Spatiotemporal models and simulations reveal the physical mechanisms that migrating cells sense and self-adapt to heterogeneous extracellular microenvironments

Cell migration plays essential roles in many normal physiological and pathological processes, such as embryonic morphogenesis, wound healing, tissue renewal, nervous system development, cancer metastasis and autoimmune disorders. Both single cell migration and collective cell migration are powered by the actin-based lamellipodia, filopodia or invadopodia protrusions at their leading edges to migrate through extremely heterogeneous extracellular microenvironments. Although extensive experimental studies about cell migration have been conducted, it is unknown of the intracellular physical mechanisms of how migrating cells sense and adapt to the highly varying extracellular mechanical microenvironments. To address this, we construct the predictive spatiotemporal model of the lamellipodial branched actin network through simulating its realistic selfassembling process by encompassing key proteins and their highly dynamic interactions. Then, using finite element simulations, we quantitatively demonstrate the mechanical roles of individual intracellular proteins in regulating the elastic properties of the self-assembling network during cell migration. More importantly, we reveal a resistance-adaptive intracellular physical mechanism of cell migration: the lamellipodial branched actin network can sense the variations of immediate extracellular resistance through the bending deformations of actin filaments, and then adapt to the resistance by self-regulating its elastic properties sensitively through Arp2/3 nucleating, remodelling with F-actin, filamin-A and α-actinin and altering the filament orientations. Such resistance-adaptive behaviours are versatile and essential in driving cells to over-come the highly varying extracellular confinements. Additionally, it is deciphered that the actin filament bending deformation and anisotropic Poisson’s ratio effect of the branched actin network and Arp2/3 branching preference jointly determine why lamellipodium grows into a sheet-like structure and protrudes against resistance persistently. Our predictions Abstract IV are confirmed by published pioneering experiments. The revealed mechanism also can be applied to endocytosis and intracellular pathogens motion. The propulsive force of cell migration is based on actin filament polymerization. We propose a theoretical ‘bending-straightening elastic ratchet’ (BSER) model, which is based on geometrical nonlinearity deformation of continuum solid mechanics. Then, we develop the self-assembling spatiotemporal mathematical model of the polymerizing lamellipodial branched actin filaments propelling the leading edge protrusion under heterogeneous extracellular microenvironment, and perform large-scale spatial and temporal simulations by applying the BSER theoretical model. Our simulation realistically encompasses the stochastic actin filament polymerization, Arp2/3 complex branching, capping proteins inhibiting actin polymerization, curved LE membrane, rupture of molecular linkers and varying extracellular mechanical microenvironment. Strikingly, our model for the first time systematically predicts all important leading-edge behaviours of a migrating cell. More importantly, we reveal two very fundamental biophysical mechanisms that migrating cells sense and adapt their protruding force to varying immediate extracellular physical constraints, and that how migrating cells navigate their migratory path to in highly heterogeneous and complex extracellular microenvironments. Additionally, our BSER theoretical model and the underlying physical mechanism revealed here are also applicable to the propulsion systems of endocytosis, intracellular pathogen transport and dendritic spine formation in cortical neurons, which are powered by polymerization of branched actin filaments as well. Filopodia and invadopodia protrusions are the other two types of cell migration behaviours at their leading edges. Through three-dimensional assembling model of filopodial/invadopodial F-actin bundles and finite element simulations, we quantitatively identify how the highly dynamic assembling and disassembling actin filaments and binding and unbinding of crosslinking proteins, i.e., α-actinin and fascin, regulate Young’s modulus and buckling behaviours of Abstract V filopodia/invadopodia, respectively and combinedly. In addition, thermal induced undulation of actin filaments has an important influence on the buckling behaviours of filopodia/invadopodia. Compared with sheet-like lamellipodia, the finger-like filopodia/invadopodia have a much larger stiffness to protrude in extracellular microenvironment. Thus, they can cooperate with lamellipodia to complementarily split a channel in extracellular microenvironment and drive cell migration through the channel

Unifying Large Language Models and Knowledge Graphs: A Roadmap

Large language models (LLMs), such as ChatGPT and GPT4, are making new waves in the field of natural language processing and artificial intelligence, due to their emergent ability and generalizability. However, LLMs are black-box models, which often fall short of capturing and accessing factual knowledge. In contrast, Knowledge Graphs (KGs), Wikipedia and Huapu for example, are structured knowledge models that explicitly store rich factual knowledge. KGs can enhance LLMs by providing external knowledge for inference and interpretability. Meanwhile, KGs are difficult to construct and evolving by nature, which challenges the existing methods in KGs to generate new facts and represent unseen knowledge. Therefore, it is complementary to unify LLMs and KGs together and simultaneously leverage their advantages. In this article, we present a forward-looking roadmap for the unification of LLMs and KGs. Our roadmap consists of three general frameworks, namely, 1) KG-enhanced LLMs, which incorporate KGs during the pre-training and inference phases of LLMs, or for the purpose of enhancing understanding of the knowledge learned by LLMs; 2) LLM-augmented KGs, that leverage LLMs for different KG tasks such as embedding, completion, construction, graph-to-text generation, and question answering; and 3) Synergized LLMs + KGs, in which LLMs and KGs play equal roles and work in a mutually beneficial way to enhance both LLMs and KGs for bidirectional reasoning driven by both data and knowledge. We review and summarize existing efforts within these three frameworks in our roadmap and pinpoint their future research directions.Comment: 29 pages, 25 figure

A Strategy for Prompt Phase Transfer of Upconverting Nanoparticles Through Surface Oleate-Mediated Supramolecular Assembly of Amino-β-Cyclodextrin

Lanthanide-doped upconverting nanoparticles (UCNPs) are promising for applications as wide as biosensing, bioimaging, controlled drug release, and cancer therapy. These applications require surface engineering of as-prepared nanocrystals, commonly coated with hydrophobic ligand of oleic acid, to enable an aqueous dispersion. However, literature-reported approaches often require a long time and/or multiple step treatment, along with several fold upconversion luminescence (UCL) intensity decrease. Here, we describe a strategy allowing oleate-capped UCNPs to become water-soluble and open-modified, with almost undiminished UCL, through ultrasonication of minutes. The prompt phase transfer was enabled by oleate-mediated supramolecular self-assembly of amino modified β-cyclodextrin (amino-β-CD) onto UCNPs surface. We showed that this method is valid for a wide range of UCNPs with quite different sizes (6–400 nm), various dopant types (Er, Tm, and Ho), and hierarchical structures (core, core-shell). Importantly, the amino group of amino-β-CD on the surface of treated UCNPs provide possibilities to introduce entities for biotargeting or functionalization, as exemplified here, a carboxylic-containing near infrared dye (Cy 7.5) that sensitizes UCNPs to enhance their UCL by ~4,820 fold when excited at ~808 nm. The described method has implications for all types of oleate-capped inorganic nanocrystals, facilitating their myriad bioapplications

Fourth order transport model on Yin-Yang grid by multi-moment constrained finite volume scheme

AbstractA fourth order transport model is proposed for global computation with the application of multi-moment constrained finite volume (MCV) scheme and Yin-Yang overset grid. Using multi-moment concept, local degrees of freedom (DOFs) are point-wisely defined within each mesh element to build a cubic spatial reconstruction. The updating formulations for local DOFs are derived by adopting multi moments as constraint conditions, including volume-integrated average (VIA), point value (PV) and first order derivative value (DV). Using Yin-Yang grid eliminates the polar singularities and results in a quasi-uniform mesh over the whole globe. Each component of Yin-Yang grid is a part of the LAT-LON grid, an orthogonal structured grid, where the MCV formulations designed for Cartesian grid can be applied straightforwardly to develop the high order numerical schemes. Proposed MCV model is checked by widely used benchmark tests. The numerical results show that the present model has fourth order accuracy and is competitive to most existing ones

Force and deformation characteristics during the reconstruction and expansion of shallow single-tube tunnels into large-span multiarch tunnels

At present, there are an ever-increasing number of tunnel expansion projects in China. Studying the mechanical properties of the expanded tunnels is of great significance for guiding their safe construction. Through model testing and numerical simulation, the mechanical properties of a double-arch tunnel constructed through the expansion of the middle pilot heading from an existing single-tube tunnel were studied. The variation characteristics of the surface subsidence, surrounding rock stress, and stress and strain of the middle partition wall and lining during the tunnel reconstruction and expansion were investigated. The mechanism for transferring stress and strain between the left and right tunnel tubes was studied by a numerical simulation method. The results showed that the surface subsidence caused by the excavation of the left (i.e., the subsequent) tunnel tube was larger, and the maximum surface subsidence occurred at the right (i.e., the first) tunnel tube. The surrounding rock on the middle wall was the sensitive part of the tunnel excavation, the stress of the surrounding rock at the left spandrel of the right tunnel tube fluctuated and exhibited the most complex variation, and the stress of the surrounding rock at the right spandrel of the left tunnel tube exhibited the largest variation. The excavation of the left tunnel tube had a great influence on the forces of the middle partition wall and the lining structure of the right tunnel tube, the middle partition wall was subjected to eccentric compression towards the left tunnel tube, and the stress at the left spandrel under the initial support of the right tunnel tube exhibited complex variations. The excavation of the left and right tunnel tubes had a great influence on the stability of the surrounding rock, as well as on the force-induced deformation of the middle partition wall and the support structure, within the width of the single tunnel tube span behind the tunnel working face. Due to the different construction sequences, the stress and strain at the symmetric measurement points of the middle partition wall, as well as the left and right tunnel support structures, were very different

Predictive assembling model reveals the self-adaptive elastic properties of lamellipodial actin networks for cell migration

Branched actin network supports cell migration through extracellular microenvironments. However, it is unknown how intracellular proteins adapt the elastic properties of the network to the highly varying extracellular resistance. Here we develop a three-dimensional assembling model to simulate the realistic self-assembling process of the network by encompassing intracellular proteins and their dynamic interactions. Combining this multiscale model with finite element method, we reveal that the network can not only sense the variation of extracellular resistance but also self-adapt its elastic properties through remodeling with intracellular proteins. Such resistance-adaptive elastic behaviours are versatile and essential in supporting cell migration through varying extracellular microenvironments. The bending deformation mechanism and anisotropic Poisson’s ratios determine why lamellipodia persistently evolve into sheet-like structures. Our predictions are confirmed by published experiments. The revealed self-adaptive elastic properties of the networks are also applicable to the endocytosis, phagocytosis, vesicle trafficking, intracellular pathogen transport and dendritic spine formation