Imaging and controlling electron transport inside a quantum ring

Traditionally, the understanding of quantum transport, coherent and ballistic1, relies on the measurement of macroscopic properties such as the conductance. While powerful when coupled to statistical theories, this approach cannot provide a detailed image of "how electrons behave down there". Ideally, understanding transport at the nanoscale would require tracking each electron inside the nano-device. Significant progress towards this goal was obtained by combining Scanning Probe Microscopy (SPM) with transport measurements2-7. Some studies even showed signatures of quantum transport in the surrounding of nanostructures4-6. Here, SPM is used to probe electron propagation inside an open quantum ring exhibiting the archetype of electron wave interference phenomena: the Aharonov-Bohm effect8. Conductance maps recorded while scanning the biased tip of a cryogenic atomic force microscope above the quantum ring show that the propagation of electrons, both coherent and ballistic, can be investigated in situ, and even be controlled by tuning the tip potential.Comment: 11 text pages + 3 figure

LEMS: a language for expressing complex biological models in concise and hierarchical form and its use in underpinning NeuroML 2.

Computational models are increasingly important for studying complex neurophysiological systems. As scientific tools, it is essential that such models can be reproduced and critically evaluated by a range of scientists. However, published models are currently implemented using a diverse set of modeling approaches, simulation tools, and computer languages making them inaccessible and difficult to reproduce. Models also typically contain concepts that are tightly linked to domain-specific simulators, or depend on knowledge that is described exclusively in text-based documentation. To address these issues we have developed a compact, hierarchical, XML-based language called LEMS (Low Entropy Model Specification), that can define the structure and dynamics of a wide range of biological models in a fully machine readable format. We describe how LEMS underpins the latest version of NeuroML and show that this framework can define models of ion channels, synapses, neurons and networks. Unit handling, often a source of error when reusing models, is built into the core of the language by specifying physical quantities in models in terms of the base dimensions. We show how LEMS, together with the open source Java and Python based libraries we have developed, facilitates the generation of scripts for multiple neuronal simulators and provides a route for simulator free code generation. We establish that LEMS can be used to define models from systems biology and map them to neuroscience-domain specific simulators, enabling models to be shared between these traditionally separate disciplines. LEMS and NeuroML 2 provide a new, comprehensive framework for defining computational models of neuronal and other biological systems in a machine readable format, making them more reproducible and increasing the transparency and accessibility of their underlying structure and properties

Improved climatological precipitation characteristics over West Africa at convection-permitting scales

The West African climate is unique and challenging to reproduce using standard resolution climate models as a large proportion of precipitation comes from organised deep convection. For the first time, a regional 4.5 km convection permitting simulation was performed on a pan-African domain for a period of 10 years (1997–2006). The 4.5 km simulation (CP4A) is compared with a 25 × 40 km convection-parameterised model (R25) over West Africa. CP4A shows increased mean precipitation, which results in improvements in the mature phase of the West African monsoon but deterioration in the early and late phases. The distribution of precipitation rates is improved due to more short lasting intense rainfall events linked with mesoscale convective systems. Consequently, the CP4A model shows a better representation of wet and dry spells both at the daily and sub-daily time-scales. The diurnal cycle of rainfall is improved, which impacts the diurnal cycle of monsoon winds and increases moisture convergence in the Sahel. Although shortcomings were identified, with implications for model development, this convection-permitting model provides a much more reliable precipitation distribution than its convection-parameterised counterpart at both daily and sub-daily time-scales. Convection-permitting scales will therefore be useful to address the crucial question of how the precipitation distribution will change in the future

libNeuroML and PyLEMS: using Python to combine procedural and declarative modeling approaches in computational neuroscience.

NeuroML is an XML-based model description language, which provides a powerful common data format for defining and exchanging models of neurons and neuronal networks. In the latest version of NeuroML, the structure and behavior of ion channel, synapse, cell, and network model descriptions are based on underlying definitions provided in LEMS, a domain-independent language for expressing hierarchical mathematical models of physical entities. While declarative approaches for describing models have led to greater exchange of model elements among software tools in computational neuroscience, a frequent criticism of XML-based languages is that they are difficult to work with directly. Here we describe two Application Programming Interfaces (APIs) written in Python (http://www.python.org), which simplify the process of developing and modifying models expressed in NeuroML and LEMS. The libNeuroML API provides a Python object model with a direct mapping to all NeuroML concepts defined by the NeuroML Schema, which facilitates reading and writing the XML equivalents. In addition, it offers a memory-efficient, array-based internal representation, which is useful for handling large-scale connectomics data. The libNeuroML API also includes support for performing common operations that are required when working with NeuroML documents. Access to the LEMS data model is provided by the PyLEMS API, which provides a Python implementation of the LEMS language, including the ability to simulate most models expressed in LEMS. Together, libNeuroML and PyLEMS provide a comprehensive solution for interacting with NeuroML models in a Python environment

Imaging Coulomb Islands in a Quantum Hall Interferometer

In the Quantum Hall regime, near integer filling factors, electrons should only be transmitted through spatially-separated edge states. However, in mesoscopic systems, electronic transmission turns out to be more complex, giving rise to a large spectrum of magnetoresistance oscillations. To explain these observations, recent models put forward that, as edge states come close to each other, electrons can hop between counterpropagating edge channels, or tunnel through Coulomb islands. Here, we use scanning gate microscopy to demonstrate the presence of quantum Hall Coulomb islands, and reveal the spatial structure of transport inside a quantum Hall interferometer. Electron islands locations are found by modulating the tunneling between edge states and confined electron orbits. Tuning the magnetic field, we unveil a continuous evolution of active electron islands. This allows to decrypt the complexity of high magnetic field magnetoresistance oscillations, and opens the way to further local scale manipulations of quantum Hall localized states

The pathology of familial breast cancer: Immunohistochemistry and molecular analysis

Extensive studies of BRCA1- and BRCA2-associated breast tumours have been carried out in the few years since the identification of these familial breast cancer predisposing genes. The morphological studies suggest that BRCA1 tumours differ from BRCA2 tumours and from sporadic breast cancers. Recent progress in immunohistochemistry and molecular biology techniques has enabled in-depth investigation of molecular pathology of these tumours. Studies to date have investigated issues such as steroid hormone receptor expression, mutation status of tumour suppressor genes TP53 and c-erbB2, and expression profiles of cell cycle proteins p21, p27 and cyclin D(1). Despite relative paucity of data, strong evidence of unique biological characteristics of BRCA1-associated breast cancer is accumulating. BRCA1-associated tumours appear to show an increased frequency of TP53 mutations, frequent p53 protein stabilization and absence of imunoreactivity for steroid hormone receptors. Further studies of larger number of samples of both BRCA1- and BRCA2-associated tumours are necessary to clarify and confirm these observations

Bone mineral density and fractures in older men with chronic obstructive pulmonary disease or asthma

In 5,541 community dwelling men, chronic obstructive pulmonary disease, or asthma was associated with lower bone mineral density (BMD) at the spine and total hip and an increased risk of vertebral and nonvertebral fractures independent of age, body mass index, and smoking. Men prescribed with corticosteroids had the lowest BMD. It is unclear whether chronic obstructive pulmonary disease (COPD) is independently associated with BMD and fractures. In 5,541 men from the Osteoporotic Fractures in Men Study, history of COPD or asthma, current treatment with corticosteroids, BMD, bone loss after 4.5 years and fractures were ascertained. Seven hundred fourteen (13%) men reported COPD or asthma, of which 103 were prescribed an oral steroid and 177 an inhaled steroid. Independent of confounders, men prescribed corticosteroids for COPD or asthma had the lowest BMD and a 2-fold increased risk of vertebral osteoporosis compared to men with no history of COPD or asthma (OR 2.13, 95% CI (confidence interval) 1.15–3.93 oral steroids; OR 2.05, 95% CI 1.27–3.31 inhaled steroids). During follow-up, BMD increased at the spine, but there was no difference in bone loss at the hip. However, men with COPD or asthma had a 2.6- and 1.4-fold increased risk of vertebral and nonvertebral fractures, respectively. Chronic obstructive pulmonary disease or asthma was associated with lower BMD at the spine and hip and increased risk of vertebral and nonvertebral fractures independent of age, clinic site, BMI, and smoking. A history of COPD or asthma may be a useful clinical risk factor to identify patients with osteoporosis

Reconciling the potentially irreconcilable? Genotypic and phenotypic amoxicillin-clavulanate resistance in Escherichia coli

Resistance to amoxicillin-clavulanate, a widely used beta-lactam/beta-lactamase inhibitor combination antibiotic, is rising globally, and yet susceptibility testing remains challenging. To test whether whole-genome sequencing (WGS) could provide a more reliable assessment of susceptibility than traditional methods, we predicted resistance from WGS for 976 Escherichia coli bloodstream infection isolates from Oxfordshire, United Kingdom, comparing against phenotypes from the BD Phoenix (calibrated against EUCAST guidelines). A total of 339/976 (35%) isolates were amoxicillin-clavulanate resistant. Predictions based solely on beta-lactamase presence/absence performed poorly (sensitivity, 23% [78/339]) but improved when genetic features associated with penicillinase hyperproduction (e.g., promoter mutations and copy number estimates) were considered (sensitivity, 82% [277/339]; P < 0.0001). Most discrepancies occurred in isolates with MICs within ±1 doubling dilution of the breakpoint. We investigated two potential causes: the phenotypic reference and the binary resistant/susceptible classification. We performed reference standard, replicated phenotyping in a random stratified subsample of 261/976 (27%) isolates using agar dilution, following both EUCAST and CLSI guidelines, which use different clavulanate concentrations. As well as disagreeing with each other, neither agar dilution phenotype aligned perfectly with genetic features. A random-effects model investigating associations between genetic features and MICs showed that some genetic features had small, variable and additive effects, resulting in variable resistance classification. Using model fixed-effects to predict MICs for the non-agar dilution isolates, predicted MICs were in essential agreement (±1 doubling dilution) with observed (BD Phoenix) MICs for 691/715 (97%) isolates. This suggests amoxicillin-clavulanate resistance in E. coli is quantitative, rather than qualitative, explaining the poorly reproducible binary (resistant/susceptible) phenotypes and suboptimal concordance between different phenotypic methods and with WGS-based predictions

An analytical approach for prediction of elastohydrodynamic friction with inlet shear heating and starvation

An analytical friction model is presented, predicting the coefficient of friction in elastohydrodynamic (EHD) contacts. Three fully formulated SAE 75W-90 axle lubricants are examined. The effect of inlet shear heating (ISH) and starvation is accounted for in the developed friction model. The film thickness and the predicted friction are compared with experimental measurements obtained through optical interferometry and use of a mini traction machine. The results indicate the significant contribution of ISH and starvation on both the film thickness and coefficient of friction. A strong interaction between those two phenomena is also demonstrated, along with their individual and combined contribution on the EHD friction