Evolutionary tendency of vegetation systems at critical points - based on optimal control methods.

From annular to surface bubbles: unraveling wettability-controlled flow patterns and governing mechanisms in microchannels

Segmented wavetrains and sites of reversal in the mouse seminiferous tubules.

Global bifurcation for a predator-prey system with nonlinear boundary-mediated dispersal

Proteins of the Ras-family are guanine nucleotide binding proteins (GNBPs) involved in a variety of fundamental cellular processes, including cell proliferation, cell differentiation, cytoskeleton dynamics, vesicular processes and intracellular transport. A dysregulation of Ras-signaling has been found to be causative for the development of diseases, such as diverse cancer types, RASopathies, neurodegenerative diseases and ciliopathies. Ras-proteins cycle between a GTP-bound on-state and a GDP-bound off-state. Ras-proteins show low intrinsic rates for nucleotide exchange and nucleotide hydrolysis. They need guanine-nucleotide exchange factors (GEFs) and GTPase-activating proteins (GAPs) to accelerate both functions in order to act as true molecular switches in the physiological context. Ras-proteins and their regulators/effectors are targets of post-translational modifications (PTMs) such as phosphorylation, ac(et)ylation, lipidation and ubiquitination. These PTMs regulate their activity, subcellular localization and turnover. In a biological perspective, PTMs are essential components for cellular signaling cascades and for molecular pattern formation. Bacterial pathogens use PTMs of Ras-proteins to allow efficient infection processes. Besides, modifications of Ras-proteins were shown to be of therapeutic potential in oncogenic variants such as Ras G12C. In this review, we summarize current knowledge on Ras-signaling, while emphasizing PTMs as dynamic signaling hubs for its precise spatiotemporal control.

Particulate matter pollution poses a threat to public health, necessitating the development of high-efficiency, sustainable air filters. Bacterial cellulose (BC) aerogels are promising candidates; however, achieving high filtration efficiency can increase air resistance. We present a surface functionalization-guided strategy for the precise tuning of aerogel surface groups to alter particle capture behavior and improve filtration performance. Using γ-aminopropyltriethoxysilane (KH550) as a model silane precursor, we demonstrated enhanced electrostatic adsorption and the formation of dendritic deposition patterns that improved the capture of inhalable particulate matter (PM2.5). The BC-KH550 aerogels exhibited outstanding filtration efficiency (>99%) while maintaining robust mechanical properties and stability under humid conditions. Theoretical simulations revealed that the enhanced electrostatic interactions following surface modification significantly influenced filtration performance, revealing a synergistic effect between surface functional groups and PM. This advanced the fundamental understanding of the structure-function relationship of modified BC aerogels and provided a blueprint for designing next-generation sustainable air filters with tunable surfaces.

Transmission Kikuchi diffraction in the scanning electron microscope has gained popularity as a materials characterisation technique for its high throughput and nanometre-level spatial resolution. While conventional diffraction pattern analysis routines focus on Kikuchi bands on the diffraction patterns, the full physical picture of electron scattering and diffraction pattern formation is more complex. Analysis that accounts for additional diffraction features such as diffraction spots and excess-deficiency effects should provide more robust and accurate indexing, if they can be incorporated in pattern indexing or simulation routines. A more accurate understanding of their physics of formation and geometry is required to enable this change. In this work, we demonstrate geometric and full contrast dynamical simulation of on-axis transmission Kikuchi patterns, based on experimental patterns captured using a modular, direct electron detector-based set-up in the scanning electron microscope. First, a diffraction geometry calibration routine is proposed based on the electron channelling pattern of the direct electron detector. This allows us to accurately account for the position of diffraction spots in both geometric and dynamical simulations with good agreement with experimental patterns. Further, by introducing appropriate weight factors, simulation of incoherent diffuse intensity, and calculation of the energy spectra of diffracted electrons, simulated patterns can be obtained which accurately capture the many diffraction features on experimental patterns. Workflows and findings of this work can be used to improve pattern indexing routines, as well as the understanding of the physical processes in the formation of on-axis transmission Kikuchi patterns.

Land-use transition (LUT), a pivotal vector for anthropogenic intervention in the carbon cycle, profoundly influences the formation and evolution of regional carbon emission patterns. This study focuses on Hainan, China's sole tropical island, and establishes a model accounting for carbon emissions associated with LUT based on related remote-sensing data, socioeconomic statistics, and energy consumption-related data between 2000 and 2025. We combine spatial autocorrelation analysis, an extended logarithmic mean Divisia index decomposition model, and the Tapio decoupling model to systematically elucidate the spatiotemporal features of LUT-associated carbon emissions, their driving factors, and their decoupling relation with economic growth. Notably, Hainan Province features an LUT involving decreasing and increasing proportions of carbon-sink land and carbon-source land, respectively, with construction land expansion being the primary transition mode driving carbon emission growth. The associated carbon emission response features a spatial differentiation pattern of high values concentrated in the north and west and low values localized in the south and east. In addition, carbon sources and sinks demonstrate considerable spatial agglomeration. Economic output is the core driver promoting carbon emission growth, with improvements in land-use efficiency and energy intensity being critical for carbon emission mitigation. During the examined period, the correlation between LUT-associated carbon emissions and economic growth evolves from weak to strong decoupling, demonstrating the remarkable efficacy of peak carbon and carbon neutrality goals in guiding emission reduction-focused LUT. Overall, this research provides a scientific basis for coordinating LUT and low-carbon development in the Hainan Free Trade Port initiative.

The evaporation of a sessile colloidal suspension droplet on a substrate yields various drying-induced patterns, which are crucial for both technological advancements and fundamental understandings of colloidal droplet evaporation. Several factors influence the formation of various drying-induced patterns on the substrate. In this study, the variation in dried deposit patterns formed after complete evaporation of a gold nanorod (Au-NR) dispersion droplet is investigated by simultaneously varying the characteristics of the surfactant stabilizing the particles and the particle aspect ratio. Here, cetyltrimethylammonium bromide (CTAB) is used to prepare Au-NRs of aspect ratios 3.5 and lower, and the combination of CTAB and benzyl-dodecyldimethylammonium chloride (BDAC) is used to prepare Au-NRs of aspect ratios 5.4 and higher. As the Au-NR dispersion evaporates, coffee-stain patterns with distinct microstructures form. Changes in the characteristics of the surfactant stabilizing the Au-NR dispersion droplets influence their adsorption at the three interfaces during droplet drying and alter the depinning rate of the droplet during the initial stages of evaporation. This, in turn, affects the deposition of Au-NRs outside the coffee stain and the diameter of the coffee stain. Additionally, as the aspect ratios of the Au-NR in the droplet increase, the width of the outer coffee-stain edges and the extent of Au-NR self-assemblies within it significantly increase, as supported by interaction energy calculations. This study demonstrates that changing the surfactant type used to stabilize colloidal particles can significantly impact the drying kinetics and the resultant dried patterns of colloidal suspension droplets.

The organization of bacteria has a central role in shaping interactions, dynamics, and composition within communities and microbiomes. Bacteria form distinct spatial patterns that have often been attributed to microbial processes such as chemotaxis, nutrient transport, and signaling. However, common patterns are observed across distinct bacteria and conditions, suggesting that a general organizing principle could direct bacterial organization. Here, we find that the organization of bacteria is explained by geometric ordering that promotes space-filling efficiency, giving rise to geometric patterns known as Voronoi tessellations. We find that the Voronoi Growth Model accurately predicts bacterial pattern formation in diverse conditions including in biofilms at the liquid-air interface, swimming populations, the zebrafish gut, and conditions that promote swarming. The patterns are observed in two and three dimensions, at the cm and mm length scales, across diverse species (Vibrio cholerae, Pseudomonas aeruginosa, Escherichia coli), arise solely from the principles of Voronoi tessellation, and require no detailed knowledge of microbial processes. Entropic considerations show that bacteria provide little or no information about the pattern formation, which is determined solely by their initial positions and environmental conditions. These findings demonstrate that bacterial communities achieve robust, reproducible organization through a universal geometric principle, linking microbial patterning to the broader biological context of multicellular organization.

From Renaissance drapery to tissue morphogenesis, pattern formation exemplifies how geometry and constraints generate complex structures. In soft and architected matter, motifs such as creases, kinks, and domain walls function as order-parameter textures mediating structural transitions. Yet deterministic and reprogrammable control of such patterns remains a central challenge: conventional geometry-based strategies hardwire functionality into structure, leaving deformation modes defect-sensitive and difficult to reconfigure. Here we introduce a pseudo-dynamic mapping that interprets static deformation fields as trajectories of fictitious particles evolving in engineered energy landscapes. This paradigm provides a forward design strategy in which reshaping potential symmetry and bifurcation structure prescribes diverse reprogrammable solitonic domain-wall-lattices in a single, defect-free metamaterial solely under uniform loading. We demonstrate initiation, modulation, inversion, melting, and annihilation of these patterns, governed by a tunable bifurcation landscape. Predictions are validated through simulation and experiment, culminating in a mechanical display that encodes digital information via domain-wall-bits. This approach bridges nonlinear field theory with practical pattern reprogramming, offering a versatile route for programmable design in architected and adaptive materials.

Physicochemical transformations of starch during ohmic heating considering amylose concentration at high temperatures.

Correlation between irradiated Cu2+ ion agglomeration and self-organized microdot formation on silicon surfaces.

Gallium surfaces were irradiated with a 350fs, 1040nm femtosecond laser while submerged in liquid nitrogen, producing laser-induced periodic surface structures (LIPSS) spanning multiple length scales. Scanning electron microscopy reveals a hierarchical morphology with characteristic periodicities of approximately 10μm, 1μm, 250nm, and down to ~ 30nm. The largest structures (10μm and 1μm) are oriented perpendicular to the laser polarization, consistent with conventional wavelength-scale LIPSS, whereas the subwavelength (~ 250nm) and deep-subwavelength (~ 30nm) features are oriented at large angles relative to the larger patterns. The coexistence of multiple periodicities and their systematic angular relationships indicate a multistep self-organization process that cannot be explained solely by linear optical interference. We propose that plasmonic interactions play a central role in this hierarchical pattern formation. Specifically, wavelength-scale ripple ridges support propagating surface plasmon polaritons (SPPs), while their elongated ridge-like geometry enables localized longitudinal charge oscillations that strongly reshape the near field. Coupling between propagating SPPs and these localized plasmon modes enhances electromagnetic confinement, facilitating the emergence of both subwavelength and deep-subwavelength periodic structures. These results indicate a plasmon-mediated feedback mechanism underlying multiscale surface patterning on gallium under femtosecond laser irradiation.

Resource concentration in the vicinity of plants is observed in drylands as a result of various mechanisms, developed to cope with water scarcity. This often leads to self-organized spatial patterns that enhance drylands’ ecosystem resilience to environmental changes. Numerous vegetation dynamics models have been developed over the past few decades to study this pattern formation. Generally, they represent plant spatial spread as a diffusive process, which captures well species that reproduce via seed dispersal or through clonal growth following the “phalanx” strategy, characterized by slow, compact expansion. However, many dryland species exhibit “guerrilla” clonal growth, characterized by rapid, directional exploration of favourable areas, which is poorly captured by diffusion. To address this limitation, we introduce a novel term for lateral biomass expansion into a classical dryland model. We found conditions suitable for periodic patterns to emerge with a Turing analysis, aiming to test the stability of a uniform solution against uniform and periodic perturbations. However, numerically, these patterns could not be observed by perturbing the homogeneous equilibria with small perturbations, possibly because of the non-linearity of the guerrilla expansion term. Instead, remarkably, the model produced amorphous, far-from-equilibrium patterns when integrated along a rainfall precipitation gradient. These findings highlight the need to represent the diversity of clonal plant strategies in dryland ecosystem models, as they play an important role in pattern formation and, thus, may influence ecosystem resilience and responses to global environmental change. Furthermore, our results highlight the need to move beyond linear analyses when studying systems with nonlinear dispersal dynamics. • Clonal growth is common among plants in dryland ecosystems • We introduce a novel model representing the main clonal growth types in drylands • Vegetation dominated by guerrilla clonal growth forms amorphous patterns • Nonlinear dispersal may require methods beyond classical linear stability analysis.

Intracellular protein patterns govern essential cellular functions by dynamically redistributing proteins between membrane-bound and cytosolic states, conserving their total numbers. This review presents a theoretical framework for understanding such patterns based on mass-conserving reaction-diffusion systems. The emergence, selection, and evolution of patterns are analyzed in terms of mass redistribution and interface motion, resulting in mesoscale laws of coarsening and wavelength selection. A geometric phase-space perspective provides a conceptual tool to link local reactive equilibria with global pattern dynamics through conserved mass fluxes. The Min protein system of Escherichia coli provides a paradigmatic example, enabling direct comparison between theory and experiment. Successive model refinements capture both the robustness of pattern formation and the diversity of dynamic regimes observed in vivo and in vitro. The Min system thus illustrates how to extract predictive, multiscale theory from biochemical detail, providing a foundation for understanding pattern formation in more complex and synthetic systems.

Research note: Integration of GWAS and RNA-seq identifies mutations linked to within feather patterning in domestic chickens.

Eutectic solidification exemplifies nonequilibrium pattern formation, making it a well-studied moving boundary problem. Yet the mechanisms behind the formation of complex-regular microstructures — particularly in highly anisotropic systems with a significant volume fraction of a faceted phase — remain poorly understood. Our understanding of such systems is made complicated by the nonlinear interface kinetics and unique growth dynamics characteristic of faceted phases. To address these challenges, we investigate a model Al-Ge eutectic system, where the faceted Ge phase constitutes a substantial volume fraction ( ∼ 0.35) and where the two solid phases arrange into so-called “fishbone” or “feather” complex-regular patterns. Using synchrotron-based x-ray nano-imaging and nanotomography with high spatial resolution (22 nm per pixel), we capture in real-time the evolution of the solid–liquid interfaces and the resulting three-dimensional microstructures in this faceted/non-faceted eutectic system. By integrating these observations with electron backscattered diffraction, we elucidate the crystallographic biases on the solidification process and the mechanisms driving the formation of such complex-regular microstructures. These findings inform a new growth model for irregular eutectics in (near-)symmetrical phase diagrams, offering insight on advanced microstructural design and processing strategies. More broadly, we demonstrate how interfacial curvature is generated in irregular eutectic alloys and how it depends on the volume fraction of the faceted phase.

While extreme ultraviolet (EUV) lithography has enabled the continued scaling toward high-resolution features, existing processes are limited to patterning of planar two-dimensional (2D) structures. This work demonstrates EUV colloidal Talbot lithography (CTL) for the patterning of 3D nanostructures with 25 nm minimum feature sizes. In this approach, a monolayer of self-assembled nanospheres is utilized as a binary mask and illuminated using a tabletop high-harmonic generation (HHG) EUV source to form a volumetric intensity pattern for proximity-field printing. The interference pattern formation is investigated using finite difference time domain (FDTD) simulations and maintains an adequate fringe contrast within the volume. Experimental results demonstrate the fabrication of 2D nanostructures with tunable unit-cell geometry and 3D nanostructures down to 25 nm using a single exposure. This cost-effective approach enables single-exposure 3D EUV lithography with low hardware requirements and has broad applications in nanophotonics, quantum devices, and advanced materials.

Band-pass filters, which selectively transmit signals within a defined range of input magnitudes, are fundamental components of signal-processing systems. In cellular gene circuits, band-pass behavior has likewise been pursued as a mean to implement complex signal-processing functions. However, previously reported genetic band-pass circuits have typically relied not only on a large number of regulatory components but also on transcriptional cascades involving multiple transcription factors, resulting in long DNA sequences and increased circuit complexity. Here, we first propose a band-pass gene circuit that operates without transcriptional cascades. By co-expressing two variants of the transcription factor BetI that exhibit opposite input-response behaviors-one acting as an inducer-dependent activator and the other as an inducer-dependent repressor-band-pass filtering is achieved solely through differential tuning of their inducer sensitivities. This minimal architecture enables gene expression only within a specific range of intracellular choline concentrations. Furthermore, we demonstrate that this cascade-free band-pass circuit can be exploited to generate spatial expression patterns in Escherichia coli populations in response to a choline diffusion gradient, illustrating its utility for pattern formation in multicellular contexts.