Journal of The Royal Society Interface最新文献

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.

Wave propagation in the heart tube is key to establishing an early pumping mechanism, as explained by impedance pump theory in zebrafish. Though initially proposed for embryonic blood circulation, the role of impedance-like behaviour in the mature cardiovascular system remains unclear. This study focuses on the understudied physiological mechanism of longitudinal displacement in the adult aorta caused by the long-axis motion of the heart. Using magnetic resonance imaging on 159 individuals, we compared aortic displacement profiles between a control group and those with heart failure, revealing a significant difference in aortic stretch between the two groups. Building on this clinical evidence, we conducted in vitro experiments to isolate the effects of longitudinal aortic wave pumping by eliminating the pumping action of the heart. We identified three biomechanical properties of stretch-related longitudinal wave pumping that exhibit characteristics like impedance pump: (i) a nonlinear flow-frequency relationship, (ii) bidirectional flow, and (iii) the potential for both positive and negative flow at a fixed frequency, contingent upon the aorta's wave speed dictating the wave state. Our results demonstrate for the first time that this mechanism generates a significant flow, potentially providing a supplementary pumping mechanism for the heart.

Vaccines are a crucial tool for controlling infectious diseases, yet rarely offer perfect protection. 'Vaccine efficacy' describes a population-level effect measured in clinical trials, but mathematical models used to evaluate the impact of vaccination campaigns require specifying how vaccines fail at the individual level, which is often impossible to measure. Does 90% efficacy imply perfect protection in 90% of people and no protection in 10% ('all-or-nothing') or that the per-exposure risk is reduced by 90% in all vaccinated individuals ('leaky') or somewhere in between? Here, we systematically investigate the role of vaccine failure mode in controlling ongoing epidemics. We find that the difference in population-level impact between all-or-nothing and leaky vaccines can be substantial when R₀ is higher, vaccines efficacy is intermediate, and vaccines slow but cannot curtail an outbreak. Comparing COVID-19 pandemic phases, we show times when model predictions would have been most sensitive to assumptions about vaccine failure mode. When determining the optimal risk group to prioritize for limited vaccines, we find that modelling a leaky vaccine as all-or-nothing (or vice versa) can change the recommended target group. Overall, we conclude that models of vaccination campaigns should include uncertainty about vaccine failure mode in their design and interpretation.

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.

Efficient energy harvesting, conversion and recycling technologies are crucial for addressing the challenges faced by modern societies and the global economy. The potential of harnessing mid-infrared (mid-IR) thermal radiation as a pervasive and readily available energy source has so far not been fully exploited, particularly through bioinspiration. In this article, by reviewing existing photon-based strategies and the efficiency of natural systems in harnessing light and thermal radiation, I highlight the promising role of bioinspiration in enhancing energy capture, conversion and recycling. Natural photonic structures found in various organisms, including insects, birds and plants, exhibit sophisticated optical properties that can be leveraged for energy-efficient applications. These developments pave the way for future research and innovation in bioinspired energy solutions. Ultimately, they contribute to the pursuit of a sustainable and environmentally conscious future by harnessing the beauty of nature's designs to meet humankind's energy needs.

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.

Building mathematical models of brains is difficult because of the sheer complexity of the problem. One potential starting point is basal cognition, which gives an abstract representation of a range of organisms without central nervous systems, including fungi, slime moulds and bacteria. We propose one such model, demonstrating how a combination of oscillatory and current-based reinforcement processes can be used to couple resources in an efficient manner, mimicking the way these organisms function. A key ingredient in our model, not found in previous basal cognition models, is that we explicitly model oscillations in the number of particles (i.e. the nutrients, chemical signals or similar, which make up the biological system) and the flow of these particles within the modelled organisms. Using this approach, our model builds efficient solutions, provided the environmental oscillations are sufficiently out of phase. We further demonstrate that amplitude differences can promote efficient solutions and that the system is robust to frequency differences. In the context of these findings, we discuss connections between our model and basal cognition in biological systems and slime moulds, in particular, how oscillations might contribute to self-organized problem-solving by these organisms.

Malignant tumorigenesis is a complex process involving growth, invasion and mechanical deformation of a cancerous tissue. In this paper, a biomechanical model is proposed to couple the mechanical and biological mechanisms governing invasive tumour development. As an example, this model is applied to investigate the spatio-temporal evolution of tissue stresses in an invasive tumour spheroid and its host tissue. I show that cancer invasiveness lowers the compressive tissue stresses and blurs the stress distribution across the cancerous-normal tissue boundary, both consistent with experimental observations. Importantly, with the steady propagation of the cancerous region driven by persistent cancer invasion, tumour stresses are predicted to saturate rather than keep increasing as in benign tumour growth. The model is further used to analyse the deformation and stress state of a cancerous tissue being cut into two pieces, and reproduces the bulge of the cut surface observed in experiments. I hope this study can pave the way for the quantitative evaluation of mechanical states in cancer.

Culturing living cells in three-dimensional environments increases the biological relevance of laboratory experiments, but requires solutes to overcome a diffusion barrier to reach the centre of cellular constructs. We present a theoretical and numerical investigation that brings a mechanistic understanding of how microfluidic culture conditions, including chamber size, inlet fluid velocity and spatial confinement, affect solute distribution within three-dimensional cellular constructs. Contact with the chamber substrate reduces the maximally achievable construct radius by 15%. In practice, finite diffusion and convection kinetics in the microfluidic chamber further lower that limit. The benefits of external convection are greater if transport rates across diffusion-dominated areas are high. Those are omnipresent and include the diffusive boundary layer growing from the fluid-construct interface and regions near corners where fluid is recirculating. Such regions multiply the required convection to achieve a given solute penetration by up to 100, so chip designs ought to minimize them. Our results define conditions where complete solute transport into an avascular three-dimensional cell construct is achievable and applies to real chambers without needing to simulate their exact geometries.