Sub-micron surface plasmon resonance sensor systems

A sensor for detecting the presence of a target analyte, ligand or molecule in a test fluid, comprising a light transmissive substrate on which an array of surface plasmon resonant (SPR) elements is mounted is described. A multi-channel sensor for detecting the presence of several targets with a single micro-chip sensor is described. A multi-channel sensor including collections of SPR elements which are commonly functionalized to one of several targets is also described. The detectors sense changes in the resonant response of the SPR elements indicative of binding with the targets

Sub-micron surface plasmon resonance sensor systems

A sensor for detecting the presence of a target analyte, ligand or molecule in a test fluid, comprising a light transmissive substrate on which an array of surface plasmon resonant (SPR) elements is mounted is described. A multi-channel sensor for detecting the presence of several targets with a single micro-chip sensor is described. A multi-channel sensor including collections of SPR elements which are commonly functionalized to one of several targets is also described. The detectors sense changes in the resonant response of the SPR elements indicative of binding with the targets

Bulk elastic properties of chicken embryos during somitogenesis

We present measurements of the bulk Young's moduli of early chick embryos at Hamburger-Hamilton stage 10. Using a micropipette probe with a force constant k ~0.025 N/m, we applied a known force in the plane of the embryo in the anterior-posterior direction and imaged the resulting tissue displacements. We used a two-dimensional finite-element simulation method to model the embryo as four concentric elliptical elastic regions with dimensions matching the embryo's morphology. By correlating the measured tissue displacements to the displacements calculated from the in-plane force and the model, we obtained the approximate short time linear-elastic Young's moduli: 2.4 ± 0.1 kPa for the midline structures (notocord, neural tube, and somites), 1.3 ± 0.1 kPa for the intermediate nearly acellular region between the somites and area pellucida, 2.1 ± 0.1 kPa for the area pellucida, and 11.9 ± 0.8 kPa for the area opaca

Viscous instabilities in flowing foams: A Cellular Potts Model approach

The Cellular Potts Model (CPM) succesfully simulates drainage and shear in foams. Here we use the CPM to investigate instabilities due to the flow of a single large bubble in a dry, monodisperse two-dimensional flowing foam. As in experiments in a Hele-Shaw cell, above a threshold velocity the large bubble moves faster than the mean flow. Our simulations reproduce analytical and experimental predictions for the velocity threshold and the relative velocity of the large bubble, demonstrating the utility of the CPM in foam rheology studies.Comment: 10 pages, 3 figures. Replaced with revised version accepted for publication in JSTA

Experimental growth law for bubbles in a "wet" 3D liquid foam

We used X-ray tomography to characterize the geometry of all bubbles in a liquid foam of average liquid fraction $\phi_l\approx 17$ and to follow their evolution, measuring the normalized growth rate $\mathcal{G}=V^{-{1/3}}\frac{dV} {dt}$ for 7000 bubbles. While $\mathcal{G}$ does not depend only on the number of faces of a bubble, its average over $f-$faced bubbles scales as $G_f\sim f-f_0$ for large $f$s at all times. We discuss the dispersion of $\mathcal{G}$ and the influence of $V$ on $\mathcal{G}$.Comment: 10 pages, submitted to PR

Multiscale Modeling of Spheroid Tumors: Effect of Nutrient Availability on Tumor Evolution

Recent years have revealed a large number of complex mechanisms and interactions that drive the development of malignant tumors. Tumor evolution is a framework that explains tumor development as a process driven by survival of the fittest, with tumor cells of different properties competing for limited available resources. To predict the evolutionary trajectory of a tumor, knowledge of how cellular properties influence the fitness of a subpopulation in the context of the microenvironment is required and is often inaccessible. Computational multiscale-modeling of tissues enables the observation of the full trajectory of each cell within the tumor environment. Here, we model a 3D spheroid tumor with subcellular resolution. The fitness of individual cells and the evolutionary behavior of the tumor are quantified and linked to cellular and environmental parameters. The fitness of cells is solely influenced by their position in the tumor, which in turn is influenced by the two variable parameters of our model: cell–cell adhesion and cell motility. We observe the influence of nutrient independence and static and dynamically changing nutrient availability on the evolutionary trajectories of heterogeneous tumors in a high-resolution computational model. Regardless of nutrient availability, we find a fitness advantage of low-adhesion cells, which are favorable for tumor invasion. We find that the introduction of nutrient-dependent cell division and death accelerates the evolutionary speed. The evolutionary speed can be increased by fluctuations in nutrients. We identify a distinct frequency domain in which the evolutionary speed increases significantly over a tumor with constant nutrient supply. The findings suggest that an unstable supply of nutrients can accelerate tumor evolution and, thus, the transition to malignancy

Instantaneous cell migration velocity may be ill-defined

Cell crawling is critical to biological development, homeostasis and disease. In many cases, cell trajectories are quasi-random-walk. In vitro assays on flat surfaces often described such quasi-random-walk cell trajectories as approximations to a solution of a Langevin process. However, experiments show quasi-diffusive behavior at small timescales, indicating that instantaneous velocity and velocity autocorrelations are not well-defined. We propose to characterize mean-squared cell displacement using a modified F\"urth equation with three temporal and spatial regimes: short- and long-time/range diffusion and intermediate time/range ballistic motion. This analysis collapses mean-squared displacements of previously published experimental data onto a single-parameter family of curves, allowing direct comparison between movement in different cell types, and between experiments and numerical simulations. Our method also show that robust cell-motility quantification requires an experiment with a maximum interval between images of a few percent of the cell-motion persistence time or less, and a duration of a few orders-of-magnitude longer than the cell-motion persistence time or more.Comment: 5 pages, plus Supplemental materia