Response of Single Cells to Shock Waves and Numerically Optimized Waveforms for Cancer Therapy

Shock waves are used clinically for breaking kidney stones and treating musculoskeletal indications. The mechanisms by which shock waves interact with tissue are still not well understood. Here, ultra-high-speed imaging was used to visualize the deformation of individual cells embedded in a tissue-mimicking phantom when subject to shock-wave exposure from a clinical source. Three kidney epithelial cell lines were considered to represent normal healthy (human renal epithelial), cancer (CAKI-2), and virus-transformed (HK-2) cells. The experimental results showed that during the compressive phase of the shock waves, there was a small ($<$2%) decrease in the projected cell area, but during the tensile phase, there was a relatively large (～10%) increase in the projected cell area. The experimental observations were captured by a numerical model with a constitutive material framework consisting of an equation of state for the volumetric response and hyper-viscoelasticity for the deviatoric response. To model the volumetric cell response, it was necessary to change from a higher bulk modulus during the compression to a lower bulk modulus during the tensile shock loading. It was discovered that cancer cells showed a smaller deformation but faster response to the shock-wave tensile phase compared to their noncancerous counterparts. Cell viability experiments, however, showed that cancer cells suffered more damage than other cell types. These data suggest that the cell response to shock waves is specific to the type of cell and waveforms that could be tailored to an application. For example, the model predicts that a shock wave with a tensile stress of 4.59 MPa would increase cell membrane permeability for cancer cells with minimal impact on normal cells.     

Steady-State Differential Dose Response in Biological Systems

In pharmacology and systems biology, it is a fundamental problem to determine how biological systems change their dose-response behavior upon perturbations. In particular, it is unclear how topologies, reactions, and parameters (differentially) affect the dose response. Because parameters are often unknown, systematic approaches should directly relate network structure and function. Here, we outline a procedure to compare general non-monotone dose-response curves and subsequently develop a comprehensive theory for differential dose responses of biochemical networks captured by non-equilibrium steady-state linear framework models. Although these models are amenable to analytical derivations of non-equilibrium steady states in principle, their size frequently increases (super) exponentially with model size. We extract general principles of differential responses based on a model’s graph structure and thereby alleviate the combinatorial explosion. This allows us, for example, to determine reactions that affect differential responses, to identify classes of networks with equivalent differential, and to reject hypothetical models reliably without needing to know parameter values. We exemplify such applications for models of insulin signaling.     

Sharing of Phosphatases Promotes Response Plasticity in Phosphorylation Cascades

Sharing of positive or negative regulators between multiple targets is frequently observed in cellular signaling cascades. For instance, phosphatase sharing between multiple kinases is ubiquitous within the MAPK pathway. Here we investigate how such phosphatase sharing could shape robustness and evolvability of the phosphorylation cascade. Through modeling and evolutionary simulations, we demonstrate that 1) phosphatase sharing dramatically increases robustness of a bistable MAPK response, and 2) phosphatase-sharing cascades evolve faster than nonsharing cascades. This faster evolution is particularly pronounced when evolving from a monostable toward a bistable phenotype, whereas the transition speed of a population from a bistable to monostable response is not affected by phosphatase sharing. This property may enable the phosphatase-sharing design to adapt better in a changing environment. Analysis of the respective mutational landscapes reveal that phosphatase sharing reduces the number of limiting mutations required for transition from monostable to bistable responses, hence facilitating a faster transition to such response types. Taken together, using MAPK cascade as an example, our study offers a general theoretical framework to explore robustness and evolutionary plasticity of signal transduction cascades.     

CD38-NAD+Axis Regulates Immunotherapeutic Anti-Tumor T Cell Response

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How to Connect Cardiac Excitation to the Atomic Interactions of Ion Channels

Many have worked to create cardiac action potential models that explicitly represent atomic-level details of ion channel structure. Such models have the potential to define new therapeutic directions and to show how nanoscale perturbations to channel function predispose patients to deadly cardiac arrhythmia. However, there have been significant experimental and theoretical barriers that have limited model usefulness. Recently, many of these barriers have come down, suggesting that considerable progress toward creating these long-sought models may be possible in the near term.