Coexistence of Magnetic Order and Two-dimensional Superconductivity at LaAlO3_3/SrTiO3_3 Interfaces

A two dimensional electronic system with novel electronic properties forms at the interface between the insulators LaAlO$_3$ and SrTiO$_3$. Samples fabricated until now have been found to be either magnetic or superconducting, depending on growth conditions. We combine transport measurements with high-resolution magnetic torque magnetometry and report here evidence of magnetic ordering of the two-dimensional electron liquid at the interface. The magnetic ordering exists from well below the superconducting transition to up to 200 K, and is characterized by an in-plane magnetic moment. Our results suggest that there is either phase separation or coexistence between magnetic and superconducting states. The coexistence scenario would point to an unconventional superconducting phase in the ground state.Comment: 10 pages, 4 figure

Direct observation of incommensurate magnetism in Hubbard chains

The interplay between magnetism and doping is at the origin of exotic strongly correlated electronic phases and can lead to novel forms of magnetic ordering. One example is the emergence of incommensurate spin-density waves with a wave vector that does not match the reciprocal lattice. In one dimension this effect is a hallmark of Luttinger liquid theory, which also describes the low energy physics of the Hubbard model. Here we use a quantum simulator based on ultracold fermions in an optical lattice to directly observe such incommensurate spin correlations in doped and spin-imbalanced Hubbard chains using fully spin and density resolved quantum gas microscopy. Doping is found to induce a linear change of the spin-density wave vector in excellent agreement with Luttinger theory predictions. For non-zero polarization we observe a decrease of the wave vector with magnetization as expected from the Heisenberg model in a magnetic field. We trace the microscopic origin of these incommensurate correlations to holes, doublons and excess spins which act as delocalized domain walls for the antiferromagnetic order. Finally, when inducing interchain coupling we observe fundamentally different spin correlations around doublons indicating the formation of a magnetic polaron

Exploring forest structural complexity by multi-scale segmentation of VHR imagery

Forests are complex ecological systems, characterised by multiple-scale structural and dynamical patterns which are not inferable from a system description that spans only a narrow window of resolution; this makes their investigation a difficult task using standard field sampling protocols. We segment a QuickBird image covering a beech forest in an initial stage of old-growthness – showing, accordingly, a good degree of structural complexity – into three segmentation levels. We apply field-based diversity indices of tree size, spacing, species assemblage to quantify structural heterogeneity amongst forest regions delineated by segmentation. The aim of the study is to evaluate, on a statistical basis, the relationships between spectrally delineated image segments and observed spatial heterogeneity in forest structure, including gaps in the outer canopy. Results show that: some 45% of the segments generated at the coarser segmentation scale (level 1) are surrounded by structurally different neighbours; level 2 segments distinguish spatial heterogeneity in forest structure in about 63% of level 1 segments; level 3 image segments detect better canopy gaps, rather than differences in the spatial pattern of the investigated structural indices. Results support also the idea of a mixture of macro and micro structural heterogeneity within the beech forest: large size populations of trees homogeneous for the examined structural indices at the coarser segmentation level, when analysed at a finer scale, are internally heterogeneous; and vice versa. Findings from this study demonstrate that multiresolution segmentation is able to delineate scale-dependent patterns of forest structural heterogeneity, even in an initial stage of old-growth structural differentiation. This tool has therefore a potential to improve the sampling design of field surveys aimed at characterizing forest structural complexity across multiple spatio-temporal scales.L'articolo è disponibile sul sito dell'editore www.sciencedirect.co

Breast cancer oestrogen independence mediated by BCAR1 or BCAR3 genes is transmitted through mechanisms distinct from the oestrogen receptor signalling pathway or the epidermal growth factor receptor signalling pathway

INTRODUCTION: Tamoxifen is effective for endocrine treatment of oestrogen receptor-positive breast cancers but ultimately fails due to the development of resistance. A functional screen in human breast cancer cells identified two BCAR genes causing oestrogen-independent proliferation. The BCAR1 and BCAR3 genes both encode components of intracellular signal transduction, but their direct effect on breast cancer cell proliferation is not known. The aim of this study was to investigate the growth control mediated by these BCAR genes by gene expression profiling. METHODS: We have measured the expression changes induced by overexpression of the BCAR1 or BCAR3 gene in ZR-75-1 cells and have made direct comparisons with the expression changes after cell stimulation with oestrogen or epidermal growth factor (EGF). A comparison with published gene expression data of cell models and breast tumours is made. RESULTS: Relatively few changes in gene expression were detected in the BCAR-transfected cells, in comparison with the extensive and distinct differences in gene expression induced by oestrogen or EGF. Both BCAR1 and BCAR3 regulate discrete sets of genes in these ZR-75-1-derived cells, indicating that the proliferation signalling proceeds along distinct pathways. Oestrogen-regulated genes in our cell model showed general concordance with reported data of cell models and gene expression association with oestrogen receptor status of breast tumours. CONCLUSIONS: The direct comparison of the expression profiles of BCAR transfectants and oestrogen or EGF-stimulated cells strongly suggests that anti-oestrogen-resistant cell proliferation is not caused by alternative activation of the oestrogen receptor or by the epidermal growth factor receptor signalling pathway

A qualitative study of health care professionals' views and experiences of paediatric advance care planning

Background Good end-of-life care planning is vital to ensure optimal care is provided for patients and their families. Two key factors are open and honest advance care planning conversations between the patient (where possible), family, and health care professionals, focusing on exploring what their future wishes are; and the development of an advance care plan document. However, in paediatric and neonatal settings, there has been little research to demonstrate how advance care planning conversations take place. This study explored health care professionals’ views and experiences of paediatric advance care planning in hospitals, community settings and hospices. MethodsA qualitative methodology was employed using purposive sampling of health care professionals involved in the end-of-life care for children aged 0–18 years known to the hospital palliative care team, and had died at least three months before, but less than 18 months prior to the study. Ethics committee approval was obtained for the study. Located in the North of England, the study involved three hospitals, a children’s hospice, and community services. Data were collected using semi-structured, digitally recorded, telephone interviews. All interviews were transcribed verbatim and subjected to thematic analysis. ResultsTwenty-one health care professionals participated, including generalist paediatric staff as well as specialist palliative care staff.Two themes were generated from the study: The timing of planning conversations, including waiting for the relationship with the family to form; the introduction of parallel planning; avoiding a crisis situation. Secondly, supporting effective conversations around advance care planning, including where to have the conversation; introducing the conversation; and how to approach the topic encompassing the value of advance care planning and documentation for families. Conclusion The timing of when to start the advance care planning conversations remains an issue for health care professionals. The value of doing it in stages and considering the environment where the conversations are held was noted. Timely planning was seen as vital to avoid difficult conversations at a crisis point and for co-ordination of care. Good advance care planning is to provide the best person-centred care for the child and experience for the family

Query Large Scale Microarray Compendium Datasets Using a Model-Based Bayesian Approach with Variable Selection

In microarray gene expression data analysis, it is often of interest to identify genes that share similar expression profiles with a particular gene such as a key regulatory protein. Multiple studies have been conducted using various correlation measures to identify co-expressed genes. While working well for small datasets, the heterogeneity introduced from increased sample size inevitably reduces the sensitivity and specificity of these approaches. This is because most co-expression relationships do not extend to all experimental conditions. With the rapid increase in the size of microarray datasets, identifying functionally related genes from large and diverse microarray gene expression datasets is a key challenge. We develop a model-based gene expression query algorithm built under the Bayesian model selection framework. It is capable of detecting co-expression profiles under a subset of samples/experimental conditions. In addition, it allows linearly transformed expression patterns to be recognized and is robust against sporadic outliers in the data. Both features are critically important for increasing the power of identifying co-expressed genes in large scale gene expression datasets. Our simulation studies suggest that this method outperforms existing correlation coefficients or mutual information-based query tools. When we apply this new method to the Escherichia coli microarray compendium data, it identifies a majority of known regulons as well as novel potential target genes of numerous key transcription factors

Misty Mountain clustering: application to fast unsupervised flow cytometry gating

<p>Abstract</p> <p>Background</p> <p>There are many important clustering questions in computational biology for which no satisfactory method exists. Automated clustering algorithms, when applied to large, multidimensional datasets, such as flow cytometry data, prove unsatisfactory in terms of speed, problems with local minima or cluster shape bias. Model-based approaches are restricted by the assumptions of the fitting functions. Furthermore, model based clustering requires serial clustering for all cluster numbers within a user defined interval. The final cluster number is then selected by various criteria. These supervised serial clustering methods are time consuming and frequently different criteria result in different optimal cluster numbers. Various unsupervised heuristic approaches that have been developed such as affinity propagation are too expensive to be applied to datasets on the order of 10⁶points that are often generated by high throughput experiments.</p> <p>Results</p> <p>To circumvent these limitations, we developed a new, unsupervised density contour clustering algorithm, called Misty Mountain, that is based on percolation theory and that efficiently analyzes large data sets. The approach can be envisioned as a progressive top-down removal of clouds covering a data histogram relief map to identify clusters by the appearance of statistically distinct peaks and ridges. This is a parallel clustering method that finds every cluster after analyzing only once the cross sections of the histogram. The overall run time for the composite steps of the algorithm increases linearly by the number of data points. The clustering of 10⁶data points in 2D data space takes place within about 15 seconds on a standard laptop PC. Comparison of the performance of this algorithm with other state of the art automated flow cytometry gating methods indicate that Misty Mountain provides substantial improvements in both run time and in the accuracy of cluster assignment.</p> <p>Conclusions</p> <p>Misty Mountain is fast, unbiased for cluster shape, identifies stable clusters and is robust to noise. It provides a useful, general solution for multidimensional clustering problems. We demonstrate its suitability for automated gating of flow cytometry data.</p