Invasive aspergillosis-on-chip: A quantitative treatment study of human Aspergillus fumigatus infection.

Invasive pulmonary aspergillosis is associated with a high mortality rate and poses a direct threat to immunocompromised patients. Here, we present the invasive aspergillosis-on-chip (IAC) model to investigate Aspergillus fumigatus infection in vitro. The model allows the study of the lateral growth and the invasive behaviour of fungal hyphae from the epithelium into the endothelial cell layer in an alveolus-on-chip model. We established an algorithm-based analysis pipeline for three-dimensional confocal microscopy images to visualize and quantify fungal morphology, including hyphal growth and branching. Human macrophages in the IAC model partially inhibited the growth of the fungus, contributed to the release of proinflammatory cytokines (IL-1, IL-6, TNF) and chemokines (IL-8 and MCP-1) associated with an increased number of invasive hyphae. Similar to in vivo, the application of the fungistatic drug caspofungin limited the fungal growth and resulted in morphological changes of the hyphal tree previously described in other studies. The IAC infection model allows the identification and characterization of cellular infection targets and in vitro testing of antifungal drugs in clinically relevant concentrations. It thus represents a promising tool to broaden the understanding of pathogenicity and pathophysiology of invasive aspergillosis.

One-step finite-difference time-domain algorithm to solve the Maxwell equations.

We present a one-step algorithm to solve the time-dependent Maxwell equations for systems with spatially varying permittivity and permeability. We compare the results of this algorithm with those obtained from the Yee algorithm and from unconditionally stable algorithms. We demonstrate that for a range of applications the one-step algorithm may be orders of magnitude more efficient than multiple time-step, finite-difference time-domain algorithms. We discuss both the virtues and limitations of this one-step approach.

Higher-order unconditionally stable algorithms to solve the time-dependent Maxwell equations.

For the recently introduced algorithms to solve the time-dependent Maxwell equations [J. S. Kole, M. T. Figge, and H. De Raedt, Phys. Rev. E 64, 066705 (2001)], we construct a variable grid implementation and an improved spatial discretization implementation that preserve the exceptional property of the algorithms to be unconditionally stable by construction. We find that the performance and accuracy of the corresponding algorithms are significant and illustrate their practical relevance by simulating various physical model systems.

Unconditionally stable algorithms to solve the time-dependent Maxwell equations.

Based on the Suzuki product-formula approach, we construct a family of unconditionally stable algorithms to solve the time-dependent Maxwell equations. We describe a practical implementation of these algorithms for one-, two-, and three-dimensional systems with spatially varying permittivity and permeability. The salient features of the algorithms are illustrated by computing selected eigenmodes and the full density of states of one-, two-, and three-dimensional models and by simulating the propagation of light in slabs of photonic band-gap materials.

Peierls transition with acoustic phonons and solitwistons in carbon nanotubes.

We show that the Peierls instability can result in softening of acoustic phonons with small wave vectors and suggest that this unusual transition takes place in carbon nanotubes, resulting in a static twist deformation of the nanotube lattice. The topological excitations in the ordered phase are immobile and propagate only in pairs.