Nano-sized (10−9–10−7 m) particles offer many technical and biomedical advances over the bulk material. The use of nanoparticles in cosmetics, detergents, food and other commercial products is rapidly increasing despite little knowledge of their effect on organism metabolism. We show here that commercially manufactured polystyrene nanoparticles, transported through an aquatic food chain from algae, through zooplankton to fish, affect lipid metabolism and behaviour of the top consumer. At least three independent metabolic parameters differed between control and test fish: the weight loss, the triglycerides∶cholesterol ratio in blood serum, and the distribution of cholesterol between muscle and liver. Moreover, we demonstrate that nanoparticles bind to apolipoprotein A-I in fish serum in-vitro, thereby restraining them from properly utilising their fat reserves if absorbed through ingestion. In addition to the metabolic effects, we show that consumption of nanoparticle-containing zooplankton affects the feeding behaviour of the fish. The time it took the fish to consume 95% of the food presented to them was more than doubled for nanoparticle-exposed compared to control fish. Since many nano-sized products will, through the sewage system, end up in freshwater and marine habitats, our study provides a potential bioassay for testing new nano-sized material before manufacturing. In conclusion, our study shows that from knowledge of the molecular composition of the protein corona around nanoparticles it is possible to make a testable molecular hypothesis and bioassay of the potential biological risks of a defined nanoparticle at the organism and ecosystem level.

The combinatorial nature of many important mathematical problems, including nondeterministic-polynomial-time (NP)-complete problems, places a severe limitation on the problem size that can be solved with conventional, sequentially operating electronic computers. There have been significant efforts in conceiving parallel-computation approaches in the past, for example: DNA computation, quantum computation, and microfluidics-based computation. However, these approaches have not proven, so far, to be scalable and practical from a fabrication and operational perspective. Here, we report the foundations of an alternative parallel-computation system in which a given combinatorial problem is encoded into a graphical, modular network that is embedded in a nanofabricated planar device. Exploring the network in a parallel fashion using a large number of independent, molecularmotor-propelled agents then solves the mathematical problem. This approach uses orders of magnitude less energy than conventional computers, thus addressing issues related to power consumption and heat dissipation. We provide a proof-of-concept demonstration of such a device by solving, in a parallel fashion, the small instance {2, 5, 9} of the subset sum problem, which is a benchmark NPcomplete problem. Finally, we discuss the technical advances necessary to make our system scalable with presently available technology.parallel computing | molecular motors | NP complete | biocomputation | nanotechnology M any combinatorial problems of practical importance, such as the design and verification of circuits (1), the folding (2) and design (3) of proteins, and optimal network routing (4), require that a large number of possible candidate solutions are explored in a brute-force manner to discover the actual solution. Because the time required for solving these problems grows exponentially with their size, they are intractable for conventional electronic computers, which operate sequentially, leading to impractical computing times even for medium-sized problems. Solving such problems therefore requires efficient parallel-computation approaches (5). However, the approaches proposed so far suffer from drawbacks that have prevented their implementation. For example, DNA computation, which generates mathematical solutions by recombining DNA strands (6, 7), or DNA static (8) or dynamic (9) nanostructures, is limited by the need for impractically large amounts of DNA (10-13). Quantum computation is limited in scale by decoherence and by the small number of qubits that can be integrated (14). Microfluidics-based parallel computation (15) is difficult to scale up in practice due to rapidly diverging physical size and complexity of the computation devices with the size of the problem, as well as the need for impractically large external pressure.Here, we propose a parallel-computation approach, which is based on encoding combinatorial problems into the geometry of a physical network of lithographically defined channels, followed by exploration of the network in a par...

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Semiconductor nanowire arrays offer significant potential for biosensing applications with optical read-out due to their high surface area and due to the unique optical properties of one-dimensional materials. A challenge for optical read-out of analyte-binding to the nanowires is the need to efficiently collect and detect light from a three-dimensional volume. Here we show that light from fluorophores attached along several μm long vertical Al2O3 coated gallium phosphide nanowires couples into the wires, is guided along them and emitted at the tip. This enables effective collection of light emitted by fluorescent analytes located at different focal planes along the nanowire. We unequivocally demonstrate the light-guiding effect using a novel method whereby the changes in emitted fluorescence intensity are observed when fluorescent cytoskeletal filaments are propelled by molecular motors along the wires. The findings are discussed in relation to nanobiosensor developments, other nanotechnological applications, and fundamental studies of motor function.

Portable biosensor systems would benefit from reduced dependency on external power supplies as well as from further miniaturization and increased detection rate. Systems built around self-propelled biological molecular motors and cytoskeletal filaments hold significant promise in these regards as they are built from nanoscale components that enable nanoseparation independent of fluidic pumping. Previously reported microtubule-kinesin based devices are slow, however, compared to several existing biosensor systems. Here we demonstrate that this speed limitation can be overcome by using the faster actomyosin motor system. Moreover, due to lower flexural rigidity of the actin filaments, smaller features can be achieved compared to microtubule-based systems, enabling further miniaturization. Using a device designed through optimization by Monte Carlo simulations, we demonstrate extensive myosin driven enrichment of actin filaments on a detector area of less than 10 μm², with a concentration half-time of approximately 40 s. We also show accumulation of model analyte (streptavidin at nanomolar concentration in nanoliter effective volume) detecting increased fluorescence intensity within seconds after initiation of motor-driven transportation from capture regions. We discuss further optimizations of the system and incorporation into a complete biosensing workflow.