Sensors are the first element of the pathways that control the response of cells to their environment. Protein complexes that produce or enable a chemical signal in response to a mechanical stimulus are called "mechanosensors". In this work, we develop a theoretical model describing the physical mechanism of a reversible single-molecule stiffness sensor. Although this has the potential for general application, here we apply the model to focal adhesion kinase, which initiates the chemical signal in its active phosphorylated conformation, but can spontaneously return to its closed folded conformation. We find how the rates of conformation changes depend on the substrate stiffness and the pulling force applied from the cell cytoskeleton. We find the sensor is homeostatic, spontaneously self-adjusting to reach a state where its range of maximum sensitivity matches the substrate stiffness. The results compare well with the phenotype observations of cells on different substrates.

Experiments have shown that self-propelled particles can slide along the surface of a circular obstacle without becoming trapped over long times. Using simulations and theory, we study the impact of boundary conditions on the diffusive transport of active particles in an obstacle lattice. We find that particle dynamics with sliding boundary conditions result in large diffusivities even at high obstacle density, unlike classical specular reflection. These dynamics are very well described by a model based on Run-and-Tumble particles with microscopically derived reorientation functions arising from obstacle-induced tumbles. This model, however, fails to describe fine structure in the diffusivity at high obstacle density predicted by simulations. Using a simple deterministic model, we show that this structure results from particles being guided by the lattice. Our results thus show how non-classical surface scattering introduces a dependence on the lattice geometry at high densities. We discuss implications for the study of bacteria in complex environments.

While anti-VEGF drugs are commonly used to inhibit pathological retinal and choroidal neovascularization, not all patients respond in an optimal manner. Mechanisms underpinning resistance to anti‑VEGF therapy include the upregulation of other proangiogenic factors. Therefore, therapeutic strategies that simultaneously target multiple growth factor signaling pathways would have significant value. Here, we show that Ca 2+ /calmodulin-dependent kinase II (CAMKII) mediates the angiogenic actions of a range of growth factors in human retinal endothelial cells and that this kinase acts as a key nodal point for the activation of several signal transduction cascades that are known to play a critical role in growth factor–induced angiogenesis. We also demonstrate that endothelial CAMKIIγ and -δ isoforms differentially regulate the angiogenic effects of different growth factors and that genetic deletion of these isoforms suppresses pathological retinal and choroidal neovascularization in vivo. Our studies suggest that CAMKII could provide a novel and efficacious target to inhibit multiple angiogenic signaling pathways for the treatment of vasoproliferative diseases of the eye. CAMKIIγ represents a particularly promising target, as deletion of this isoform inhibited pathological neovascularization, while enhancing reparative angiogenesis in the ischemic retina.

The rate of binding of a grafted polymer to the surface is controlled by entropic barriers. Using a mean-field approximation of ideal polymer dynamics, we first calculate the characteristic binding time for a tethered ligand reaching for a binding site located on the tethering surface. This time is determined by two separate entropic effects: a barrier for the chain to be stretched sufficiently to reach the distant target and a restriction on chain conformations near the surface, versus the increase in available phase space for longer chains. The competition between these two constraints determines the optimal (shortest) binding time. The theory is then extended to model bridging between two surfaces, in particular relevant for cell adhesion. Here the tethered ligand reaches for a receptor on a parallel surface, and the binding time depends on the gap between the two constraining surfaces. Again, an optimal binding time is determined for the given tether geometry. The results look similar to those for free particles in the "narrow escape problem", but modified by an entropic activation factor introduced by the tether.

Adapting to the environment statistics by reducing brain responses to repetitive sensory information is key for efficient information processing. Yet, the fine-scale computations that support this adaptive processing in the human brain remain largely unknown. Here, we capitalise on the sub-millimetre resolution of ultra-high field imaging to examine functional magnetic resonance imaging signals across cortical depth and discern competing hypotheses about the brain mechanisms (feedforward vs. feedback) that mediate adaptive processing. We demonstrate layer-specific suppressive processing within visual cortex, as indicated by stronger BOLD decrease in superficial and middle than deeper layers for gratings that were repeatedly presented at the same orientation. Further, we show altered functional connectivity for adaptation: enhanced feedforward connectivity from V1 to higher visual areas, short-range feedback connectivity between V1 and V2, and long-range feedback occipito-parietal connectivity. Our findings provide evidence for a circuit of local recurrent and feedback interactions that mediate rapid brain plasticity for adaptive information processing.