Journal of The Royal Society Interface最新文献

Contemporary dynamical models of human postural control propose an intermittent controller regulating the postural centre of pressure (CoP) about a stable saddle-shaped manifold along anatomical anteroposterior (AP) and mediolateral (ML) axes, releasing CoP in an outwards spiral when inactive. Experimental manipulations can evoke this saddle-type topology in fractal temporal correlations along the AP axis and reducing correlations along the ML axis. However, true effects of task demands may often manifest within angular space between anatomical AP and ML axes-a space not typically modelled explicitly. We tested how instability and attentional load influence postural control across the full angular range of fractal variability along the two-dimensional (2D) support surface. Forty-eight healthy young adults performed a suprapostural Trail Making Test (TMT) while standing on a wobble board, inducing continuous perturbations along the ML axis. Stable, quiet standing exhibited classic saddle-like topology, with stronger fractal temporal correlations in CoP displacements along AP axes. The attentional demand of the TMT did not affect angular variation or strength of fractal temporal correlations across the 2Dsupport surface. However, maintaining upright balance on the wobble board reshaped and reoriented the angular distribution of fractal temporal correlations, accentuating saddle-like angular variation and rotating the strongest fractal temporal correlations predominantly along the ML axis. Stabilizing posture in the face of wobble board instability prompted the saddle-type angular distribution of fractal temporal correlations. These findings challenge the traditional dependence of postural control theories exclusively on external force-plate axes and underscore the significance of multifractality in defining control parameters that govern postural stability across the full angular range of the 2D support surface.

Tails used as inertial appendages induce body rotations of animals and robots-a phenomenon that is governed largely by the ratio of the body and tail moments of inertia. However, vertebrate tails have more degrees of freedom (e.g. number of joints and rotational axes) than most current theoretical models and robotic tails. To understand how morphology affects inertial appendage function, we developed an optimization-based approach that finds the maximally effective tail trajectory and measures error from a target trajectory. For tails of equal total length and mass, increasing the number of equal-length joints increased the complexity of maximally effective tail motions. When we optimized the relative lengths of tail bones while keeping the total tail length, mass and number of joints the same, this optimization-based approach found that the lengths matched the pattern found in the tail bones of mammals specialized for inertial manoeuvring. In both experiments, adding joints enhanced the performance of the inertial appendage, but with diminishing returns, largely due to the total control effort constraint. This optimization-based simulation can compare the maximum performance of diverse inertial appendages that dynamically vary in a moment of inertia in three-dimensional space, predict inertial capabilities from skeletal data and inform the design of robotic inertial appendages.

Microbes often inhabit complex, spatially partitioned environments such as host tissue or soil, but the effects of habitat fragmentation on microbial ecology and infection dynamics are poorly understood. Here, we investigate how habitat fragmentation impacts a prevalent microbial collective defence mechanism: enzymatic degradation of an environmental toxin. Using a theoretical model, we predict that habitat fragmentation can strongly enhance the collective benefits of enzymatic toxin degradation. For the example of [Formula: see text]-lactamase-producing bacteria that mount a collective defence by degrading a [Formula: see text]-lactam antibiotic, we find that realistic levels of habitat fragmentation can allow a population to survive antibiotic doses that greatly exceed those required to kill a non-fragmented population. This 'habitat-fragmentation rescue' is a stochastic effect that originates from variation in bacterial density among different subpopulations and demographic noise. We also study the contrasting case of collective enzymatic foraging, where enzyme activity releases nutrients from the environment; here we find that increasing habitat fragmentation decreases the lag time for population growth but does not change the ecological outcome. Taken together, this work predicts that stochastic effects arising from habitat fragmentation can greatly enhance the effectiveness of microbial collective defence via enzymatic toxin degradation.

Maintaining engineered cell populations' genetic stability is a key challenge in synthetic biology. Synthetic genetic constructs compete with a host cell's native genes for expression resources, burdening the cell and impairing its growth. This creates a selective pressure favouring mutations which alleviate this growth defect by removing synthetic gene expression. Non-functional mutants thus spread in cell populations, eventually making them lose engineered functions. Past work has attempted to limit mutation spread by coupling synthetic gene expression to survival. However, these approaches are highly context-dependent and must be tailor-made for each particular synthetic gene circuit to be retained. By contrast, we develop and analyse a biomolecular controller which depresses mutant cell growth independently of the mutated synthetic gene's identity. Modelling shows how our design can be deployed alongside various synthetic circuits without any re-engineering of its genetic components, outperforming extant gene-specific mutation spread mitigation strategies. Our controller's performance is evaluated using a novel simulation approach which leverages resource-aware cell modelling to directly link a circuit's design parameters to its population-level behaviour. Our design's adaptability promises to mitigate mutation spread in an expanded range of applications, while our analyses provide a blueprint for using resource-aware cell models in circuit design.

Spiders use piriform silk attachment discs to adhere threads during web construction and to secure safety lines. Water could degrade attachment disc adhesion by either interfering with placement of the discs or later reducing adhesion during loading. We tested the effect of water on the adhesion of attachment discs for the spider Latrodectus hesperus, which spins webs in mostly dry environments. We compared adhesion for discs spun on wet versus dry glass that were subsequently loaded in either wet or dry conditions. Attachment discs placed on wet glass showed similar adhesion to discs placed on dry glass. However, water significantly decreased both peak force of adhesion and work of adhesion when loading occurred under wet conditions, regardless of initial placement conditions. Furthermore, failure mode shifted from rupture of draglines in dry loading conditions to adhesive failure of discs in wet loading conditions. Our results show the importance of considering both the conditions in which biological structures are produced and those in which the structures perform as potentially independent factors for performance. Our results also suggest that adhesion in wet conditions can challenge some spiders, potentially leading to specialization of attachment discs for riparian or aquatic species.

A continuing frustration for origin of life scientists is that abiotic and, by extension, pre-biotic attempts to develop self-sustaining, evolving molecular systems tend to produce more dead-end substances than macromolecular products with the necessary potential for biostructure and function - the so-called 'tar problem'. Nevertheless primordial life somehow emerged despite that presumed handicap. A resolution of this problem is important in emergence-of-life science because it would provide valuable guidance in choosing subsequent paths of investigation, such as identifying pre-biotic patterns on Mars. To study the problem we set up a simple non-equilibrium flow dynamical model for the coupled temperature and mass dynamics of the decomposition of a polymeric carbohydrate adsorbed on a mineral surface, with incident stochastic thermal fluctuations. Results show that the model system behaves as a reciprocating thermochemical oscillator. The output fluctuation distribution is bimodal, with a right-weighted component that guarantees a bias towards detachment and desorption of monomeric species such as ribose, even while tar is formed concomitantly. This fluctuating thermochemical reciprocator may ensure that non-performing polymers can be fractionated into a refractory carbon reservoir and active monomers which may be reincorporated into better-performing polymers with less vulnerability towards adsorptive tarring.

Bicycle infrastructure networks must meet the needs of cyclists to position cycling as a viable transportation choice in cities. In particular, protected infrastructure should be planned cohesively for the whole city and spacious enough to accommodate all cyclists safely and prevent cyclist congestion-a common problem in cycling cities like Copenhagen. Here, we devise an adaptive method for optimal bicycle network design and for evaluating congestion criticalities on bicycle paths. The method goes beyond static network measures, using computationally efficient adaptation rules inspired by optimal transport on the dynamically updating multilayer network of roads and protected bicycle lanes. Street capacities and cyclist flows reciprocally control each other to optimally accommodate cyclists on streets with one control parameter that dictates the preference of bicycle infrastructure over roads. Applying our method to Copenhagen confirms that the city's bicycle network is generally well-developed. However, we are able to identify the network's bottlenecks, and we find, at a finer scale, disparities in network accessibility and criticalities between different neighbourhoods. Our model and results are generalizable beyond this particular case study to serve as a scalable and versatile tool for aiding urban planners in designing cycling-friendly cities.

The true slime mould Physarum polycephalum has the remarkable capability to perform self-organized activities such as network formation among food sources. Despite well reproducing the emergence of slime networks, existing models are limited in the investigation of the minimal mechanisms, at the microscopic scale, that ensure robust problem-solving capabilities at the macroscopic scale. To this end, we develop three progressively more complex multi-agent models to provide a flexible framework to understand the self-organized foraging and network formation behaviours of Physarum. The hierarchy of models allows for a stepwise investigation of the minimal set of rules that allow bio-inspired computing agents to achieve the desired behaviours on nutrient-poor substrates. By introducing a quantitative measure of connectedness among food sources, we assess the sensitivity of the model to user-defined and bio-inspired parameters, as well as the robustness of the model to parameter heterogeneity across agents. We ultimately observe the robust emergence of pattern formation, in line with experimental evidence. Overall, our study sheds light on the basic mechanisms of self-organization and paves the way towards the development of decentralized strategies for network formation in engineered systems, focusing on trade-offs between biological fidelity and computational efficiency.

Everyday experience shows that cellular sheets are stiffened by the presence of a pressurized gas: from bicycle inner tubes to bubble wrap, the presence of an internal pressure increases the stiffness of otherwise floppy structures. The same is true of plants, with turgor pressure (due to the presence of water) taking the place of gas pressure; indeed, in the absence of water, many plants wilt. However, the mechanical basis of this stiffening is somewhat opaque: simple attempts to rationalize it suggest that the stiffness should be independent of the pressure, at odds with everyday experience. Here, we study the mechanics of sheets that are a single-cell thick and show how a pressure-dependent bending stiffness may arise. Our model rationalizes observations of turgor-driven shrinkage in plant cells and also suggests that turgor is unlikely to provide significant structural support in many monolayer leaves, such as those found in mosses. However, for such systems, turgor does provide a way to control leaf shape, in accordance with observations of curling upon drying of moss leaves. Guided by our results, we also present a biomimetic actuator that uncurls upon pressurization.

The reproduction number, the mean number of secondary cases infected by each primary case, gives an indication of the effort required to control the disease. Beyond the well-known basic reproduction number, there are two natural extensions, namely the control and effective reproduction numbers. As behaviour, population immunity and viral characteristics can change with time, these reproduction numbers can vary over time. Real-world data can be complex, so in this work we consider a generalized additive model to smooth surveillance data through the explicit incorporation of day-of-the-week effects, to provide a simple measure of the time-varying growth rate associated with the data. Converting the resulting spline into an estimator for both the control and effective reproduction numbers requires assumptions on a model structure, which we here assume to be a compartmental model. The reproduction numbers calculated are based on both simulated and real-world data, and are compared with estimates from an already existing tool. The derived method for estimating the time-varying reproduction number is effective, efficient and comparable with other methods. It provides a useful alternative approach, which can be included as part of a toolbox of models, that is particularly apt at smoothing out day-of-the-week effects in surveillance.