Truly Tiny Acoustic Biomolecules for Ultrasound Imaging and Therapy.

Nanotechnology offers significant advantages for medical imaging and therapy, including enhanced contrast and precision targeting. However, integrating these benefits into ultrasonography is challenging due to the size and stability constraints of conventional bubble-based agents. Here bicones, truly tiny acoustic contrast agents based on gas vesicles (GVs), a unique class of air-filled protein nanostructures naturally produced in buoyant microbes, are described. It is shown that these sub-80 nm particles can be effectively detected both in vitro and in vivo, infiltrate tumors via leaky vasculature, deliver potent mechanical effects through ultrasound-induced inertial cavitation, and are easily engineered for molecular targeting, prolonged circulation time, and payload conjugation.

Broad Elevation Projection Super-Resolution Ultrasound (BEP-SRUS) Imaging With a 1-D Unfocused Linear Array.

Super-resolution ultrasound (SRUS) through localizing spatially isolated microbubbles (MBs) has been demonstrated to overcome the wave diffraction limit and reveal the microvascular structure and flow information at the microscopic scale. However, 3-D SRUS imaging remains a challenge due to the fabrication and computational complexity of 2-D matrix array probes. Inspired by X-ray radiography which can present information within a volume in a single projection image with much simpler hardware than X-ray computerized tomography (CT), this study investigates the feasibility of broad elevation projection super-resolution (BEP-SR) ultrasound using a 1-D unfocused linear array. Both simulation and in vitro experiments were conducted on 3-D microvessel phantoms. In vivo demonstration was done on the Rabbit kidney. Data from a 1-D linear array with and without an elevational focus were synthesized by summing up row signals acquired from a 2-D matrix array with and without delays. A full 3-D reconstruction was also generated as the reference, using the same data of the 2-D matrix array but without summing row signals. Results show that using an unfocused 1-D array probe, BEP-SR can capture significantly more information within a volume in both vascular structure and flow velocity than the conventional 1-D elevational-focused probe. Compared with the 2-D projection image of the full 3-D SRUS results using the 2-D array probe with the same aperture size, the 2-D projection SRUS image of BEP-SR has similar volume coverage, using 32 folds fewer independent elements. This study demonstrates BEP-SR's ability of high-resolution imaging of microvascular structures and flow velocity within a 3-D volume at significantly reduced costs. The proposed BEP method could significantly benefit the clinical translation of the SRUS imaging technique by making it more affordable and repeatable.

Remote control of mechanochemical reactions under physiological conditions using biocompatible focused ultrasound.

External control of chemical reactions in biological settings with spatial and temporal precision is a grand challenge for noninvasive diagnostic and therapeutic applications. While light is a conventional stimulus for remote chemical activation, its penetration is severely attenuated in tissues, which limits biological applicability. On the other hand, ultrasound is a biocompatible remote energy source that is highly penetrant and offers a wide range of functional tunability. Coupling ultrasound to the activation of specific chemical reactions under physiological conditions, however, remains a challenge. Here, we describe a synergistic platform that couples the selective mechanochemical activation of mechanophore-functionalized polymers with biocompatible focused ultrasound (FUS) by leveraging pressure-sensitive gas vesicles (GVs) as acousto-mechanical transducers. The power of this approach is illustrated through the mechanically triggered release of covalently bound fluorogenic and therapeutic cargo molecules from polymers containing a masked 2-furylcarbinol mechanophore. Molecular release occurs selectively in the presence of GVs upon exposure to FUS under physiological conditions. These results showcase the viability of this system for enabling remote control of specific mechanochemical reactions with spatiotemporal precision in biologically relevant settings and demonstrate the translational potential of polymer mechanochemistry.

Truly tiny acoustic biomolecules for ultrasound imaging and therapy.

Nanotechnology offers significant advantages for medical imaging and therapy, including enhanced contrast and precision targeting. However, integrating these benefits into ultrasonography has been challenging due to the size and stability constraints of conventional bubble-based agents. Here we describe bicones, truly tiny acoustic contrast agents based on gas vesicles, a unique class of air-filled protein nanostructures naturally produced in buoyant microbes. We show that these sub-80 nm particles can be effectively detected both in vitro and in vivo, infiltrate tumors via leaky vasculature, deliver potent mechanical effects through ultrasound-induced inertial cavitation, and are easily engineered for molecular targeting, prolonged circulation time, and payload conjugation.

Tolerance-conferring defensive symbionts and the evolution of parasite virulence.

Defensive symbionts in the host microbiome can confer protection from infection or reduce the harms of being infected by a parasite. Defensive symbionts are therefore promising agents of biocontrol that could be used to control or ameliorate the impact of infectious diseases. Previous theory has shown how symbionts can evolve along the parasitism-mutualism continuum to confer greater or lesser protection to their hosts and in turn how hosts may coevolve with their symbionts to potentially form a mutualistic relationship. However, the consequences of introducing a defensive symbiont for parasite evolution and how the symbiont may coevolve with the parasite have received relatively little theoretical attention. Here, we investigate the ecological and evolutionary implications of introducing a tolerance-conferring defensive symbiont into an established host-parasite system. We show that while the defensive symbiont may initially have a positive impact on the host population, parasite and symbiont evolution tend to have a net negative effect on the host population in the long term. This is because the introduction of the defensive symbiont always selects for an increase in parasite virulence and may cause diversification into high- and low-virulence strains. Even if the symbiont experiences selection for greater host protection, this simply increases selection for virulence in the parasite, resulting in a net negative effect on the host population. Our results therefore suggest that tolerance-conferring defensive symbionts may be poor biocontrol agents for population-level infectious disease control.

Non-pharmaceutical interventions and the emergence of pathogen variants.

Non-pharmaceutical interventions (NPIs), such as social distancing and contact tracing, are important public health measures that can reduce pathogen transmission. In addition to playing a crucial role in suppressing transmission, NPIs influence pathogen evolution by mediating mutation supply, restricting the availability of susceptible hosts, and altering the strength of selection for novel variants. Yet it is unclear how NPIs might affect the emergence of novel variants that are able to escape pre-existing immunity (partially or fully), are more transmissible or cause greater mortality. We analyse a stochastic two-strain epidemiological model to determine how the strength and timing of NPIs affect the emergence of variants with similar or contrasting life-history characteristics to the wild type. We show that, while stronger and timelier NPIs generally reduce the likelihood of variant emergence, it is possible for more transmissible variants with high cross-immunity to have a greater probability of emerging at intermediate levels of NPIs. This is because intermediate levels of NPIs allow an epidemic of the wild type that is neither too small (facilitating high mutation supply), nor too large (leaving a large pool of susceptible hosts), to prevent a novel variant from becoming established in the host population. However, since one cannot predict the characteristics of a variant, the best strategy to prevent emergence is likely to be an implementation of strong, timely NPIs.

Antigenic evolution of SARS-CoV-2 in immunocompromised hosts.

OBJECTIVES/AIMS: Prolonged infections of immunocompromised individuals have been proposed as a crucial source of new variants of SARS-CoV-2 during the COVID-19 pandemic. In principle, sustained within-host antigenic evolution in immunocompromised hosts could allow novel immune escape variants to emerge more rapidly, but little is known about how and when immunocompromised hosts play a critical role in pathogen evolution. MATERIALS AND METHODS: Here, we use a simple mathematical model to understand the effects of immunocompromised hosts on the emergence of immune escape variants in the presence and absence of epistasis. CONCLUSIONS: We show that when the pathogen does not have to cross a fitness valley for immune escape to occur (no epistasis), immunocompromised individuals have no qualitative effect on antigenic evolution (although they may accelerate immune escape if within-host evolutionary dynamics are faster in immunocompromised individuals). But if a fitness valley exists between immune escape variants at the between-host level (epistasis), then persistent infections of immunocompromised individuals allow mutations to accumulate, therefore, facilitating rather than simply speeding up antigenic evolution. Our results suggest that better genomic surveillance of infected immunocompromised individuals and better global health equality, including improving access to vaccines and treatments for individuals who are immunocompromised (especially in lower- and middle-income countries), may be crucial to preventing the emergence of future immune escape variants of SARS-CoV-2.

Critical weaknesses in shielding strategies for COVID-19.

The COVID-19 pandemic, caused by the coronavirus SARS-CoV-2, has led to a wide range of non-pharmaceutical interventions being implemented around the world to curb transmission. However, the economic and social costs of some of these measures, especially lockdowns, has been high. An alternative and widely discussed public health strategy for the COVID-19 pandemic would have been to 'shield' those most vulnerable to COVID-19 (minimising their contacts with others), while allowing infection to spread among lower risk individuals with the aim of reaching herd immunity. Here we retrospectively explore the effectiveness of this strategy using a stochastic SEIR framework, showing that even under the unrealistic assumption of perfect shielding, hospitals would have been rapidly overwhelmed with many avoidable deaths among lower risk individuals. Crucially, even a small (20%) reduction in the effectiveness of shielding would have likely led to a large increase (>150%) in the number of deaths compared to perfect shielding. Our findings demonstrate that shielding the vulnerable while allowing infections to spread among the wider population would not have been a viable public health strategy for COVID-19 and is unlikely to be effective for future pandemics.

Incorporating domain growth into hybrid methods for reaction-diffusion systems.

Reaction-diffusion mechanisms are a robust paradigm that can be used to represent many biological and physical phenomena over multiple spatial scales. Applications include intracellular dynamics, the migration of cells and the patterns formed by vegetation in semi-arid landscapes. Moreover, domain growth is an important process for embryonic growth and wound healing. There are many numerical modelling frameworks capable of simulating such systems on growing domains; however, each of these may be well suited to different spatial scales and particle numbers. Recently, spatially extended hybrid methods on static domains have been produced to bridge the gap between these different modelling paradigms in order to represent multi-scale phenomena. However, such methods have not been developed with domain growth in mind. In this paper, we develop three hybrid methods on growing domains, extending three of the prominent static-domain hybrid methods. We also provide detailed algorithms to allow others to employ them. We demonstrate that the methods are able to accurately model three representative reaction-diffusion systems accurately and without bias.

The blending region hybrid framework for the simulation of stochastic reaction-diffusion processes.

The simulation of stochastic reaction-diffusion systems using fine-grained representations can become computationally prohibitive when particle numbers become large. If particle numbers are sufficiently high then it may be possible to ignore stochastic fluctuations and use a more efficient coarse-grained simulation approach. Nevertheless, for multiscale systems which exhibit significant spatial variation in concentration, a coarse-grained approach may not be appropriate throughout the simulation domain. Such scenarios suggest a hybrid paradigm in which a computationally cheap, coarse-grained model is coupled to a more expensive, but more detailed fine-grained model, enabling the accurate simulation of the fine-scale dynamics at a reasonable computational cost. In this paper, in order to couple two representations of reaction-diffusion at distinct spatial scales, we allow them to overlap in a 'blending region'. Both modelling paradigms provide a valid representation of the particle density in this region. From one end of the blending region to the other, control of the implementation of diffusion is passed from one modelling paradigm to another through the use of complementary 'blending functions' which scale up or down the contribution of each model to the overall diffusion. We establish the reliability of our novel hybrid paradigm by demonstrating its simulation on four exemplar reaction-diffusion scenarios.

Doppler Passive Acoustic Mapping.

In therapeutic ultrasound using microbubbles, it is essential to drive the microbubbles into the correct type of activity and the correct location to produce the desired biological response. Although passive acoustic mapping (PAM) is capable of locating where microbubble activities are generated, it is well known that microbubbles rapidly move within the ultrasound beam. We propose a technique that can image microbubble movement by estimating their velocities within the focal volume. Microbubbles embedded within a wall-less channel of a tissue-mimicking material were sonicated using 1-MHz focused ultrasound. The acoustic emissions generated by the microbubbles were captured with a linear array (L7-4). PAM with robust Capon beamforming was used to localize the microbubble acoustic emissions. We spectrally analyzed the time trace of each position and isolated the higher harmonics. Microbubble velocity maps were constructed from the position-dependent Doppler shifts at different time points during sonication. Microbubbles moved primarily away from the transducer at velocities on the order of 1 m/s due to primary acoustic radiation forces, producing a time-dependent velocity distribution. We detected microbubble motion both away and toward the receiving array, revealing the influence of acoustic radiation forces and fluid motion due to the ultrasound exposure. High-speed optical images confirmed the acoustically measured microbubble velocities. Doppler PAM enables passive estimation of microbubble motion and may be useful in therapeutic applications, such as drug delivery across the blood-brain barrier, sonoporation, sonothrombolysis, and drug release.

Spatiotemporal Assessment of the Cellular Safety of Cavitation-Based Therapies by Passive Acoustic Mapping.

Many useful therapeutic bio-effects can be generated using ultrasound-induced cavitation. However, cavitation is also capable of causing unwanted cellular and vascular damage, which should be monitored to ensure treatment safety. In this work, the unique opportunity provided by passive acoustic mapping (PAM) to quantify cavitation dose across an entire volume of interest during therapy is utilised to provide setup-independent measures of spatially localised cavitation dose. This spatiotemporally quantifiable cavitation dose is then related to the level of cellular damage generated. The cavitation-mediated destruction of equine red blood cells mixed with one of two types of cavitation nuclei at a variety of concentrations is investigated. The blood is placed within a 0.5-MHz ultrasound field and exposed to a range of peak rarefactional pressures up to 2 MPa, with 50 to 50,000 cycle pulses maintaining a 5% duty cycle. Two co-planar linear arrays at 90° to each other are used to generate 400-µm-resolution frequency domain robust capon beamforming PAM maps, which are then used to generate estimates of cavitation dose. A relationship between this cavitation dose and the levels of haemolysis generated was found which was comparable regardless of the applied acoustic pressure, pulse length, cavitation agent type or concentration used. PAM was then used to monitor cellular damage in multiple locations within a tissue phantom simultaneously, with the damage-cavitation dose relationship being similar for the two experimental models tested. These results lay the groundwork for this method to be applied to other measures of safety, allowing for improved ultrasound monitoring of cavitation-based therapies.

Unbiased on-lattice domain growth.

Domain growth is a key process in many areas of biology, including embryonic development, the growth of tissue, and limb regeneration. As a result, mechanisms for incorporating it into traditional models for cell movement, interaction, and proliferation are of great importance. A previously well-used method to incorporate domain growth into on-lattice reaction-diffusion models causes a buildup of particles on the boundaries of the domain, which is particularly evident when diffusion is low in comparison to the rate of domain growth. Here we present an alternative method which addresses this unphysical buildup of particles at the boundaries and demonstrate that it is accurate for scenarios in which the previous method fails. Further, we discuss for which parameter regimes it is feasible to continue using the original method due to diffusion dominating the domain growth mechanism.

The auxiliary region method: a hybrid method for coupling PDE- and Brownian-based dynamics for reaction-diffusion systems.

Reaction-diffusion systems are used to represent many biological and physical phenomena. They model the random motion of particles (diffusion) and interactions between them (reactions). Such systems can be modelled at multiple scales with varying degrees of accuracy and computational efficiency. When representing genuinely multiscale phenomena, fine-scale models can be prohibitively expensive, whereas coarser models, although cheaper, often lack sufficient detail to accurately represent the phenomenon at hand. Spatial hybrid methods couple two or more of these representations in order to improve efficiency without compromising accuracy. In this paper, we present a novel spatial hybrid method, which we call the auxiliary region method (ARM), which couples PDE- and Brownian-based representations of reaction-diffusion systems. Numerical PDE solutions on one side of an interface are coupled to Brownian-based dynamics on the other side using compartment-based 'auxiliary regions'. We demonstrate that the hybrid method is able to simulate reaction-diffusion dynamics for a number of different test problems with high accuracy. Furthermore, we undertake error analysis on the ARM which demonstrates that it is robust to changes in the free parameters in the model, where previous coupling algorithms are not. In particular, we envisage that the method will be applicable for a wide range of spatial multi-scales problems including filopodial dynamics, intracellular signalling, embryogenesis and travelling wave phenomena.

Spatially extended hybrid methods: a review.

Many biological and physical systems exhibit behaviour at multiple spatial, temporal or population scales. Multiscale processes provide challenges when they are to be simulated using numerical techniques. While coarser methods such as partial differential equations are typically fast to simulate, they lack the individual-level detail that may be required in regions of low concentration or small spatial scale. However, to simulate at such an individual level throughout a domain and in regions where concentrations are high can be computationally expensive. Spatially coupled hybrid methods provide a bridge, allowing for multiple representations of the same species in one spatial domain by partitioning space into distinct modelling subdomains. Over the past 20 years, such hybrid methods have risen to prominence, leading to what is now a very active research area across multiple disciplines including chemistry, physics and mathematics. There are three main motivations for undertaking this review. Firstly, we have collated a large number of spatially extended hybrid methods and presented them in a single coherent document, while comparing and contrasting them, so that anyone who requires a multiscale hybrid method will be able to find the most appropriate one for their need. Secondly, we have provided canonical examples with algorithms and accompanying code, serving to demonstrate how these types of methods work in practice. Finally, we have presented papers that employ these methods on real biological and physical problems, demonstrating their utility. We also consider some open research questions in the area of hybrid method development and the future directions for the field.