with female mice often displaying larger effect sizes than male mice. Together, our findings provide a comprehensive view of developmental cellular and molecular dynamics across models of ASD.}, author = {Schwarz, Lena A and Dotter, Christoph and Isaev, Sergey and Lisi, Michela and Malzl, Daniel and Büschl, Christoph and Ladstätter, Sabrina and Oliveira, Bárbara and Barel, Matteo and Basilico, Bernadette and Chintaluri, Chaitanya and Gorkiewicz, Sarah and Goudarzi, Mohammad and Belinova, Tereza and Reichl, Stephan and Sendžikaitė, Gintarė and Arcot Jayaram, Satish and Koppensteiner, Peter and Sommer, Christoph M and Vogels, Tim P and Menche, Jörg and Adameyko, Igor and Kharchenko, Peter Vasili and Bock, Christoph and Novarino, Gaia}, issn = {1476-4687}, journal = {Nature}, publisher = {Springer Nature}, title = {{Cortical development dynamics across autism spectrum disorder mouse models}}, doi = {10.1038/s41586-026-10679-1}, year = {2026}, } @article{22268, abstract = {AlphaFold3 predicts highly accurate protein structures from sequence but tends to collapse to a single dominant conformation, even when the underlying structure is inherently heterogeneous. Moreover, its predictions are oblivious to experimental conditions that can alter local sequence conformation. In this work, we show that AlphaFold3 can be guided to match data obtained by nuclear magnetic resonance (NMR) spectroscopy, X-ray crystallography and cryogenic electron microscopy (cryo-EM) experiments and combinations thereof. Our approach can also incorporate data that explicitly report on dynamics, such as site-resolved order parameters. We demonstrate that this methodology generates compact structural ensembles whose ensemble-averaged observables agree with experiment, with fewer distance restraint violations than traditionally resolved NMR structures and with unmodeled alternate conformations uncovered in electron density. This methodology paves the way for experimentally aware predictive models that generate structural ensembles consistent with the measurements, potentially over multiple modalities, and that can be further refined toward thermodynamically grounded ensembles by incorporating energetics.}, author = {Maddipatla, Sai A and Sellam, Nadav E and Bojan, Meital I and Masalitin, Vova and Vedula, Sanketh and Schanda, Paul and Marx, Ailie and Bronstein, Alexander}, issn = {1546-1696}, journal = {Nature Biotechnology}, publisher = {Springer Nature}, title = {{Experiment-guided AlphaFold3 resolves measurement-consistent protein ensembles}}, doi = {10.1038/s41587-026-03166-5}, year = {2026}, } @article{21987, abstract = {We introduce JODIE, a genetic joint modeling approach that estimates how DNA loci influence human traits by partitioning genetic effects into four components: direct effects (from a child’s alleles), indirect maternal and paternal effects (from parents’ alleles), and parent-of-origin (PofO) effects (dependent on parental transmission of alleles), while uniquely accounting for assortative mating. We analyze 30,000 child-mother-father trios from the Estonian Biobank and the Norwegian Mother, Father, and Child Cohort, focusing on height, body mass index, and childhood educational test scores. We find direct effects to be the largest contributor to trait variation, but combined, indirect parental and PofO effects are similarly substantial. We support our results by within-family genome-wide association testing and identify 276 independently associated DNA regions with a complex interplay between direct, indirect, and PofO effects. By joint modeling, we show that direct, indirect, and PofO effects collectively shape human phenotypic variation across loci genome-wide.}, author = {Krätschmer, Ilse and Hegemann, Laura and Hofmeister, Robin J. and Corfield, Elizabeth C. and Mahmoudi, Mahdi and Delaneau, Olivier and Andreassen, Ole A. and Campbell, Archie and Hayward, Caroline and Marioni, Riccardo E. and Ystrom, Eivind and Havdahl, Alexandra and Robinson, Matthew Richard}, issn = {2666-979X}, journal = {Cell Genomics}, keywords = {direct genetic effects, DGE, indirect genetic effects, IGE, parent-of-origin effects, phenotypic variation, assortative mating, within-family GWAS, MoBa, EstBB}, number = {7}, publisher = {Elsevier}, title = {{Separating direct, indirect, and parent-of-origin genetic effects in the human population}}, doi = {10.1016/j.xgen.2026.101277}, volume = {6}, year = {2026}, } @phdthesis{22334, abstract = {Characterizing protein dynamics at the atomic level is essential for our understanding of biological mechanisms. Whether it is to facilitate metabolite transport, catalyze reactions, transmit signals, or regulate metabolism – proteins are constantly in motion and sample multiple conformational states to fulfill their function. Nuclear magnetic resonance (NMR) spectroscopy is particularly well suited to elucidate the dynamics of biomolecules on their complex free-energy landscape. In particular, solid-state magic-angle spinning (MAS) NMR enables the study of large molecular assemblies, protein crystals, or insoluble proteins at atomic resolution without an inherent molecular size limitation. MAS NMR experiments to probe protein dynamics are extremely versatile and sensitive to motional timescales from picoseconds to seconds. Over the past decades, technological advances, developments in experimental design, and new isotope-labeling approaches have further expanded the possibilities of this technique and significantly improved the accuracy of the determined motional parameters. Functionally important sites of proteins often contain aromatic residues. Their side-chain motions have therefore long served as valuable indicators of mechanistically relevant dynamics in NMR studies. In this thesis, site-specifically labeled aromatic residues act as sensitive reporters for MAS NMR studies of protein dynamics. The first part addresses how different environments impact side-chain motion by probing ring flips of phenylalanines and tyrosines in crystalline proteins and amyloid fibrils. It provides important insights for the analysis of dynamics obtained in non-native protein environments and emphasizes the complex factors that determine the timescale of internal dynamics. In the second part, the focus shifts towards methodological questions regarding the investigation of protein dynamics by 19F MAS NMR. The fluorine nucleus exhibits promising characteristics for NMR studies but also presents significant challenges, which is why the full methodological potential of 19F MAS NMR has not been fully realized yet. This work demonstrates that paramagnetic doping can considerably reduce the measurement time and improve the sensitivity of fluorinated samples. Finally, 19F MAS NMR is evaluated as a tool for studying protein side-chain dynamics on the example of tryptophans. The results illustrate the challenges in analyzing such experiments and lay the foundation for further development of 19F MAS NMR relaxation studies. Taken together, this thesis highlights the potential of combining specific isotope labeling, MAS NMR, and complementary methods such as crystallography and computational simulations to elucidate internal protein dynamics. The further development of such integrative approaches will be crucial to improving our understanding of complex mechanisms and protein function. }, author = {Becker, Lea Marie}, isbn = {978-3-99078-084-8}, issn = {2663-337X}, pages = {205}, publisher = {Institute of Science and Technology Austria}, title = {{Exploring protein dynamics using specific labeling approaches for solid-state MAS NMR}}, doi = {10.15479/AT-ISTA-22334}, year = {2026}, } @article{22105, abstract = {Protein conformational energy landscapes are shaped not only by intramolecular interactions but also by their environment. In protein crystals and protein–protein complexes, intermolecular contacts alter this energy landscape, but the exact nature of this alteration is difficult to decipher. Understanding how the crystal lattice affects protein dynamics is crucial for crystallography-based studies of motion, yet its influence on collective motions remains unclear. Aromatic ring flips in the hydrophobic core represent sensitive probes of such dynamics. Here, we compare the kinetics of aromatic ring flips in the protein GB1 in crystals, in complex with its binding partner IgG, and in solution, combining advanced isotope labelling with quantitative NMR methods. We show that rings in the core flip nearly a thousand times less frequently in crystals than in solution. Enhanced-sampling molecular dynamics simulations, based on a crystal structure of a GB1 variant reported in this work, reproduce these elevated barriers and reveal how the crystal restrains motions.}, author = {Becker, Lea Marie and Fu, Haohao and Tatman, Benjamin and Dreydoppel, Matthias and Kapitonova, Anna and Balazs, Daniel and Weininger, Ulrich and Engilberge, Sylvain and Chipot, Christophe and Schanda, Paul}, issn = {17554349}, journal = {Nature Chemistry}, pages = {1221--1230}, publisher = {Springer Nature}, title = {{Aromatic ring flips reveal reshaping of protein dynamics in crystals and complexes}}, doi = {10.1038/s41557-026-02155-0}, volume = {18}, year = {2026}, } @misc{21145, abstract = {Protein conformational energy landscapes are shaped not only by intramolecular interactions but also by their environment. In protein crystals and protein-protein complexes, intermolecular contacts alter this energy landscape, but the exact nature of this alteration is difficult to decipher. Understanding how the crystal lattice affects protein dynamics is crucial for crystallography-based studies of motion, yet its influence on collective motions remains unclear. Aromatic ring flips in the hydrophobic core represent sensitive probes of such dynamics. Here, we compare the kinetics of aromatic ring flips in the protein GB1 in crystals, in complex with its binding partner IgG, and in solution, combining advanced isotope labeling with quantitative NMR methods. We show that rings in the core flip nearly a thousand times less frequently in crystals than in solution. Enhanced-sampling molecular dynamics simulations, based on a new crystal structure, reproduce these elevated barriers and reveal how the crystal restrains motions. }, author = {Becker, Lea Marie and Schanda, Paul and Chipot, Christophe}, publisher = {Institute of Science and Technology Austria}, title = {{Additional Data for "Aromatic Ring Flips Reveal Reshaping of Protein Dynamics in Crystals and Complexes"}}, doi = {10.15479/AT-ISTA-21145}, year = {2026}, } @article{22613, abstract = {A phase plate has long been sought in transmission electron microscopy (TEM) to maximize the image contrast of weakly-scattering objects like biomolecules. The laser phase plate (LPP) has recently demonstrated that an amplified, focused laser standing wave reliably phase shifts the electron beam, achieving phase-contrast TEM. Building on the single-beam LPP, here we introduce the crossed laser phase plate (XLPP): two laser standing waves which intersect in the diffraction plane. We present a theoretical model for the XLPP inside the microscope and show that, relative to the original LPP, it increases information transfer at low spatial frequencies while suppressing ghost images formed by Kapitza-Dirac diffraction. We also present a simple acquisition scheme, enabled by the XLPP, which further suppresses ghosts. Finally, we discuss practical considerations of XLPP design and show experimental results from a prototype. The results of this study chart the course for future developments of LPP hardware.}, author = {Petrov, Petar N and Zhang, Jessie T. and Axelrod, Jeremy J. and Olshin, Pavel K. and Müller, Holger}, issn = {2041-1723}, journal = {Nature Communications}, publisher = {Springer Nature}, title = {{Crossed laser phase plates for transmission electron microscopy}}, doi = {10.1038/s41467-026-74060-6}, volume = {17}, year = {2026}, } @article{22365, abstract = {Phase plates can, in principle, overcome the poor image contrast in cryo–electron microscopy (cryo-EM) and the resulting limits on the structural reconstruction of small proteins. However, previous designs have been unstable and compromised the high-resolution signal and have thus been unable to surpass results achieved by standard cryo-EM. Here, we show that the laser phase plate (LPP), installed in a modern, custom Titan Krios microscope, enhances the resolution in single-particle reconstruction of small proteins by improving specimen-motion correction and recovery of information from the early frames, as well as particle visualization, three-dimensional classification, and alignment. These advances use standard defocus ranges and reconstruction procedures but open the door to LPP-tailored protocols, offering further improvements by leveraging the LPP demonstrated here.}, author = {Petrov, Petar N and Zhang, Jessie T. and Remis, Jonathan and Axelrod, Jeremy J. and Cheng, Hang and Cooper, Eric S. and Hicklin, Ian K. and Sandhaus, Shahar and Schnurr, Cooper and Glaeser, Robert M. and Müller, Holger}, issn = {1095-9203}, journal = {Science}, number = {6807}, pages = {195--196}, publisher = {AAAS}, title = {{Laser phase plate improves structure determination of small proteins by cryo-EM}}, doi = {10.1126/science.aeh0665}, volume = {393}, year = {2026}, } @article{22443, abstract = {Society faces increasingly severe flood hazards, intensifying demand for flood early warning systems (FEWS) that deliver accurate and actionable information. However, most existing FEWS remain prediction‐centric, treating decision‐making as a downstream consumer of hazard forecasts while offering limited support for uncertainty interpretation, risk communication, and real‐world response. This Perspective presents a vision and blueprint for a novel inland FEWS‐decision‐making (FEWS‐DM) framework that repositions decision‐making as an equal partner in the forecasting process—not a passive recipient of its outputs. The framework is built on three tightly coupled, co‐evolving thrusts: Physical Science (T1), which advances flood prediction with quantified uncertainty informed by decision relevance; Human Science (T2), which incorporates psychology, behavior, and cultural and institutional context; and Decision Science (T3), which unifies physical predictions and human factors through principled, utility‐based decision support with end‐to‐end uncertainty management. Rather than treating T1 as a solved problem, FEWS‐DM recognizes that forecast development itself must be shaped by decision needs through continuous bidirectional feedback. We identify key scientific, behavioral, and operational challenges limiting such integration and discuss the enabling role of AI, while emphasizing human‐centered design and community feedback as essential for building trust and improving flood risk management.}, author = {Tran, Vinh Ngoc and Huan, Xun and Antar, Anindya Das and Banovic, Nikola and Bednar, Jeff H. and Bergt, Shannon Marie and Cheng, Chen and Dominguez, Francina and Fatichi, Simone and Gonzalez, Richard and Gray, Kevin and Jewett, Brian and Kim, Jongho and Le, Phong V.V. and Lu, Dan and Prabhudesai, Snehal and Putri, Deffi and Rath, Sudhansu and Sargsyan, Khachik and Whitaker, Sarah H. and Wright, Daniel B. and Xu, Donghui and Ziker, John P. and Ivanov, Valeriy Y.}, issn = {2328-4277}, journal = {Earth's Future}, number = {6}, publisher = {American Geophysical Union}, title = {{Reimagining how flood warnings can inform decision‐making and community actions}}, doi = {10.1029/2026ef008857}, volume = {14}, year = {2026}, } @article{21381, abstract = {The lack of long-range electrostatics is a key limitation of modern machine learning interatomic potentials (MLIPs), hindering reliable applications to interfaces, charge-transfer reactions, polar and ionic materials, and biomolecules. In this Perspective, we distill two design principles behind the Latent Ewald Summation framework, which can capture long-range interactions, charges, and electrical response just by learning from standard energy and force training data: (i) use a Coulomb functional form with environment-dependent charges to capture electrostatic interactions, and (ii) avoid explicit training on ambiguous density functional theory partial charges. When both principles are satisfied, substantial flexibility remains: essentially any short-range MLIP can be augmented; charge equilibration schemes can be added when desired; dipoles and Born effective charges can be inferred or fine-tuned; and charge/spin-state embeddings or tensorial targets can be further incorporated. We also discuss current limitations and open challenges. Together, these minimal, physics-guided design rules suggest that incorporating long-range electrostatics into MLIPs is simpler and perhaps more broadly applicable than is commonly assumed.}, author = {Kim, Dongjin and Cheng, Bingqing}, issn = {1089-7690}, journal = {The Journal of Chemical Physics}, number = {6}, publisher = {AIP Publishing}, title = {{Long-range electrostatics for machine learning interatomic potentials is easier than we thought}}, doi = {10.1063/5.0316886}, volume = {164}, year = {2026}, } @article{22441, abstract = {Warming impacts both net primary production (NPP) and soil organic carbon (SOC) decomposition, and consequently, SOC storage. However, the role of warming in regulating SOC storage remains debated. Here, we leverage literature data of warming experiments and a mechanistic model to explore SOC responses to warming by partitioning the effects of air and soil warming. Both the literature data and numerical model show that air and soil warming play distinct roles in regulating SOC storage, with insignificant SOC responses under air warming and negative responses to soil warming. Soil warming decreases SOC storage because of temperature-driven increases in decomposition rate. Air warming effects on SOC are more complex. In some cases, air warming can lead to a lower NPP and higher decomposition rate. In others, air warming can stimulate NPP and enhance soil moisture depletion that inhibits SOC decomposition. Once the latter mechanisms dominate, SOC storage increases with air warming.}, author = {Luo, Zhaoyang and Ren, Jianning and Fatichi, Simone}, issn = {2662-4435}, journal = {Communications Earth & Environment}, publisher = {Springer Nature}, title = {{Air and soil warming have different effects on soil organic carbon storage}}, doi = {10.1038/s43247-026-03367-5}, volume = {7}, year = {2026}, } @article{22528, abstract = {Quantification of the impact of environmental stress on terrestrial vegetation photosynthesis is crucial for our understanding of the global carbon cycle, particularly under a changing climate. Vegetation responses to environmental stress manifest first as plant physiological changes, and at later stages through changes in canopy structure. Here we leverage CO2 and water flux data from 103 eddy covariance towers and satellite thermal images to assess whether current satellite reconstructions of solar-induced chlorophyll fluorescence capture these plant mechanisms. After removing seasonality using standardized anomalies (z-scores), we found that the relationship between tower-observed gross primary productivity and fluorescence reconstructions considerably weakened across a wide range of biomes. This loss of correlation results from a decoupling between stomatal responses and the physiological emission yield (ΦF) of fluorescence reconstructions during soil and atmospheric dry periods. The consequence is that productivity derived from fluorescence reconstructions will be progressively overestimated as dry conditions persist.}, author = {Zhao, Jiacheng and Paschalis, Athanasios and Gentine, Pierre and Feng, Zhaozhong and Fatichi, Simone}, issn = {2662-4435}, journal = {Communications Earth & Environment}, publisher = {Springer Nature}, title = {{Limited capability of current satellite solar-induced chlorophyll fluorescence reconstructions to capture stomatal responses to environmental stresses}}, doi = {10.1038/s43247-025-03035-0}, volume = {7}, year = {2026}, } @article{22663, abstract = {The detection of strong, large-scale magnetic fields at the surfaces of the oldest white dwarfs might point toward a hidden internal magnetic field slowly rising to the surface. In addition, strong magnetic fields have recently been measured through asteroseismology in the radiative interiors of red giant stars, the progenitors of white dwarfs. To investigate the potential connection between these observations, we revisited the fossil field framework using asteroseismic detections to constrain the strength of such magnetic fields as red giants evolve into the white dwarf stage. We assumed that the magnetic field was either created during the core convection on the main sequence or that it fills the radiative interior as the star evolves on the red giant branch. From these initial conditions, we evolved the magnetic flux, allowing for magnetic diffusion along the evolution of a modeled 1.5 M⊙ star. We find that measured field strengths in red giants attributed to the hydrogen-burning shell are compatible with the field amplitudes and emergence timescales of magnetized white dwarfs. On the contrary, magnetic fields generated solely from a convective-core dynamo on the main sequence and detectable on the red giant branch would be buried too deep in the star and would not match the breakout timescales or the field strengths of magnetic white dwarfs. Therefore, for us to connect magnetic fields observed along the late evolution of stars via a fossil field we would need to find a broadly magnetized internal radiative zone on the red giant branch.}, author = {Einramhof, Lukas and Bugnet, Lisa Annabelle and Calcaferro, L. M. and Barrault, Lucas and Das, S. B.}, issn = {1432-0746}, journal = {Astronomy & Astrophysics}, publisher = {EDP Sciences}, title = {{Magneto-archeology of white dwarfs}}, doi = {10.1051/0004-6361/202659069}, volume = {708}, year = {2026}, }