Analysis of defect-related inhomogeneous electroluminescence in InGaN/GaN QW LEDs

The inhomogeneous electroluminescence (EL) of InGaN/GaN quantum well light emitting diode structures was investigated in this study. Electroluminescence hyperspectral images showed that inhomogeneities in the form of bright spots exhibited spectrally blue-shifted and broadened emission. Scanning electron microscopy combined with cathodoluminescence (SEM-CL) was used to identify hexagonal pits at the centre of approximately 20% of these features. Scanning transmission electron microscopy imaging with energy dispersive X-ray spectroscopy (STEM-EDX) indicated there may be p-doped AlGaN within the active region caused by the presence of the pit. Weak beam dark-field TEM (WBDF-TEM) revealed the presence of bundles of dislocations associated with the pit, suggesting the surface features which cause the inhomogeneous EL may occur at coalescence boundaries, supported by trends in the number of features observed across the wafer.The European Research Council has provided financial support under the European Community’s Seventh Framework Programme/ ERC grant agreement no. 279361 (MACONS).This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.spmi.2016.03.03

Three-Dimensional Stochastic Off-Lattice Model of Binding Chemistry in Crowded Environments

Molecular crowding is one of the characteristic features of the intracellular environment, defined by a dense mixture of varying kinds of proteins and other molecules. Interaction with these molecules significantly alters the rates and equilibria of chemical reactions in the crowded environment. Numerous fundamental activities of a living cell are strongly influenced by the crowding effect, such as protein folding, protein assembly and disassembly, enzyme activity, and signal transduction. Quantitatively predicting how crowding will affect any particular process is, however, a very challenging problem because many physical and chemical parameters act synergistically in ways that defy easy analysis. To build a more realistic model for this problem, we extend a prior stochastic off-lattice model from two-dimensional (2D) to three-dimensional (3D) space and examine how the 3D results compare to those found in 2D. We show that both models exhibit qualitatively similar crowding effects and similar parameter dependence, particularly with respect to a set of parameters previously shown to act linearly on total reaction equilibrium. There are quantitative differences between 2D and 3D models, although with a generally gradual nonlinear interpolation as a system is extended from 2D to 3D. However, the additional freedom of movement allowed to particles as thickness of the simulation box increases can produce significant quantitative change as a system moves from 2D to 3D. Simulation results over broader parameter ranges further show that the impact of molecular crowding is highly dependent on the specific reaction system examined

Synthetic Protocells Interact with Viral Nanomachinery and Inactivate Pathogenic Human Virus

We present a new antiviral strategy and research tool that could be applied to a wide range of enveloped viruses that infect human beings via membrane fusion. We test this strategy on two emerging zoonotic henipaviruses that cause fatal encephalitis in humans, Nipah (NiV) and Hendra (HeV) viruses. In the new approach, artificial cell-like particles (protocells) presenting membrane receptors in a biomimetic manner were developed and found to attract and inactivate henipavirus envelope glycoprotein pseudovirus particles, preventing infection. The protocells do not accumulate virus during the inactivation process. The use of protocells that interact with, but do not accumulate, viruses may provide significant advantages over current antiviral drugs, and this general approach may have wide potential for antiviral development

Unified regression model of binding equilibria in crowded environments

Molecular crowding is a critical feature distinguishing intracellular environments from idealized solution-based environments and is essential to understanding numerous biochemical reactions, from protein folding to signal transduction. Many biochemical reactions are dramatically altered by crowding, yet it is extremely difficult to predict how crowding will quantitatively affect any particular reaction systems. We previously developed a novel stochastic off-lattice model to efficiently simulate binding reactions across wide parameter ranges in various crowded conditions. We now show that a polynomial regression model can incorporate several interrelated parameters influencing chemistry under crowded conditions. The unified model of binding equilibria accurately reproduces the results of particle simulations over a broad range of variation of six physical parameters that collectively yield a complicated, non-linear crowding effect. The work represents an important step toward the long-term goal of computationally tractable predictive models of reaction chemistry in the cellular environment

Probing Cellular Dynamics with a Chemical Signal Generator

Observations of material and cellular systems in response to time-varying chemical stimuli can aid the analysis of dynamic processes. We describe a microfluidic “chemical signal generator,” a technique to apply continuously varying chemical concentration waveforms to arbitrary locations in a microfluidic channel through feedback control of the interface between parallel laminar (co-flowing) streams. As the flow rates of the streams are adjusted, the channel walls are exposed to a chemical environment that shifts between the individual streams. This approach can be used to probe the dynamic behavior of objects or substances adherent to the interior of the channel. To demonstrate the technique, we exposed live fibroblast cells to ionomycin, a membrane-permeable calcium ionophore, while assaying cytosolic calcium concentration. Through the manipulation of the laminar flow interface, we exposed the cells' endogenous calcium handling machinery to spatially-contained discrete and oscillatory intracellular disturbances, which were observed to elicit a regulatory response. The spatiotemporal precision of the generated signals opens avenues to previously unapproachable areas for potential investigation of cell signaling and material behavior

Computing, Design, Art: Reflections on an Innovative Moment in History

The paper is concerned with the role of art and design in the history and philosophy of computing. It offers insights arising from research into a period in the 1960s and 70s, particularly in the UK, when computing became more available to artists and designers, focusing on John Lansdown (1929-1999) and Bruce Archer (1922-2005) in London. Models of computing interacted with conceptualisations of art, design and related creative activities in important ways

Pre-Whaling Genetic Diversity and Population Ecology in Eastern Pacific Gray Whales: Insights from Ancient DNA and Stable Isotopes

Commercial whaling decimated many whale populations, including the eastern Pacific gray whale, but little is known about how population dynamics or ecology differed prior to these removals. Of particular interest is the possibility of a large population decline prior to whaling, as such a decline could explain the ∼5-fold difference between genetic estimates of prior abundance and estimates based on historical records. We analyzed genetic (mitochondrial control region) and isotopic information from modern and prehistoric gray whales using serial coalescent simulations and Bayesian skyline analyses to test for a pre-whaling decline and to examine prehistoric genetic diversity, population dynamics and ecology. Simulations demonstrate that significant genetic differences observed between ancient and modern samples could be caused by a large, recent population bottleneck, roughly concurrent with commercial whaling. Stable isotopes show minimal differences between modern and ancient gray whale foraging ecology. Using rejection-based Approximate Bayesian Computation, we estimate the size of the population bottleneck at its minimum abundance and the pre-bottleneck abundance. Our results agree with previous genetic studies suggesting the historical size of the eastern gray whale population was roughly three to five times its current size

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

Design of complex biologically based nanoscale systems using multi-agent simulations and structure-behavior-function representations

The process of designing integrated biological systems across scales is difficult, with challenges arising from the modeling, understanding, and search of complex system design spaces. This paper explores these challenges through consideration of how stochastic nanoscale phenomenon relate to higher level systems functioning across many scales. A domain-independent methodology is introduced which uses multi-agent simulations to predict emergent system behavior and structure-behavior-function (SBF) representations to facilitate design space navigation. The methodology is validated through a nanoscale design application of synthetic myosin motor systems. In the multi-agent simulation, myosins are independent computational agents with varied structural inputs that enable differently tuned mechanochemical behaviors. Four synthetic myosins were designed and replicated as agent populations, and their simulated behavior was consistent with empirical studies of individual myosins and the macroscopic performance of myosin-powered muscle contractions. However, in order to configure high performance technologies, designers must effectively reason about simulation inputs and outputs; we find that counter-intuitive relations arise when linking system performance to individual myosin structures. For instance, one myosin population had a lower system force even though more myosins contributed to system-level force. This relationship is elucidated with SBF by considering the distribution of structural states and behaviors in agent populations. For the lower system force population, it is found that although more myosins are producing force, a greater percentage of the population produces negative force. The success of employing SBF for understanding system interactions demonstrates how the methodology may aid designers in complex systems embodiment. The methodology's domain-independence promotes its extendibility to similar complex systems, and in the myosin test case the approach enabled the reduction of a complex physical phenomenon to a design space consisting of only a few critical parameters. The methodology is particularly suited for complex systems with many parts operating stochastically across scales, and should prove invaluable for engineers facing the challenges of biological nanoscale design, where designs with unique properties require novel approaches or useful configurations in nature await discovery. Copyright © 2013 by ASME