Kondo physics in carbon nanotubes

The connection of electrical leads to wire-like molecules is a logical step in the development of molecular electronics, but also allows studies of fundamental physics. For example, metallic carbon nanotubes are quantum wires that have been found to act as one-dimensional quantum dots, Luttinger-liquids, proximity-induced superconductors and ballistic and diffusive one-dimensional metals. Here we report that electrically-contacted single-wall nanotubes can serve as powerful probes of Kondo physics, demonstrating the universality of the Kondo effect. Arising in the prototypical case from the interaction between a localized impurity magnetic moment and delocalized electrons in a metallic host, the Kondo effect has been used to explain enhanced low-temperature scattering from magnetic impurities in metals, and also occurs in transport through semiconductor quantum dots. The far higher tunability of dots (in our case, nanotubes) compared with atomic impurities renders new classes of Kondo-like effects accessible. Our nanotube devices differ from previous systems in which Kondo effects have been observed, in that they are one-dimensional quantum dots with three-dimensional metal (gold) reservoirs. This allows us to observe Kondo resonances for very large electron number (N) in the dot, and approaching the unitary limit (where the transmission reaches its maximum possible value). Moreover, we detect a previously unobserved Kondo effect, occurring for even values of N in a magnetic field.Comment: 7 pages, pdf onl

Choosing the Best Direction of Printing for Additive Manufacturing Process in Medical Applications Using a New Geometric Complexity Model Based on Part CAD Data

Additive manufacturing processes is now experiencing significant growth and is at the origin of intense research activity (optimization of topology, biomedical applications, etc.). One of the characteristics of this method is that the geometric complexity is free. The complexity of a CAD model is also a field of research. The basic idea is that the complexity of a component has implications in design and especially in manufacturing. Indeed, industrial competitiveness in the mechanical field generated the need to produce increasingly complex systems and parts (in terms of geometry, topology ...). Part deposition orientation is also very important factor of additive manufacturing as it effects build time, support structure, dimensional accuracy, surface finish and cost of the part. A number of layered manufacturing process specific parameters and constraints have to be considered while deciding the part deposition orientation. Determination of an optimal part deposition orientation is a difficult and time consuming task as one has to trade-off among various contradicting objectives like part surface finish and build time. This paper describes and compares various attempts made to determine part deposition orientation of orthoses using geometric complexity model and part CAD information. (c) Springer Nature Switzerland AG 2019

Microbiome profiling by Illumina sequencing of combinatorial sequence-tagged PCR products

We developed a low-cost, high-throughput microbiome profiling method that uses combinatorial sequence tags attached to PCR primers that amplify the rRNA V6 region. Amplified PCR products are sequenced using an Illumina paired-end protocol to generate millions of overlapping reads. Combinatorial sequence tagging can be used to examine hundreds of samples with far fewer primers than is required when sequence tags are incorporated at only a single end. The number of reads generated permitted saturating or near-saturating analysis of samples of the vaginal microbiome. The large number of reads al- lowed an in-depth analysis of errors, and we found that PCR-induced errors composed the vast majority of non-organism derived species variants, an ob- servation that has significant implications for sequence clustering of similar high-throughput data. We show that the short reads are sufficient to assign organisms to the genus or species level in most cases. We suggest that this method will be useful for the deep sequencing of any short nucleotide region that is taxonomically informative; these include the V3, V5 regions of the bac- terial 16S rRNA genes and the eukaryotic V9 region that is gaining popularity for sampling protist diversity.Comment: 28 pages, 13 figure

Hydrodebridement of wounds: effectiveness in reducing wound bacterial contamination and potential for air bacterial contamination

<p>Abstract</p> <p>Background</p> <p>The purpose of this study was to assess the level of air contamination with bacteria after surgical hydrodebridement and to determine the effectiveness of hydro surgery on bacterial reduction of a simulated infected wound.</p> <p>Methods</p> <p>Four porcine samples were scored then infected with a broth culture containing a variety of organisms and incubated at 37°C for 24 hours. The infected samples were then debrided with the hydro surgery tool (Versajet, Smith and Nephew, Largo, Florida, USA). Samples were taken for microbiology, histology and scanning electron microscopy pre-infection, post infection and post debridement. Air bacterial contamination was evaluated before, during and after debridement by using active and passive methods; for active sampling the SAS-Super 90 air sampler was used, for passive sampling settle plates were located at set distances around the clinic room.</p> <p>Results</p> <p>There was no statistically significant reduction in bacterial contamination of the porcine samples post hydrodebridement. Analysis of the passive sampling showed a significant (<it>p </it>< 0.001) increase in microbial counts post hydrodebridement. Levels ranging from 950 colony forming units per meter cubed (CFUs/m³) to 16780 CFUs/m³were observed with active sampling of the air whilst using hydro surgery equipment compared with a basal count of 582 CFUs/m³. During removal of the wound dressing, a significant increase was observed relative to basal counts (<it>p </it>< 0.05). Microbial load of the air samples was still significantly raised 1 hour post-therapy.</p> <p>Conclusion</p> <p>The results suggest a significant increase in bacterial air contamination both by active sampling and passive sampling. We believe that action might be taken to mitigate fallout in the settings in which this technique is used.</p

Dynein structure and power stroke

Dynein ATPases are microtubule motors that are critical to diverse processes such as vesicle transport and the beating of sperm tails; however, their mechanism of force generation is unknown. Each dynein comprises a head, from which a stalk and a stem emerge. Here we use electron microscopy and image processing to reveal new structural details of dynein c, an isoform from Chlamydomonas reinhardtii flagella, at the start and end of its power stroke. Both stem and stalk are flexible, and the stem connects to the head by means of a linker approximately 10 nm long that we propose lies across the head. With both ADP and vanadate bound, the stem and stalk emerge from the head 10 nm apart. However, without nucleotide they emerge much closer together owing to a change in linker orientation, and the coiled-coil stalk becomes stiffer. The net result is a shortening of the molecule coupled to an approximately 15-nm displacement of the tip of the stalk. These changes indicate a mechanism for the dynein power stroke

Exponential Random Graph Modeling for Complex Brain Networks

Exponential random graph models (ERGMs), also known as p* models, have been utilized extensively in the social science literature to study complex networks and how their global structure depends on underlying structural components. However, the literature on their use in biological networks (especially brain networks) has remained sparse. Descriptive models based on a specific feature of the graph (clustering coefficient, degree distribution, etc.) have dominated connectivity research in neuroscience. Corresponding generative models have been developed to reproduce one of these features. However, the complexity inherent in whole-brain network data necessitates the development and use of tools that allow the systematic exploration of several features simultaneously and how they interact to form the global network architecture. ERGMs provide a statistically principled approach to the assessment of how a set of interacting local brain network features gives rise to the global structure. We illustrate the utility of ERGMs for modeling, analyzing, and simulating complex whole-brain networks with network data from normal subjects. We also provide a foundation for the selection of important local features through the implementation and assessment of three selection approaches: a traditional p-value based backward selection approach, an information criterion approach (AIC), and a graphical goodness of fit (GOF) approach. The graphical GOF approach serves as the best method given the scientific interest in being able to capture and reproduce the structure of fitted brain networks

Using fractional exhaled nitric oxide (FeNO) to diagnose steroid-responsive disease and guide asthma management in routine care

Acknowledgements We thank Robin Taylor for his informative thinking and publications on FeNO, which have helped to influence and direct the thinking of the authors. Funding Extraction of the real-life dataset was funded by Research in Real Life Limited, the analysis of the dataset and the writing of this manuscript were co-funded (50:50) by Research in Real Life Limited and Aerocrine.Peer reviewedPublisher PD

Cooperation and virulence in acute Pseudomonas aeruginosa infections

BACKGROUND: Efficient host exploitation by parasites is frequently likely to depend on cooperative behaviour. Under these conditions, mixed-strain infections are predicted to show lower virulence (host mortality) than are single-clone infections, due to competition favouring non-contributing social 'cheats' whose presence will reduce within-host growth. We tested this hypothesis using the cooperative production of iron-scavenging siderophores by the pathogenic bacterium Pseudomonas aeruginosa in an insect host. RESULTS: We found that infection by siderophore-producing bacteria (cooperators) results in more rapid host death than does infection by non-producers (cheats), and that mixtures of both result in intermediate levels of virulence. Within-host bacterial growth rates exhibited the same pattern. Crucially, cheats were more successful in mixed infections compared with single-clone infections, while the opposite was true of cooperators. CONCLUSION: These data demonstrate that mixed clone infections can favour the evolution of social cheats, and thus decrease virulence when parasite growth is dependent on cooperative behaviours