Magnetic-field-induced singularities in spin dependent tunneling through InAs quantum dots

Current steps attributed to resonant tunneling through individual InAs quantum dots embedded in a GaAs-AlAs-GaAs tunneling device are investigated experimentally in magnetic fields up to 28 T. The steps evolve into strongly enhanced current peaks in high fields. This can be understood as a field-induced Fermi-edge singularity due to the Coulomb interaction between the tunneling electron on the quantum dot and the partly spin polarized Fermi sea in the Landau quantized three-dimensional emitter.Comment: 5 pages, 4 figure

Strong quantum memory at resonant Fermi edges revealed by shot noise

Studies of non-equilibrium current fluctuations enable assessing correlations involved in quantum transport through nanoscale conductors. They provide additional information to the mean current on charge statistics and the presence of coherence, dissipation, disorder, or entanglement. Shot noise, being a temporal integral of the current autocorrelation function, reveals dynamical information. In particular, it detects presence of non-Markovian dynamics, i.e., memory, within open systems, which has been subject of many current theoretical studies. We report on low-temperature shot noise measurements of electronic transport through InAs quantum dots in the Fermi-edge singularity regime and show that it exhibits strong memory effects caused by quantum correlations between the dot and fermionic reservoirs. Our work, apart from addressing noise in archetypical strongly correlated system of prime interest, discloses generic quantum dynamical mechanism occurring at interacting resonant Fermi edges.Comment: 6 pages, 3 figure

Erratum: Author Correction: Identification of genes required for eye development by high-throughput screening of mouse knockouts.

[This corrects the article DOI: 10.1038/s42003-018-0226-0.]

The epidemiology of osteonecrosis: findings from the GPRD and THIN databases in the UK

Summary We conducted a case–control study to examine osteonecrosis (ON) incidence, patient characteristics, and selected potential risk factors using two health record databases in the UK. Statistically significant risk factors for ON included systemic corticosteroid use, hospitalization, referral or specialist visit, bone fracture, any cancer, osteoporosis, connective tissue disease, and osteoarthritis.Introduction The purpose of this case–control study was to examine the incidence of osteonecrosis (ON), patient characteristics, and selected potential risk factors for ON using two health record databases in the UK: the General Practice Research Database and The Health Improvement Network.Methods ON cases (n? =?792) were identified from 1989 to 2003 and individually matched (age, sex, and medical practice) up to six controls (n?=?4,660) with no record of ON. Possible risk factors were considered for inclusion based on a review of published literature. Annual incidence rates were computed, and a multivariable logistic regression model was derived to evaluate selected risk factors.Results ON of the hip represented the majority of cases (75.9%). Statistically significant risk factors for ON were systemic corticosteroid use in the previous 2 years, hospitalization, referral or specialist visit, bone fracture, any cancer, osteoporosis, connective tissue disease, and osteoarthritis within the past 5 years. Only 4.4% of ON cases were exposed to bisphosphonates within the previous 2 years.Conclusions This study provides further perspective on the descriptive epidemiology of ON. Studies utilizing more recent data may further elucidate the understanding of ON key predictors.<br/

Animal models for arthritis: innovative tools for prevention and treatment

The development of novel treatments for rheumatoid arthritis (RA) requires the interplay between clinical observations and studies in animal models. Given the complex molecular pathogenesis and highly heterogeneous clinical picture of RA, there is an urgent need to dissect its multifactorial nature and to propose new strategies for preventive, early and curative treatments. Research on animal models has generated new knowledge on RA pathophysiology and aetiology and has provided highly successful paradigms for innovative drug development. Recent focus has shifted towards the discovery of novel biomarkers, with emphasis on presymptomatic and emerging stages of human RA, and towards addressing the pathophysiological mechanisms and subsequent efficacy of interventions that underlie different disease variants. Shifts in the current paradigms underlying RA pathogenesis have also led to increased demand for new (including humanised) animal models. There is therefore an urgent need to integrate the knowledge on human and animal models with the ultimate goal of creating a comprehensive 'pathogenesis map' that will guide alignment of existing and new animal models to the subset of disease they mimic. This requires full and standardised characterisation of all models at the genotypic, phenotypic and biomarker level, exploiting recent technological developments in '-omics' profiling and computational biology as well as state of the art bioimaging. Efficient integration and dissemination of information and resources as well as outreach to the public will be necessary to manage the plethora of data accumulated and to increase community awareness and support for innovative animal model research in rheumatology

insights for ecological applications from the German Biodiversity Exploratories

Biodiversity, a multidimensional property of natural systems, is difficult to quantify partly because of the multitude of indices proposed for this purpose. Indices aim to describe general properties of communities that allow us to compare different regions, taxa, and trophic levels. Therefore, they are of fundamental importance for environmental monitoring and conservation, although there is no consensus about which indices are more appropriate and informative. We tested several common diversity indices in a range of simple to complex statistical analyses in order to determine whether some were better suited for certain analyses than others. We used data collected around the focal plant Plantago lanceolata on 60 temperate grassland plots embedded in an agricultural landscape to explore relationships between the common diversity indices of species richness (S), Shannon's diversity (H'), Simpson's diversity (D1), Simpson's dominance (D2), Simpson's evenness (E), and Berger–Parker dominance (BP). We calculated each of these indices for herbaceous plants, arbuscular mycorrhizal fungi, aboveground arthropods, belowground insect larvae, and P. lanceolata molecular and chemical diversity. Including these trait-based measures of diversity allowed us to test whether or not they behaved similarly to the better studied species diversity. We used path analysis to determine whether compound indices detected more relationships between diversities of different organisms and traits than more basic indices. In the path models, more paths were significant when using H', even though all models except that with E were equally reliable. This demonstrates that while common diversity indices may appear interchangeable in simple analyses, when considering complex interactions, the choice of index can profoundly alter the interpretation of results. Data mining in order to identify the index producing the most significant results should be avoided, but simultaneously considering analyses using multiple indices can provide greater insight into the interactions in a system

Testing the paradox of enrichment along a land use gradient in a multitrophic aboveground and belowground community

In the light of ongoing land use changes, it is important to understand how multitrophic communities perform at different land use intensities. The paradox of enrichment predicts that fertilization leads to destabilization and extinction of predator-prey systems. We tested this prediction for a land use intensity gradient from natural to highly fertilized agricultural ecosystems. We included multiple aboveground and belowground trophic levels and land use-dependent searching efficiencies of insects. To overcome logistic constraints of field experiments, we used a successfully validated simulation model to investigate plant responses to removal of herbivores and their enemies. Consistent with our predictions, instability measured by herbivore-induced plant mortality increased with increasing land use intensity. Simultaneously, the balance between herbivores and natural enemies turned increasingly towards herbivore dominance and natural enemy failure. Under natural conditions, there were more frequently significant effects of belowground herbivores and their natural enemies on plant performance, whereas there were more aboveground effects in agroecosystems. This result was partly due to the “boom-bust” behavior of the shoot herbivore population. Plant responses to herbivore or natural enemy removal were much more abrupt than the imposed smooth land use intensity gradient. This may be due to the presence of multiple trophic levels aboveground and belowground. Our model suggests that destabilization and extinction are more likely to occur in agroecosystems than in natural communities, but the shape of the relationship is nonlinear under the influence of multiple trophic interactions.

High-resolution analysis of multi-copy variant surface glycoprotein gene expression sites in African trypanosomes

BACKGROUND: African trypanosomes cause lethal diseases in humans and animals and escape host immune attack by switching the expression of Variant Surface Glycoprotein (VSG) genes. The expressed VSGs are located at the ends of telomeric, polycistronic transcription units known as VSG expression sites (VSG-ESs). Each cell has many VSG-ESs but only one is transcribed in bloodstream-form parasites and all of them are inactive upon transmission to the insect vector mid-gut; a subset of monocistronic metacyclic VSG-ESs are then activated in the insect salivary gland. Deep-sequence analyses have been informative but assigning sequences to individual VSG-ESs has been challenging because they each contain closely related expression-site associated genes, or ESAGs, thought to contribute to virulence. RESULTS: We utilised ART, an in silico short read simulator to demonstrate the feasibility of accurately aligning reads to VSG-ESs. Then, using high-resolution transcriptomes from isogenic bloodstream and insect-stage Lister 427 Trypanosoma brucei, we uncover increased abundance in the insect mid-gut stage of mRNAs from metacyclic VSG-ESs and of mRNAs from the unusual ESAG, ESAG10. Further, we show that the silencing associated with allelic exclusion involves repression focussed at the ends of the VSG-ESs. We also use the approach to report relative fitness costs following ESAG RNAi from a genome-scale screen. CONCLUSIONS: By assigning sequences to individual VSG-ESs we provide new insights into VSG-ES transcription control, allelic exclusion and impacts on fitness. Thus, deeper insights into the expression and function of regulated multi-gene families are more accessible than previously anticipated. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-3154-8) contains supplementary material, which is available to authorized users