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Wind-dispersed plants have evolved ingenious ways to lift their seeds 1 , 2 . The common dandelion uses a bundle of drag-enhancing bristles (the pappus) that helps to keep their seeds aloft. This passive flight mechanism is highly effective, enabling seed dispersal over formidable distances 3 , 4 ; however, the physics underpinning pappus-mediated flight remains unresolved. Here we visualized the flow around dandelion seeds, uncovering an extraordinary type of vortex. This vortex is a ring of recirculating fluid, which is detached owing to the flow passing through the pappus. We hypothesized that the circular disk-like geometry and the porosity of the pappus are the key design features that enable the formation of the separated vortex ring. The porosity gradient was surveyed using microfabricated disks, and a disk with a similar porosity was found to be able to recapitulate the flow behaviour of the pappus. The porosity of the dandelion pappus appears to be tuned precisely to stabilize the vortex, while maximizing aerodynamic loading and minimizing material requirements. The discovery of the separated vortex ring provides evidence of the existence of a new class of fluid behaviour around fluid-immersed bodies that may underlie locomotion, weight reduction and particle retention in biological and manmade structures. The flight of dandelion seeds is enabled by an extraordinary vortex ring, which was revealed by the visualization of the flow around the seed.

Beginning in May 2022, Mpox virus spread rapidly in high-income countries through close human-to-human contact primarily amongst communities of gay, bisexual and men who have sex with men (GBMSM). Behavioural change arising from increased knowledge and health warnings may have reduced the rate of transmission and modified Vaccinia-based vaccination is likely to be an effective longer-term intervention. We investigate the UK epidemic presenting 26-week projections using a stochastic discrete-population transmission model which includes GBMSM status, rate of formation of new sexual partnerships, and clique partitioning of the population. The Mpox cases peaked in mid-July; our analysis is that the decline was due to decreased transmission rate per infected individual and infection-induced immunity among GBMSM, especially those with the highest rate of new partners. Vaccination did not cause Mpox incidence to turn over, however, we predict that a rebound in cases due to behaviour reversion was prevented by high-risk group-targeted vaccination. An outbreak of Mpox in the UK began in May 2022 and peaked in July. In this modelling study, the authors show that the decline in cases was likely due to behavioural changes among high-risk populations, whilst vaccination could prevent a rebound.

Baleen whales (mysticetes) use vocalizations to mediate their complex social and reproductive behaviours in vast, opaque marine environments 1 . Adapting to an obligate aquatic lifestyle demanded fundamental physiological changes to efficiently produce sound, including laryngeal specializations 2 – 4 . Whereas toothed whales (odontocetes) evolved a nasal vocal organ 5 , mysticetes have been thought to use the larynx for sound production 1 , 6 – 8 . However, there has been no direct demonstration that the mysticete larynx can phonate, or if it does, how it produces the great diversity of mysticete sounds 9 . Here we combine experiments on the excised larynx of three mysticete species with detailed anatomy and computational models to show that mysticetes evolved unique laryngeal structures for sound production. These structures allow some of the largest animals that ever lived to efficiently produce frequency-modulated, low-frequency calls. Furthermore, we show that this phonation mechanism is likely to be ancestral to all mysticetes and shares its fundamental physical basis with most terrestrial mammals, including humans 10 , birds 11 , and their closest relatives, odontocetes 5 . However, these laryngeal structures set insurmountable physiological limits to the frequency range and depth of their vocalizations, preventing them from escaping anthropogenic vessel noise 12 , 13 and communicating at great depths 14 , thereby greatly reducing their active communication range. Studies of vocal production in baleen whales show that their larynx has evolved unique structures that enable their low-frequency vocalizations but limit their active communication range.

Ordinary differential equation (ODE) models are a key tool to understand complex mechanisms in systems biology. These models are studied using various approaches, including stability and bifurcation analysis, but most frequently by numerical simulations. The number of required simulations is often large, e.g., when unknown parameters need to be inferred. This renders efficient and reliable numerical integration methods essential. However, these methods depend on various hyperparameters, which strongly impact the ODE solution. Despite this, and although hundreds of published ODE models are freely available in public databases, a thorough study that quantifies the impact of hyperparameters on the ODE solver in terms of accuracy and computation time is still missing. In this manuscript, we investigate which choices of algorithms and hyperparameters are generally favorable when dealing with ODE models arising from biological processes. To ensure a representative evaluation, we considered 142 published models. Our study provides evidence that most ODEs in computational biology are stiff, and we give guidelines for the choice of algorithms and hyperparameters. We anticipate that our results will help researchers in systems biology to choose appropriate numerical methods when dealing with ODE models.

Morphogen signals are essential for cell fate specification during embryogenesis. Some receptors that sense these morphogens are known to localize to only the apical or basolateral membrane of polarized cell lines in vitro. How such localization affects morphogen sensing and patterning in the developing embryo remains unknown. Here, we show that the formation of a robust BMP signaling gradient in the early mouse embryo depends on the restricted, basolateral localization of BMP receptors. The mis-localization of receptors to the apical membrane results in ectopic BMP signaling in the mouse epiblast in vivo. With evidence from mathematical modeling, human embryonic stem cells in vitro, and mouse embryos in vivo, we find that the geometric compartmentalization of BMP receptors and ligands creates a signaling gradient that is buffered against fluctuations. Our results demonstrate the importance of receptor localization and embryo geometry in shaping morphogen signaling during embryogenesis. How receptor localization affects morphogen gradient formation during embryonic development is unclear. Here, the authors study the relationship between the BMP gradient, receptor localization, and compartmentalized geometry in the early mouse embryo, using experimental data and computational simulation.

African swine fever (ASF) is a severe viral disease that is currently spreading among domestic pigs and wild boar ( Sus scrofa ) in large areas of Eurasia. Wild boar play a key role in the spread of ASF, yet despite their significance, little is known about the key mechanisms that drive infection transmission and disease persistence. A mathematical model of the wild boar ASF system is developed that captures the observed drop in population density, the peak in infected density and the persistence of the virus observed in ASF outbreaks. The model results provide insight into the key processes that drive the ASF dynamics and show that environmental transmission is a key mechanism determining the severity of an infectious outbreak and that direct frequency dependent transmission and transmission from individuals that survive initial ASF infection but eventually succumb to the disease are key for the long-term persistence of the virus. By considering scenarios representative of Estonia and Spain we show that faster degradation of carcasses in Spain, due to elevated temperature and abundant obligate scavengers, may reduce the severity of the infectious outbreak. Our results also suggest that the higher underlying host density and longer breeding season associated with supplementary feeding leads to a more pronounced epidemic outbreak and persistence of the disease in the long-term. The model is used to assess disease control measures and suggests that a combination of culling and infected carcass removal is the most effective method to eradicate the virus without also eradicating the host population, and that early implementation of these control measures will reduce infection levels whilst maintaining a higher host population density and in some situations prevent ASF from establishing in a population.

This research paper investigates discrete predator-prey dynamics with two logistic maps. The study extensively examines various aspects of the system’s behavior. Firstly, it thoroughly investigates the existence and stability of fixed points within the system. We explores the emergence of transcritical bifurcations, period-doubling bifurcations, and Neimark-Sacker bifurcations that arise from coexisting positive fixed points. By employing central bifurcation theory and bifurcation theory techniques. Chaotic behavior is analyzed using Marotto’s approach. The OGY feedback control method is implemented to control chaos. Theoretical findings are validated through numerical simulations.

DeGroot dynamics, a prototypical model of opinion formation under social influence, tends to yield biased consensus in centralized groups. However, such a consensus can be accurate if competent individuals occupy central positions and exert disproportionate influence. Focusing on groups with stable memberships that engage in iterative consensus formation across a sequence of issues, we propose social network rewiring as a self-organization mechanism that identifies competent members and positions them centrally, thereby empowering them to make decisions on behalf of the group. Numerical experiments show that the effects of rewiring on consensus accuracy and structural adaptability oppose each other depending on its search scope. Local rewiring—where agents search for new connections within their immediate neighborhoods—progressively concentrates influence among competent members and enhances consensus accuracy but reduces the group’s adaptability to evolving environments, modeled as temporal shifts in individual competence. In contrast, global rewiring—where agents may connect to any member of the group—preserves adaptability but significantly undermines accuracy. A unique contribution of this study lies in its novel approach to information integration for collective decision-making, shifting the focus from the intrinsic information individuals possess to information about agents’ competence, acquired from local interactions and communicated through rewiring.

Vertex models are a widespread approach for describing the biophysics and behaviors of multicellular systems, especially of epithelial tissues. Vertex models describe a wide variety of developmental scenarios and behaviors like cell rearrangement and tissue folding. Often, these models are implemented as single-use or closed-source software, which inhibits reproducibility and decreases accessibility for researchers with limited proficiency in software development and numerical methods. We developed a physics-based vertex model methodology in Tissue Forge, an open-source, particle-based modeling and simulation environment. Our methodology describes the properties and processes of vertex model objects on the basis of vertices, which allows integration of vertex modeling with the particle-based formalism of Tissue Forge, enabling an environment for developing mixed-method models of multicellular systems. Our methodology in Tissue Forge inherits all features provided by Tissue Forge, delivering open-source, extensible vertex modeling with interactive simulation, real-time simulation visualization and model sharing in the C, C++ and Python programming languages and a Jupyter Notebook. Demonstrations show a vertex model of cell sorting and a mixed-method model of cell migration combining vertex- and particle-based models. Our methodology provides accessible vertex modeling for a broad range of scientific disciplines, and we welcome community-developed contributions to our open-source software implementation.

Computational techniques have significantly advanced our understanding of cardiac electrophysiology, yet they have predominantly concentrated on averaged models that do not represent the intricate dynamics near individual cardiomyocytes. Recently, accurate models representing individual cells have gained popularity, enabling analysis of the electrophysiology at the micrometer level. Here, we evaluate five mathematical models to determine their computational efficiency and physiological fidelity. Our findings reveal that cell-based models introduced in recent literature offer both efficiency and precision for simulating small tissue samples (comprising thousands of cardiomyocytes). Conversely, the traditional bidomain model and its simplified counterpart, the monodomain model, are more appropriate for larger tissue masses (encompassing millions to billions of cardiomyocytes). For simulations requiring detailed parameter variations along individual cell membranes, the EMI model emerges as the only viable choice. This model distinctively accounts for the extracellular (E), membrane (M), and intracellular (I) spaces, providing a comprehensive framework for detailed studies. Nonetheless, the EMI model’s applicability to large-scale tissues is limited by its substantial computational demands for subcellular resolution.