@article{21013, abstract = {We have addressed convective self‐aggregation (CSA) in steady and oscillating sea surface temperature (SST) and solar radiation (SOLIN) cloud‐resolving model simulations in a non‐rotating radiative‐convective equilibrium (RCE) framework. Our experiment designs are motivated by land‐ocean heterogeneity of atmospheric convection. The steady and oscillating forcings are idealizations of ocean and land conditions, respectively, based on their differences in heat capacities. In both kinds of simulations, the diurnal mean SST and SOLIN are the same, and both SST and SOLIN are only varied in time (i.e., they are spatially homogeneous at any given time). We find that diurnally oscillating forcing accelerates CSA. Stronger long‐wave cooling in dry regions at night and during the warm SST phase (late afternoon) both allow the long‐wave feedback, known to favor aggregation, to intensify compared to steady forcing simulations. In addition to the long‐wave, reduced short‐wave warming in dry regions (during the day) further enhances radiative cooling there compared to moist regions. Overall, the radiative cooling is enhanced in dry regions compared to neighboring moist convective regions. A dry subsidence is driven by this net radiative (short‐wave plus long‐wave) cooling, consistent with earlier work on CSA. Stronger radiative cooling allows stronger subsidence which allows low‐level circulation to more efficiently transport moisture and energy up‐gradient, driving convection to aggregate faster. We also note a sensitivity of our experimental setup to initial conditions, more so at warmer SST. This stochastic behavior might be critical in reconciling the differences of opinion regarding the response of convection aggregation to oscillating SST forcing.}, author = {GOSWAMI, BIDYUT B and Lu, Ziyin and Muller, Caroline J}, issn = {1942-2466}, journal = {Journal of Advances in Modeling Earth Systems}, number = {1}, publisher = {Wiley}, title = {{Convective self‐aggregation in diurnally oscillating sea surface temperature and solar forcing experiments}}, doi = {10.1029/2024ms004576}, volume = {18}, year = {2026}, } @article{21015, abstract = {Early embryo geometry is one of the most invariant species-specific traits, yet its role in ensuring developmental reproducibility and robustness remains underexplored. Here we show that in zebrafish, the geometry of the fertilized egg—specifically its curvature and volume—serves as a critical initial condition triggering a cascade of events that influence development. The embryo geometry guides patterned asymmetric cell divisions in the blastoderm, generating radial gradients of cell volume and nucleocytoplasmic ratio. These gradients generate mitotic phase waves, with the nucleocytoplasmic ratio determining individual cell cycle periods independently of other cells. We demonstrate that reducing cell autonomy reshapes these waves, emphasizing the instructive role of geometry-derived volume patterns in setting the intrinsic period of the cell cycle oscillator. In addition to organizing cell cycles, early embryo geometry spatially patterns zygotic genome activation at the midblastula transition, a key step in establishing embryonic autonomy. Disrupting the embryo shape alters the zygotic genome activation pattern and causes ectopic germ layer specification, underscoring the developmental significance of geometry. Together, our findings reveal a symmetry-breaking function of early embryo geometry in coordinating cell cycle and transcriptional patterning.}, author = {Mishra, Nikhil and Li, Yuting I and Hannezo, Edouard B and Heisenberg, Carl-Philipp J}, issn = {1745-2481}, journal = {Nature Physics}, pages = {139--150}, publisher = {Springer Nature}, title = {{Geometry-driven asymmetric cell divisions pattern cell cycles and zygotic genome activation in the zebrafish embryo}}, doi = {10.1038/s41567-025-03122-1}, volume = {22}, year = {2026}, } @misc{21137, author = {Naik, Suyash}, publisher = {Institute of Science and Technology Austria}, title = {{Data associated with Keratins coordinate tissue spreading }}, doi = {10.15479/AT-ISTA-21137}, year = {2026}, } @article{21485, abstract = {Insulating oxides are among the most abundant solid materials in the universe1,2,3. Of the many ways in which they influence natural phenomena, perhaps the most consequential is their capacity to transfer electrical charge during contact4,5,6,7,8,9,10—which occurs even between samples of the same oxide—yet the symmetry-breaking parameter that causes this remains unidentified11,12. Here we show that adventitious carbonaceous molecules adsorbed from the environment are the symmetry-breaking factor in same-material oxide contact electrification (CE). We use acoustic levitation to measure charge exchange between a sphere and a plate composed of identical amorphous silicon dioxide (SiO2). Although charging polarity is random for co-prepared samples, we control it with baking or plasma treatment. Observing the charge-exchange relaxation afterwards, we see dynamics over a timescale of hours and connect this directly to the presence of adventitious carbon with time-of-flight mass spectrometry, low-energy ion scattering and infrared spectroscopy. Going further, we confirm that adventitious carbon can even determine charge exchange among different oxides. Our results identify the symmetry-breaking parameter that causes insulating oxides to exchange charge in settings ranging from desert sands4 to volcanic plumes5,6, while simultaneously highlighting an overlooked factor in CE more broadly.}, author = {Grosjean, Galien M and Ostermann, Markus and Sauer, Markus and Hahn, Michael and Pichler, Christian M. and Fahrnberger, Florian and Pertl, Felix and Balazs, Daniel and Link, Mason M. and Kim, Seong H. and Schrader, Devin L. and Blanco, Adriana and Gracia, Francisco and Mujica, Nicolás and Waitukaitis, Scott R}, issn = {1476-4687}, journal = {Nature}, number = {8106}, pages = {626--631}, publisher = {Springer Nature}, title = {{Adventitious carbon breaks symmetry in oxide contact electrification}}, doi = {10.1038/s41586-025-10088-w}, volume = {651}, year = {2026}, } @phdthesis{21918, author = {Khudiakova, Kseniia}, issn = {2663-337X}, pages = {89}, publisher = {Institute of Science and Technology Austria}, title = {{How epistasis and purifying selection shape genetic diversity}}, doi = {10.15479/AT-ISTA-21918}, year = {2026}, } @article{22229, abstract = {Hippocampal CA3 pyramidal neurons (PNs) form the largest autoassociative network in the mammalian brain. Whether CA3–CA3 recurrent connectivity is genetically preconfigured or environmentally shaped during ongoing memory storage is currently unknown. To address this question, we performed multicellular patch-clamp-based circuit mapping of up to eight CA3 PNs in the mouse hippocampus at multiple postnatal time points (P7–8, P18–25, and P45–50). Here, we show that the hippocampal CA3 network undergoes a developmental transformation from local, dense, and random connectivity to a distributed, sparse, and structured configuration. Thus, sparse and structured connectivity may emerge via experience-dependent mechanisms. In parallel, the strength of single synapses is downregulated; single synaptic events are sufficient to trigger postsynaptic spiking early in development, whereas spatial summation of several inputs is required at later time points. Biologically inspired models of memory storage by Hebbian synaptic plasticity and retrieval via pattern completion suggest that developmental changes improve specific aspects of memory storage and retrieval. Our results imply a developmental transformation of the neuronal code and the memory functions in the hippocampal CA3 network.}, author = {Vargas Barroso, Victor M and Watson, Jake and Navas Olivé, Andrea C and Schlögl, Alois and Jonas, Peter M}, issn = {2041-1723}, journal = {Nature Communications}, publisher = {Springer Nature}, title = {{Developmental emergence of sparse and structured synaptic connectivity in the hippocampal CA3 memory circuit}}, doi = {10.1038/s41467-026-71914-x}, volume = {17}, year = {2026}, } @article{21161, abstract = {In many species, sex-biased expression is widespread and thought to contribute to sexual dimorphism. While bulk RNA-sequencing has been instrumental in identifying strongly sex-biased genes, it lacks resolution to assess variation across cell-types and tissue compartments. Using single-nucleus expression data from the Fly Cell Atlas, we investigate sex differences in adult Drosophila melanogaster. We find that differences in cell-type composition between the sexes are not a major source of sex-bias, as for the vast majority of genes, the degree of sex-bias is similar regardless of whether sex differences in cell-type composition are controlled for or not. Our analysis confirms a deficit of X-linked male-biased genes in the body’s somatic tissues that is widespread across cell-types. We also find the excess of X-linked female-biased genes to be associated with nervous system cells in the head but with epithelial cells in the body’s somatic tissues, showing that single-nucleus data crucially resolves sex-bias at the cell-type level. We investigate dosage compensation (DC) across 15 tissues and 17 cell-types. We observe that it varies throughout the body. Surprisingly, we observe a lack of DC in a cluster of main cells within the male accessory glands. This result highlights the importance of understanding context-dependent DC.}, author = {De Castro Barbosa Rodrigues Barata, Carolina and Vicoso, Beatriz}, issn = {1471-2954}, journal = {Proceedings of the Royal Society B Biological Sciences}, number = {2063}, publisher = {Royal Society of London}, title = {{Single-nucleus resolution of sex-biased expression and dosage compensation in Drosophila melanogaster}}, doi = {10.1098/rspb.2025.2471}, volume = {293}, year = {2026}, } @article{22333, abstract = {RNA polymerase II (Pol II) must be assembled in the cytoplasm before it enters the nucleus, where it transcribes protein-coding genes. Although transcription by Pol II is intensively studied, how this central multi-subunit enzyme is made and the role of dedicated assembly factors remains unclear. Here, we report the integrative structural analysis of a native human Pol II from the cytoplasm captured near the end of biogenesis. The complex contains Gdown1 and three biogenesis factors – RPAP2 and the critical small GTPases GPN1 and GPN3. Cryo-EM analysis of the complex reveals how Gdown1 and RPAP2 associate with Pol II and prevent the premature association of transcription factors. Further biochemical and cryo-EM analysis reveals how RPAP2 tethers GPN1–GPN3 to the complex and how the assembly of the RPAP2–GPN1–GPN3 complex is controlled by GTP hydrolysis. The combined results uncover a network of interactions that chaperone cytoplasmic Pol II to prevent aberrant interactions, reveal a molecular switch regulating biogenesis factor association, and suggest a general mechanism for the action of GPN-loop GTPase family of enzymes.}, author = {Hlavata, Annamaria and Neuditschko, Benjamin and Schellhaas, Ulla and Plaschka, Clemens and Herzog, Franz and Bernecky, Carrie A}, issn = {2041-1723}, journal = {Nature Communications}, publisher = {Springer Nature}, title = {{Structure of cytoplasmic RNA polymerase II}}, doi = {10.1038/s41467-026-75416-8}, year = {2026}, } @phdthesis{21021, abstract = {This thesis examines how geometry and topology intersect in the representation, transformation, and analysis of complex shapes. It considers how continuous manifolds relate to their discrete analogues, how topological structures evolve in persistence vineyards, and how tools from topological data analysis can illuminate problems in mathematical physics. Central to this exploration is the question of how structure, both geometric and topological, persists or changes under approximation, sampling, or deformation. The work develops new approaches to skeletal and grid-based representations of surfaces, reveals the full expressive capacity of persistence vineyards, and applies topological methods to the longstanding problem of equilibria in electrostatic fields. These threads braid together into a broader understanding of how topology and geometry inform one another across theory, computation, and application.}, author = {Fillmore, Christopher D}, issn = {2663-337X}, pages = {122}, publisher = {Institute of Science and Technology Austria}, title = {{Braiding geometry and topology to study shapes and data}}, doi = {10.15479/AT-ISTA-21021}, year = {2026}, } @article{20590, abstract = {Moist convection is a fundamental process occurring in the Earth's atmosphere. It plays a central role in the weather and climate of the Tropics, where, to first order, the heating of the atmosphere by convection is in balance with the cooling of the atmosphere by the emission of radiation to outer space. In this study, we use a cloud-resolving model in radiative–convective equilibrium with an imposed constant rate of radiative cooling and study the response of moist convection to varying this rate of radiative cooling. In particular, we study two types of simulation: varying air temperature (VAT) simulations, where the air temperature is allowed to adjust to the imposed radiative cooling, and constant air temperature (CAT) simulations, where the surface temperature is tuned to ensure that the atmospheric temperature profile in the domain is constant. We recover the previously known result that, in response to increasing radiative cooling, the area of convection expands rapidly, while the intensity of convection does not change. We find that this response is explained by the increased boundary-layer variability in simulations with greater radiative cooling, which compensates for the decreasing temperature by adding a larger initial velocity close to the cloud base. We also propose a fundamental scaling of the non-dimensional cumulus mass flux in moist convection, which is robust across models of different complexity. We aim to bridge the gap between highly idealised prototypes of moist convection, such as the “Rainy–Bénard convection” introduced by Vallis et al., and comprehensive cloud-resolving models.}, author = {Agasthya, Lokahith N and Muller, Caroline J}, issn = {1477-870X}, journal = {Quarterly Journal of the Royal Meteorological Society}, number = {775}, publisher = {Wiley}, title = {{Moist convection and radiative cooling: Dynamical response and scaling}}, doi = {10.1002/qj.70044}, volume = {152}, year = {2026}, } @article{21486, abstract = {Sex-chromosome systems are highly variable across animals, but how they transition from one to another is not well understood. Diptera have undergone multiple sex-chromosome turnovers and expansions while maintaining their general chromosomal content, which makes them an ideal clade to study such transitions. We analyzed more than 100 dipteran whole-genome assemblies and identified 4 new lineages that underwent sex-chromosome turnover (in addition to the 5 previously reported). We find that the majority of turnovers happened in the group Schizophora, which tend to have fewer genes on Muller element F (the chromosome homologous to the ancestral insect X chromosome) than lower dipterans, a factor previously hypothesized to facilitate turnover. Most derived X chromosomes have higher GC content than autosomes, consistent with a high prevalence of male achiasmy in Diptera. In addition, an excess of gene movement out of the X is detected for most of these new X chromosomes, and many of these moved genes have high testis expression in Drosophila, suggesting that out-of-X gene movement contributes to the long-term demasculinization of X chromosomes.}, author = {Layana Franco, Lorena Alexandra and Toups, Melissa A and Vicoso, Beatriz}, issn = {2056-3744}, journal = {Evolution Letters}, number = {3}, publisher = {Oxford University Press}, title = {{Causes and consequences of sex-chromosome turnovers in Diptera}}, doi = {10.1093/evlett/qrag003}, volume = {10}, year = {2026}, } @unpublished{21859, abstract = {As artificial neural networks, and specifically large language models, have improved rapidly in capabilities and quality, they have increasingly been deployed in real-world applications, from customer service to Google search, despite the fact that they frequently make factually incorrect or undesirable statements. This trend has inspired practical and academic interest in model editing, that is, in adjusting the weights of the model to modify its likely outputs for queries relating to a specific fact or set of facts. This may be done either to amend a fact or set of facts, for instance, to fix a frequent error in the training data, or to suppress a fact or set of facts entirely, for instance, in case of dangerous knowledge. Multiple methods have been proposed to do such edits. However, at the same time, it has been shown that such model editing can be brittle and incomplete. Moreover the effectiveness of any model editing method necessarily depends on the data on which the model is trained, and, therefore, a good understanding of the interaction of the training data distribution and the way it is stored in the network is necessary and helpful to reliably perform model editing. However, working with large language models trained on real-world data does not allow us to understand this relationship or fully measure the effects of model editing. We therefore propose Behemoth, a fully synthetic data generation framework. To demonstrate the practical insights from the framework, we explore model editing in the context of simple tabular data, demonstrating surprising findings that, in some cases, echo real-world results, for instance, that in some cases restricting the update rank results in a more effective update.}, author = {Iofinova, Eugenia B and Alistarh, Dan-Adrian}, booktitle = {arXiv}, title = {{Behemoth: Benchmarking unlearning in LLMs using fully synthetic data}}, doi = {10.48550/arXiv.2601.23153}, year = {2026}, } @phdthesis{22258, abstract = {Uncovering the genetic architecture of complex traits and pinpointing causal molecular drivers require the ability to distinguish true signals from noise within massive, high-dimensional omics datasets. To extract meaningful biological insights from these datasets, such as identifying causal genetic variants and proteins, scalable and accurate inference methods are essential. To this end, this thesis develops novel Bayesian inference frameworks based on Vector Approximate Message Passing and demonstrates their effectiveness in the modeling of disease onset times and quantitative physical and clinical measures. First, we introduce gVAMP, a Bayesian framework tailored for Genome-Wide Association Studies that enables the joint modeling of quantitative complex traits across millions of genetic variants. gVAMP demonstrates superior accuracy in variable selection and out-of-sample polygenic risk prediction compared to state-of-the-art approaches. We model human height using 17 million whole-genome sequence variants from the UK Biobank, incorporating a vast number of rare variants and revealing novel associations. gVAMP achieves a prediction accuracy of approximately 46% for human height, representing the highest reported performance for this trait to date. Second, we present vampW, a Bayesian framework for survival analysis applied to proteomic data. By effectively handling right-censoring and complex protein dependencies within the UK Biobank Pharma Proteomics Project dataset, vampW identifies 219 protein associations across 24 disease outcomes, the majority of which are not among the top marginal discoveries. We further adjust protein levels for exponential age effects, yielding 1,308 associations and highlighting the sensitivity of the analysis to the chosen age-correction methodology. Finally, vampW improves upon the variable selection capabilities of the commonly used (penalized) variants of the Cox proportional hazards model and delivers state-of-the-art out-of-sample prediction of disease onset times. Collectively, these methods provide powerful tools for dissecting the genetic architecture of complex traits and the proteomic drivers of disease onset. Furthermore, by delivering accurate polygenic risk scores and precise predictions of onset times, this work advances the capabilities of personalized medicine and clinical risk stratification.}, author = {Depope, Al}, issn = {2663-337X}, keywords = {Approximate Message Passing, GWAS, Genomics, Proteomics, Survival modeling}, pages = {169}, publisher = {Institute of Science and Technology Austria}, title = {{From sparse selection to risk prediction: Approximate message passing for proteomic survival models and large-scale genomics}}, doi = {10.15479/AT-ISTA-22258}, year = {2026}, } @article{22608, abstract = {For tissues to spread, they must deform while staying intact. How spreading tissues balance flexibility with integrity is not yet well understood. Here, we show that keratin intermediate filaments adapt tissue mechanical resilience to the stresses arising in epithelial tissues during spreading. By analyzing the expansion of the enveloping cell layer (EVL) over the yolk cell in zebrafish embryos in vivo, we find that keratin network maturation in EVL cells is promoted by stresses building up within the spreading tissue. Through genetic interference and tissue rheology experiments, complemented by a vertex model with mechanochemical feedback, we demonstrate that stress-induced keratin network maturation in the EVL increases tissue viscosity, to prevent tissue rupture. Further, keratins are required in the yolk cell for mechanosensitive actomyosin network contraction and flow, the forces pulling the EVL. These dual mechanosensitive functions of keratins enable a balance between pulling force production and EVL mechanical resilience, ensuring uniform and robust tissue spreading.}, author = {Naik, Suyash and Keta, Yann-Edwin and Pranjic-Ferscha, Kornelija and Hannezo, Edouard B and Henkes, Silke and Heisenberg, Carl-Philipp J}, issn = {2041-1723}, journal = {Nature Communications}, publisher = {Springer Nature}, title = {{Keratins coordinate tissue spreading by balancing spreading forces with tissue material properties}}, doi = {10.1038/s41467-026-72366-z}, volume = {17}, 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{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}, } @article{22148, abstract = {How the twin-arginine translocase (Tat) system transports fully folded substrate proteins across cellular membranes without disrupting membrane integrity has been a fundamental question in cell biology for decades. The Tat system, found in prokaryotes and plant organelles, recognizes a cargo signal peptide via a conserved twin-arginine motif. The multi-subunit Tat complex facilitates the proton-motive-force-dependent translocation process, yet its overall architecture has remained unknown. Here, we present the cryo-electron microscopy (cryo-EM) structure of the Escherichia coli (E. coli) trimeric TatB₃C₃ complex with bound substrate SufI, assembled in vivo. The complex adopts an unusual, wide-open, bowl-shaped architecture with a polar inner cavity. Unexpectedly, the cargo is engaged in a dual-contact mode: while the signal peptide binds inside one TatBC unit, the folded domain docks tightly onto an adjacent unit, possibly performing a proofreading function. This structure provides a mechanistic framework for substrate engagement and suggests the direct involvement of the entire Tat complex in substrate translocation.}, author = {Zhao, Ziyu and Sazanov, Leonid A}, issn = {1097-4164}, journal = {Molecular Cell}, publisher = {Elsevier}, title = {{Structure of E. Coli twin-arginine translocase (Tat) complex with bound cargo}}, doi = {10.1016/j.molcel.2026.05.026}, year = {2026}, } @inproceedings{22722, abstract = {The local structure of a protein strongly impacts its function and interactions with other molecules. Representing local biomolecular environments remains a key challenge while applying machine learning approaches over protein structures. The structural and chemical variability of these environments makes them challenging to model, and performing representation learning on these objects remains largely under-explored. In this work, we propose representations for local protein environments that leverage intermediate features from machine learning force fields (MLFFs). We extensively benchmark state-of-the-art MLFFs, comparing their performance across latent spaces and downstream tasks, and show that their embeddings capture local structural (e.g., secondary motifs) and chemical features (e.g., amino acid identity and protonation state), organizing protein environments into a structured manifold. We show that these representations enable zero-shot generalization and transfer across diverse downstream tasks. As a case study, we build a physics-informed, uncertainty-aware chemical shift predictor that achieves state-of-the-art accuracy in biomolecular NMR spectroscopy. Our results establish MLFFs as general-purpose, reusable representation learners for protein modeling, opening new directions in representation learning for structured physical systems. Code and data are available at https://github.com/mb012/MLFF_representation. }, author = {Bojan, Meital I and Vedula, Sanketh and Maddipatla, Sai A and Sellam, Nadav E and Rzayev, Anar and Napoli, Federico and Schanda, Paul and Bronstein, Alexander}, booktitle = {14th International Conference on Learning Representations}, location = {Rio de Janeiro, Brazil}, pages = {100760--100799}, title = {{Representing local protein environments with machine learning force fields}}, volume = {2026}, year = {2026}, } @phdthesis{22684, abstract = {Contact electrification (CE) is a simple yet elusive phenomenon that occurs when two materials come into contact and separate, leaving behind net electrical charge. Despite its ubiquity, the microscopic origin of CE remains unclear. In this thesis, we investigate CE from three complementary perspectives: developing a quantitative method to measure charge at the nanoscale, exploring the dynamic behavior of charge on insulating surfaces, and uncovering the role of mechanical history in forming a triboelectric series. In the first part, we establish a rigorous framework for converting qualitative Kelvin probe force microscopy (KPFM) voltage maps into quantitative charge density distributions. Using finite element method (FEM) simulations, we determine the point-spread function of the KPFM tip–sample geometry and demonstrate that the true surface charge can be reconstructed by numerical deconvolution. This procedure enables the recovery of both the magnitude and sign of charge density with high fidelity, resolving nanoscale features that are otherwise obscured. Applying the method to contact-charged SiO$_2$ surfaces, we show that existing analytical approximations, such as parallel plate or spherical models, can miscalculate charge magnitude by orders of magnitude. Our hybrid FEM/KPFM approach therefore provides a fast and general method to convert qualitative KPFM signals into quantitative charge data, enabling nanoscale charge mapping under realistic experimental conditions. In the second part, we study the temporal stability of CE-induced charges and identify the key material factors that determine whether KPFM can capture meaningful charge patterns. Through time-resolved experiments combining a custom-built transfer system with both microscopic and macroscopic measurements, we demonstrate that only the best insulators, such as SiO$_2$, preserve CE charge long enough for stationary imaging. For less conductive polymers, such as PDMS, charge decays within the duration of a single KPFM scan due to bulk conduction. Using a simple capacitor-based model, we reproduce the observed decay dynamics and confirm that the transferred charge decays characteristic to the sample's bulk conductivity. Further, we always observe homogeneous charge transfer. In the third part, we address the question: can we form a triboelectric series with identical materials? Using controlled repetitive contact experiments, we show that nominally identical materials can progressively order themselves into a triboelectric series, where surfaces with more contact history charge negatively relative to fresher ones. By constructing a minimal model based on this ``contact bias'', we replicate the evolution from random to ordered charging observed in experiments. Supporting surface analyses, including atomic force microscopy, reveal that repeated contact induces nanoscale morphological changes, suggesting a mechanism tightly coupled to mechanical strain. These results highlight the crucial role of surface history and nanoscale mechanics in dictating charge transfer, motivating further exploration of mechanisms such as mechanochemical bond cleavage and flexoelectric polarization.}, author = {Pertl, Felix}, isbn = {978-3-99078-083-1}, issn = {2663-337X}, pages = {107}, publisher = {Institute of Science and Technology Austria}, title = {{Experimental probing of nanoscale charge features and surface morphology changes during tribocharging}}, doi = {10.15479/AT-ISTA-22684}, year = {2026}, } @article{21762, abstract = {Bacteria, like eukaryotes, use conserved cytoskeletal systems for intracellular organization. The plasmid-encoded ParMRC system forms actin-like filaments that segregate low–copy number plasmids. In multicellular cyanobacteria such as Anabaena sp., we found that a chromosomally encoded ParMR system has evolved into a cytoskeletal system named CorMR with a function in cell shape control rather than DNA segregation. Live-cell imaging, in vitro reconstitution, and cryo–electron microscopy revealed that CorM formed dynamically unstable, antiparallel double-stranded filaments that were recruited to the membrane by CorR through an amphipathic helix conserved in multicellular cyanobacteria. CorMR filaments were regulated by MinC, which excluded them from the poles and division plane. Comparative genomics indicated that the repurposing of ParMR and Min systems coevolved with cyanobacterial multicellularity, highlighting the evolutionary plasticity of cytoskeletal systems in bacteria.}, author = {Springstein, Benjamin L and Javoor, Manjunath and Megrian, Daniela and Hajdu, Roman and Hanke, Dustin M. and Zens, Bettina and Weiss, Gregor L. and Schur, Florian Km and Loose, Martin}, issn = {1095-9203}, journal = {Science}, number = {6795}, publisher = {AAAS}, title = {{Repurposing of a DNA segregation machinery into a cytoskeletal system controlling cell shape}}, doi = {10.1126/science.aea6343}, volume = {392}, year = {2026}, }