Simon Brown

Bio: Simon Brown is an academic researcher from MacDiarmid Institute for Advanced Materials and Nanotechnology. The author has contributed to research in topics: Bismuth & Cluster (physics). The author has an hindex of 29, co-authored 182 publications receiving 5521 citations. Previous affiliations of Simon Brown include CGG & University of British Columbia.

Carbon nanotubes introduced into the abdominal cavity of mice show asbestos-like pathogenicity in a pilot study.

Abstract: Carbon nanotubes have distinctive characteristics, but their needle-like fibre shape has been compared to asbestos, raising concerns that widespread use of carbon nanotubes may lead to mesothelioma, cancer of the lining of the lungs caused by exposure to asbestos. Here we show that exposing the mesothelial lining of the body cavity of mice, as a surrogate for the mesothelial lining of the chest cavity, to long multiwalled carbon nanotubes results in asbestos-like, length-dependent, pathogenic behaviour. This includes inflammation and the formation of lesions known as granulomas. This is of considerable importance, because research and business communities continue to invest heavily in carbon nanotubes for a wide range of products under the assumption that they are no more hazardous than graphite. Our results suggest the need for further research and great caution before introducing such products into the market if long-term harm is to be avoided.

Apoptosis disables CD31-mediated cell detachment from phagocytes promoting binding and engulfment.

Abstract: Macrophage recognition and ingestion of 'self' cells undergoing apoptosis in vivo protects tissues from the toxic contents of dying cells and modulates macrophage regulation of inflammatory and immune responses. However, the complex molecular mechanisms mediating macrophage discrimination between viable and apoptotic cells are poorly understood. In particular, little is known of why viable nucleated cells are not engulfed by macrophages. To reveal active repulsion of viable cells and to seek specific capture or 'tethering' of apoptotic cells, we studied macrophage binding of viable and apoptotic leukocytes under conditions of flow. We found that homophilic ligation of CD31 (ref. 4) on viable leukocytes promoted their active, temperature-dependent detachment under low shear, whereas such CD31-mediated detachment was disabled in apoptotic leukocytes, promoting tight binding and macrophage ingestion of dying cells. Here we propose that CD31 (also known as platelet-endothelial cell adhesion molecule-1, PECAM-1) is an example of a cell-surface molecule that prevents phagocyte ingestion of closely apposed viable cells by transmitting 'detachment' signals, and which changes function on apoptosis, promoting tethering of dying cells to phagocytes.

Impaired recognition of apoptotic neutrophils by the C1q/calreticulin and CD91 pathway in systemic lupus erythematosus.

Abstract: Objective A deficiency in a subcomponent of C1q can result in increased susceptibility to autoimmune diseases such as systemic lupus erythematosus (SLE). The monocyte endocytic receptor CD91 is implicated in the endocytosis of apoptotic neutrophils via interactions with C1q and calreticulin. In this clinical study, we studied the binding of C1q to leukocytes and determined whether C1q bound specifically to calreticulin and CD91 on cells undergoing apoptosis in SLE. Methods Proximal antibody phage display, calreticulin-transfected cells, and immunocytochemical and confocal techniques were used in a comprehensive analysis of direct binding of C1q to apoptotic neutrophils that were obtained from healthy individuals and from patients with SLE. In addition, apoptotic cellular systems were assessed in vitro. Results C1q appeared to colocalize to apoptotic blebs on the surface of leukocytes in association with both calreticulin and CD91, as determined by phage display and transfected cell studies. However, C1q did not bind to apoptotic cells isolated from SLE patients, despite the positivity of the cells for both calreticulin and CD91. Surface expression of calreticulin decreased on neutrophils as they aged, but increased on monocytes. In an apoptotic phagocytic assay, the addition of C1q and calreticulin significantly enhanced the phagocytosis of apoptotic cell debris by monocyte-derived cells. Conclusion These observations indicate that neutrophils from SLE patients have a reduced ability to be recognized and removed by the C1q/calreticulin/CD91-mediated apoptotic pathway, despite the presence of main apoptotic recognition partners. This suggests that an additional component, as yet unidentified, acts as a C1q binding partner on apoptotic cells, and this component may be lacking in cells isolated from SLE patients.

Real-time TEM and kinetic Monte Carlo studies of the coalescence of decahedral gold nanoparticles.

Abstract: We report on a real-time in situ TEM study of the coalescence of individual pairs of decahedral gold nanoparticles, which have been synthesized in solution. We observe the rate of growth of the neck that joins two particles during coalescence and compare this to classical continuum theory and to atomistic kinetic Monte Carlo simulations. We find good agreement between the observations and the simulations but not with the classical continuum model. This disagreement is attributed to the faceted nature of the particles.

Nanoscale electronic devices & fabrication methods

Abstract: The invention relates to a method of forming a conducting nanowire between two contacts on a substrate surface wherein a plurality of nanoparticles is deposited on the substrate in the region between the contacts, and the single nanowire running substantially between the two contacts is formed by either by monitoring the conduction between the contacts and ceasing deposition at the onset of conduction, and/or modifying the substrate to achieve, or taking advantage of pre-existing topographical features which will cause the nanoparticles to form the nanowire. The resultant conducting nanowires are also claimed as well as devices incorporating such nanowires.

Machine learning

Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Understanding biophysicochemical interactions at the nano–bio interface

Abstract: Rapid growth in nanotechnology is increasing the likelihood of engineered nanomaterials coming into contact with humans and the environment. Nanoparticles interacting with proteins, membranes, cells, DNA and organelles establish a series of nanoparticle/biological interfaces that depend on colloidal forces as well as dynamic biophysicochemical interactions. These interactions lead to the formation of protein coronas, particle wrapping, intracellular uptake and biocatalytic processes that could have biocompatible or bioadverse outcomes. For their part, the biomolecules may induce phase transformations, free energy releases, restructuring and dissolution at the nanomaterial surface. Probing these various interfaces allows the development of predictive relationships between structure and activity that are determined by nanomaterial properties such as size, shape, surface chemistry, roughness and surface coatings. This knowledge is important from the perspective of safe use of nanomaterials.

Carbon Nanotubes: Present and Future Commercial Applications

Abstract: Worldwide commercial interest in carbon nanotubes (CNTs) is reflected in a production capacity that presently exceeds several thousand tons per year. Currently, bulk CNT powders are incorporated in diverse commercial products ranging from rechargeable batteries, automotive parts, and sporting goods to boat hulls and water filters. Advances in CNT synthesis, purification, and chemical modification are enabling integration of CNTs in thin-film electronics and large-area coatings. Although not yet providing compelling mechanical strength or electrical or thermal conductivities for many applications, CNT yarns and sheets already have promising performance for applications including supercapacitors, actuators, and lightweight electromagnetic shields.

Skyrmion Lattice in a Chiral Magnet

Abstract: Skyrmions represent topologically stable field configurations with particle-like properties. We used neutron scattering to observe the spontaneous formation of a two-dimensional lattice of skyrmion lines, a type of magnetic vortex, in the chiral itinerant-electron magnet MnSi. The skyrmion lattice stabilizes at the border between paramagnetism and long-range helimagnetic order perpendicular to a small applied magnetic field regardless of the direction of the magnetic field relative to the atomic lattice. Our study experimentally establishes magnetic materials lacking inversion symmetry as an arena for new forms of crystalline order composed of topologically stable spin states.

Topological properties and dynamics of magnetic skyrmions

Abstract: Magnetic skyrmions are particle-like nanometre-sized spin textures of topological origin found in several magnetic materials, and are characterized by a long lifetime. Skyrmions have been observed both by means of neutron scattering in momentum space and microscopy techniques in real space, and their properties include novel Hall effects, current-driven motion with ultralow current density and multiferroic behaviour. These properties can be understood from a unified viewpoint, namely the emergent electromagnetism associated with the non-coplanar spin structure of skyrmions. From this description, potential applications of skyrmions as information carriers in magnetic information storage and processing devices are envisaged.