Eulerian simulation of complex suspensions and biolocomotion in three dimensions.

We present a numerical method specifically designed for simulating three-dimensional fluid-structure interaction (FSI) problems based on the reference map technique (RMT). The RMT is a fully Eulerian FSI numerical method that allows fluids and large-deformation elastic solids to be represented on a single fixed computational grid. This eliminates the need for meshing complex geometries typical in other FSI approaches and greatly simplifies the coupling between fluid and solids. We develop a three-dimensional implementation of the RMT, parallelized using the distributed memory paradigm, to simulate incompressible FSI with neo-Hookean solids. As part of our method, we develop a field extrapolation scheme that works efficiently in parallel. Through representative examples, we demonstrate the method's suitability in investigating many-body and active systems, as well as its accuracy and convergence. The examples include settling of a mixture of heavy and buoyant soft ellipsoids, lid-driven cavity flow containing a soft sphere, and swimmers actuated via active stress.

A simple developmental model recapitulates complex insect wing venation patterns.

Insect wings are typically supported by thickened struts called veins. These veins form diverse geometric patterns across insects. For many insect species, even the left and right wings from the same individual have veins with unique topological arrangements, and little is known about how these patterns form. We present a large-scale quantitative study of the fingerprint-like "secondary veins." We compile a dataset of wings from 232 species and 17 families from the order Odonata (dragonflies and damselflies), a group with particularly elaborate vein patterns. We characterize the geometric arrangements of veins and develop a simple model of secondary vein patterning. We show that our model is capable of recapitulating the vein geometries of species from other, distantly related winged insect clades.

Flow-Driven Branching in a Frangible Porous Medium.

Channel formation and branching is widely seen in physical systems where movement of fluid through a porous structure causes the spatiotemporal evolution of the medium. We provide a simple theoretical framework that embodies this feedback mechanism in a multiphase model for flow through a frangible porous medium with a dynamic permeability. Numerical simulations of the model show the emergence of branched networks whose topology is determined by the geometry of external flow forcing. This allows us to delineate the conditions under which splitting and/or coalescing branched network formation is favored, with potential implications for both understanding and controlling branching in soft frangible media.

Differential Activity-Driven Instabilities in Biphasic Active Matter.

Active stresses can cause instabilities in contractile gels and living tissues. Here we provide a generic hydrodynamic theory that treats these systems as a mixture of two phases of varying activity and different mechanical properties. We find that differential activity between the phases causes a uniform mixture to undergo a demixing instability. We follow the nonlinear evolution of the instability and characterize a phase diagram of the resulting patterns. Our study complements other instability mechanisms in mixtures driven by differential adhesion, differential diffusion, differential growth, and differential motion.

Transcriptome-Wide Cleavage Site Mapping on Cellular mRNAs Reveals Features Underlying Sequence-Specific Cleavage by the Viral Ribonuclease SOX.

Many viruses express factors that reduce host gene expression through widespread degradation of cellular mRNA. An example of this class of proteins is the mRNA-targeting endoribonuclease SOX from the gamma-herpesvirus Kaposi's sarcoma-associated herpesvirus (KSHV). Previous studies indicated that cleavage of messenger RNAs (mRNA) by SOX occurs at specific locations defined by the sequence of the target RNA, which is at odds with the down-regulation of a large portion of cellular transcripts. In this study, we address this paradox by using high-throughput sequencing of cleavage intermediates combined with a custom bioinformatics-based analysis pipeline to identify SOX cleavage sites across the mRNA transcriptome. These data, coupled with targeted mutagenesis, reveal that while cleavage sites are specific and reproducible, they are defined by a degenerate sequence motif containing a small number of conserved residues rather than a strong consensus sequence. This degenerate element is well represented in both human and KSHV mRNA, and its presence correlates with RNA destabilization by SOX. This represents a new endonuclease targeting strategy, in which use of a degenerate targeting element enables RNA cleavage at specific locations without restricting the range of targets. Furthermore, it shows that strong target selectivity can be achieved without a high degree of sequence specificity.

Rapid disorganization of mechanically interacting systems of mammary acini.

Cells and multicellular structures can mechanically align and concentrate fibers in their ECM environment and can sense and respond to mechanical cues by differentiating, branching, or disorganizing. Here we show that mammary acini with compromised structural integrity can interconnect by forming long collagen lines. These collagen lines then coordinate and accelerate transition to an invasive phenotype. Interacting acini begin to disorganize within 12.5 ± 4.7 h in a spatially coordinated manner, whereas acini that do not interact mechanically with other acini disorganize more slowly (in 21.8 ± 4.1 h) and to a lesser extent (P < 0.0001). When the directed mechanical connections between acini were cut with a laser, the acini reverted to a slowly disorganizing phenotype. When acini were fully mechanically isolated from other acini and also from the bulk gel by box-cuts with a side length <900 µm, transition to an invasive phenotype was blocked in 20 of 20 experiments, regardless of waiting time. Thus, pairs or groups of mammary acini can interact mechanically over long distances through the collagen matrix, and these directed mechanical interactions facilitate transition to an invasive phenotype.

A mathematical model of fluid and gas flow in nanoporous media.

The mathematical modeling of the flow in nanoporous rocks (e.g., shales) becomes an important new branch of subterranean fluid mechanics. The classic approach that was successfully used in the construction of the technology to develop oil and gas deposits in the United States, Canada, and the Union of Soviet Socialist Republics becomes insufficient for deposits in shales. In the present article a mathematical model of the flow in nanoporous rocks is proposed. The model assumes the rock consists of two components: (i) a matrix, which is more or less an ordinary porous or fissurized-porous medium, and (ii) specific organic inclusions composed of kerogen. These inclusions may have substantial porosity but, due to the nanoscale of pores, tubes, and channels, have extremely low permeability on the order of a nanodarcy (~109-²¹ m² ) or less. These inclusions contain the majority of fluid: oil and gas. Our model is based on the hypothesis that the permeability of the inclusions substantially depends on the pressure gradient. At the beginning of the development of the deposit, boundary layers are formed at the boundaries of the low-permeable inclusions, where the permeability is strongly increased and intensive flow from inclusions to the matrix occurs. The resulting formulae for the production rate of the deposit are presented in explicit form. The formulae demonstrate that the production rate of deposits decays with time following a power law whose exponent lies between -1/2 and -1. Processing of experimental data obtained from various oil and gas deposits in shales demonstrated an instructive agreement with the prediction of the model.

Bendability parameter for twisted ribbons to describe longitudinal wrinkling and delineate the near-threshold regime.

We propose a dimensionless bendability parameter, ε^{-1}=[(h/W)^{2}T^{-1}]^{-1}, for wrinkling of thin, twisted ribbons with thickness h, width W, and tensional strain T. Bendability permits efficient collapse of data for wrinkle onset, wavelength, critical stress, and residual stress, demonstrating longitudinal wrinkling's primary dependence on this parameter. This parameter also allows us to distinguish the highly bendable range (ε^{-1}>20) from moderately bendable samples (ε^{-1}∈(0,20]). We identify scaling relations to describe longitudinal wrinkles that are valid across our entire set of simulated ribbons. When restricted to the highly bendable regime, simulations confirm theoretical near-threshold (NT) predictions for wrinkle onset and wavelength.

How microscopic epistasis and clonal interference shape the fitness trajectory in a spin glass model of microbial long-term evolution.

The adaptive dynamics of evolving microbial populations takes place on a complex fitness landscape generated by epistatic interactions. The population generically consists of multiple competing strains, a phenomenon known as clonal interference. Microscopic epistasis and clonal interference are central aspects of evolution in microbes, but their combined effects on the functional form of the population's mean fitness are poorly understood. Here, we develop a computational method that resolves the full microscopic complexity of a simulated evolving population subject to a standard serial dilution protocol. Through extensive numerical experimentation, we find that stronger microscopic epistasis gives rise to fitness trajectories with slower growth independent of the number of competing strains, which we quantify with power-law fits and understand mechanistically via a random walk model that neglects dynamical correlations between genes. We show that increasing the level of clonal interference leads to fitness trajectories with faster growth (in functional form) without microscopic epistasis, but leaves the rate of growth invariant when epistasis is sufficiently strong, indicating that the role of clonal interference depends intimately on the underlying fitness landscape. The simulation package for this work may be found at https://github.com/nmboffi/spin_glass_evodyn.

In silico screening of carbon-capture materials.

One of the main bottlenecks to deploying large-scale carbon dioxide capture and storage (CCS) in power plants is the energy required to separate the CO(2) from flue gas. For example, near-term CCS technology applied to coal-fired power plants is projected to reduce the net output of the plant by some 30% and to increase the cost of electricity by 60-80%. Developing capture materials and processes that reduce the parasitic energy imposed by CCS is therefore an important area of research. We have developed a computational approach to rank adsorbents for their performance in CCS. Using this analysis, we have screened hundreds of thousands of zeolite and zeolitic imidazolate framework structures and identified many different structures that have the potential to reduce the parasitic energy of CCS by 30-40% compared with near-term technologies.

Computational model of twisted elastic ribbons.

We develop an irregular lattice mass-spring model to simulate and study the deformation modes of a thin elastic ribbon as a function of applied end-to-end twist and tension. Our simulations reproduce all reported experimentally observed modes, including transitions from helicoids to longitudinal wrinkles, creased helicoids and loops with self-contact, and transverse wrinkles to accordion self-folds. Our simulations also show that the twist angles at which the primary longitudinal and transverse wrinkles appear are well described by various analyses of the Föppl-von Kármán equations, but the characteristic wavelength of the longitudinal wrinkles has a more complex relationship to applied tension than previously estimated. The clamped edges are shown to suppress longitudinal wrinkling over a distance set by the applied tension and the ribbon width, but otherwise have no apparent effect on measured wavelength. Further, by analyzing the stress profile, we find that longitudinal wrinkling does not completely alleviate compression, but caps the magnitude of the compression. Nonetheless, the width over which wrinkles form is observed to be wider than the near-threshold analysis predictions: the width is more consistent with the predictions of far-from-threshold analysis. However, the end-to-end contraction of the ribbon as a function of twist is found to more closely follow the corresponding near-threshold prediction as tension in the ribbon is increased, in contrast to the expectations of far-from-threshold analysis. These results point to the need for further theoretical analysis of this rich thin elastic system, guided by our physically robust and intuitive simulation model.

Cut site preference allows influenza A virus PA-X to discriminate between host and viral mRNAs.

Many viruses block host gene expression to take over the infected cell. This process, termed host shutoff, is thought to promote viral replication by preventing antiviral responses and redirecting cellular resources to viral processes. Several viruses from divergent families accomplish host shutoff through RNA degradation by endoribonucleases. However, viruses also need to ensure expression of their own genes. The influenza A virus endoribonuclease PA-X solves this problem by sparing viral mRNAs and some host RNAs necessary for viral replication. To understand how PA-X distinguishes between RNAs, we characterized PA-X cut sites transcriptome-wide using 5' rapid amplification of complementary DNA ends coupled to high-throughput sequencing. This analysis, along with RNA structure predictions and validation experiments using reporters, shows that PA-Xs from multiple influenza strains preferentially cleave RNAs at GCUG tetramers in hairpin loops. Importantly, GCUG tetramers are enriched in the human but not the influenza transcriptome. Moreover, optimal PA-X cut sites inserted in the influenza A virus genome are quickly selected against during viral replication in cells. This finding suggests that PA-X evolved these cleavage characteristics to preferentially target host over viral mRNAs in a manner reminiscent of cellular self versus non-self discrimination.

A subcellular biochemical model for T6SS dynamics reveals winning competitive strategies.

The type VI secretion system (T6SS) is a broadly distributed interbacterial weapon that can be used to eliminate competing bacterial populations. Although unarmed target populations are typically used to study T6SS function in vitro, bacteria most likely encounter other T6SS-armed competitors in nature. However, the connection between subcellular details of the T6SS and the outcomes of such mutually lethal battles is not well understood. Here, we incorporate biological data derived from natural competitors of Vibrio fischeri light organ symbionts to build a biochemical model for T6SS at the single-cell level, which we then integrate into an agent-based model (ABM). Using the ABM, we isolate and experiment with strain-specific physiological differences between competitors in ways not possible with biological samples to identify winning strategies for T6SS-armed populations. Through in vitro experiments, we discover that strain-specific differences exist in T6SS activation speed. ABM simulations corroborate that faster activation is dominant in determining survival during competition. Once competitors are fully activated, the energy required for T6SS creates a tipping point where increased weapon building and firing becomes too costly to be advantageous. Through ABM simulations, we identify the threshold where this transition occurs in the T6SS parameter space. We also find that competitive outcomes depend on the geometry of the battlefield: unarmed target cells survive at the edges of a range expansion where unlimited territory can be claimed. Alternatively, competitions within a confined space, much like the light organ crypts where natural V. fischeri compete, result in the rapid elimination of the unarmed population.

Fracture toughness of metallic glasses: annealing-induced embrittlement.

Quantitative understanding of the fracture toughness of metallic glasses, including the associated ductile-to-brittle (embrittlement) transitions, is not yet available. Here, we use a simple model of plastic deformation in glasses, coupled to an advanced Eulerian level set formulation for solving complex free-boundary problems, to calculate the fracture toughness of metallic glasses as a function of the degree of structural relaxation corresponding to different annealing times near the glass temperature. Our main result indicates the existence of an elastoplastic crack tip instability for sufficiently relaxed glasses, resulting in a marked drop in the toughness, which we interpret as annealing-induced embrittlement transition similar to experimental observations.

Nuclear speed and cycle length co-vary with local density during syncytial blastoderm formation in a cricket.

The blastoderm is a broadly conserved stage of early animal development, wherein cells form a layer at the embryo's periphery. The cellular behaviors underlying blastoderm formation are varied and poorly understood. In most insects, the pre-blastoderm embryo is a syncytium: nuclei divide and move throughout the shared cytoplasm, ultimately reaching the cortex. In Drosophila melanogaster, some early nuclear movements result from pulsed cytoplasmic flows that are coupled to synchronous divisions. Here, we show that the cricket Gryllus bimaculatus has a different solution to the problem of creating a blastoderm. We quantified nuclear dynamics during blastoderm formation in G. bimaculatus embryos, finding that: (1) cytoplasmic flows are unimportant for nuclear movement, and (2) division cycles, nuclear speeds, and the directions of nuclear movement are not synchronized, instead being heterogeneous in space and time. Moreover, nuclear divisions and movements co-vary with local nuclear density. We show that several previously proposed models for nuclear movements in D. melanogaster cannot explain the dynamics of G. bimaculatus nuclei. We introduce a geometric model based on asymmetric pulling forces on nuclei, which recapitulates the patterns of nuclear speeds and orientations of both unperturbed G. bimaculatus embryos, and of embryos physically manipulated to have atypical nuclear densities.

Inverse Design of Mechanical Metamaterials with Target Nonlinear Response via a Neural Accelerated Evolution Strategy.

Materials with target nonlinear mechanical response can support the design of innovative soft robots, wearable devices, footwear, and energy-absorbing systems, yet it is challenging to realize them. Here, mechanical metamaterials based on hinged quadrilaterals are used as a platform to realize target nonlinear mechanical responses. It is first shown that by changing the shape of the quadrilaterals, the amount of internal rotations induced by the applied compression can be tuned, and a wide range of mechanical responses is achieved. Next, a neural network is introduced that provides a computationally inexpensive relationship between the parameters describing the geometry and the corresponding stress-strain response. Finally, it is shown that by combining the neural network with an evolution strategy, one can efficiently identify geometries resulting in a wide range of target nonlinear mechanical responses and design optimized energy-absorbing systems, soft robots, and morphing structures.

Machine-Learning Spectral Indicators of Topology.

Topological materials discovery has emerged as an important frontier in condensed matter physics. While theoretical classification frameworks have been used to identify thousands of candidate topological materials, experimental determination of materials' topology often poses significant technical challenges. X-ray absorption spectroscopy (XAS) is a widely used materials characterization technique sensitive to atoms' local symmetry and chemical bonding, which are intimately linked to band topology by the theory of topological quantum chemistry (TQC). Moreover, as a local structural probe, XAS is known to have high quantitative agreement between experiment and calculation, suggesting that insights from computational spectra can effectively inform experiments. In this work, computed X-ray absorption near-edge structure (XANES) spectra of more than 10 000 inorganic materials to train a neural network (NN) classifier that predicts topological class directly from XANES signatures, achieving F1 scores of 89% and 93% for topological and trivial classes, respectively is leveraged. Given the simplicity of the XAS setup and its compatibility with multimodal sample environments, the proposed machine-learning-augmented XAS topological indicator has the potential to discover broader categories of topological materials, such as non-cleavable compounds and amorphous materials, and may further inform field-driven phenomena in situ, such as magnetic field-driven topological phase transitions.

A model for the fragmentation kinetics of crumpled thin sheets.

As a confined thin sheet crumples, it spontaneously segments into flat facets delimited by a network of ridges. Despite the apparent disorder of this process, statistical properties of crumpled sheets exhibit striking reproducibility. Experiments have shown that the total crease length accrues logarithmically when repeatedly compacting and unfolding a sheet of paper. Here, we offer insight to this unexpected result by exploring the correspondence between crumpling and fragmentation processes. We identify a physical model for the evolution of facet area and ridge length distributions of crumpled sheets, and propose a mechanism for re-fragmentation driven by geometric frustration. This mechanism establishes a feedback loop in which the facet size distribution informs the subsequent rate of fragmentation under repeated confinement, thereby producing a new size distribution. We then demonstrate the capacity of this model to reproduce the characteristic logarithmic scaling of total crease length, thereby supplying a missing physical basis for the observed phenomenon.

Coordinate transformation methodology for simulating quasistatic elastoplastic solids.

Molecular dynamics simulations frequently employ periodic boundary conditions where the positions of the periodic images are manipulated in order to apply deformation to the material sample. For example, Lees-Edwards conditions use moving periodic images to apply simple shear. Here, we examine the problem of precisely comparing this type of simulation to continuum solid mechanics. We employ a hypoelastoplastic mechanical model, and develop a projection method to enforce quasistatic equilibrium. We introduce a simulation framework that uses a fixed Cartesian computational grid on a reference domain, and which imposes deformation via a time-dependent coordinate transformation to the physical domain. As a test case for our method, we consider the evolution of shear bands in a bulk metallic glass using the shear transformation zone theory of amorphous plasticity. We examine the growth of shear bands in simple shear and pure shear conditions as a function of the initial preparation of the bulk metallic glass.

Area-Preserving Mapping of 3D Carotid Ultrasound Images Using Density-Equalizing Reference Map.

Atherosclerotic plaques are focal and tend to occur at arterial bends and bifurcations. To quantitatively monitor the local changes in the carotid vessel-wall-plus-plaque thickness (VWT) and compare the VWT distributions for different patients or for the same patients at different ultrasound scanning sessions, a mapping technique is required to adjust for the geometric variability of different carotid artery models. In this work, we propose a novel method called density-equalizing reference map (DERM) for mapping 3D carotid surfaces to a standardized 2D carotid template, with an emphasis on preserving the local geometry of the carotid surface by minimizing the local area distortion. The initial map was generated by a previously described arc-length scaling (ALS) mapping method, which projects a 3D carotid surface onto a 2D non-convex L-shaped domain. A smooth and area-preserving flattened map was subsequently constructed by deforming the ALS map using the proposed algorithm that combines the density-equalizing map and the reference map techniques. This combination allows, for the first time, one-to-one mapping from a 3D surface to a standardized non-convex planar domain in an area-preserving manner. Evaluations using 20 carotid surface models show that the proposed method reduced the area distortion of the flattening maps by over 80% as compared to the ALS mapping method. The proposed method is capable of improving the accuracy of area estimation for plaque regions without compromising inter-scan reproducibility.