Local Thermometry of Neutral Modes on the Quantum Hall Edge

A system of electrons in two dimensions and strong magnetic fields can be tuned to create a gapped 2D system with one dimensional channels along the edge. Interactions among these edge modes can lead to independent transport of charge and heat, even in opposite directions. Measuring the chirality and transport properties of these charge and heat modes can reveal otherwise hidden structure in the edge. Here, we heat the outer edge of such a quantum Hall system using a quantum point contact. By placing quantum dots upstream and downstream along the edge of the heater, we can measure both the chemical potential and temperature of that edge to study charge and heat transport, respectively. We find that charge is transported exclusively downstream, but heat can be transported upstream when the edge has additional structure related to fractional quantum Hall physics.Comment: 24 pages, 18 figure

UNCLES: Method for the identification of genes differentially consistently co-expressed in a specific subset of datasets

Background: Collective analysis of the increasingly emerging gene expression datasets are required. The recently proposed binarisation of consensus partition matrices (Bi-CoPaM) method can combine clustering results from multiple datasets to identify the subsets of genes which are consistently co-expressed in all of the provided datasets in a tuneable manner. However, results validation and parameter setting are issues that complicate the design of such methods. Moreover, although it is a common practice to test methods by application to synthetic datasets, the mathematical models used to synthesise such datasets are usually based on approximations which may not always be sufficiently representative of real datasets. Results: Here, we propose an unsupervised method for the unification of clustering results from multiple datasets using external specifications (UNCLES). This method has the ability to identify the subsets of genes consistently co-expressed in a subset of datasets while being poorly co-expressed in another subset of datasets, and to identify the subsets of genes consistently co-expressed in all given datasets. We also propose the M-N scatter plots validation technique and adopt it to set the parameters of UNCLES, such as the number of clusters, automatically. Additionally, we propose an approach for the synthesis of gene expression datasets using real data profiles in a way which combines the ground-truth-knowledge of synthetic data and the realistic expression values of real data, and therefore overcomes the problem of faithfulness of synthetic expression data modelling. By application to those datasets, we validate UNCLES while comparing it with other conventional clustering methods, and of particular relevance, biclustering methods. We further validate UNCLES by application to a set of 14 real genome-wide yeast datasets as it produces focused clusters that conform well to known biological facts. Furthermore, in-silico-based hypotheses regarding the function of a few previously unknown genes in those focused clusters are drawn. Conclusions: The UNCLES method, the M-N scatter plots technique, and the expression data synthesis approach will have wide application for the comprehensive analysis of genomic and other sources of multiple complex biological datasets. Moreover, the derived in-silico-based biological hypotheses represent subjects for future functional studies.The National Institute for Health Research (NIHR) under its Programme Grants for Applied Research Programme (Grant Reference Number RP-PG-0310-1004)

The role of GPS-enabled information in transforming operational decision making: an exploratory study

Although the impact of ICT-enabled information on firm performance has been well documented in the business value of IT literature, our understanding of how Global Positioning System (GPS) adoption can transform operational decision making and foster differential firm performance is limited. In response, we conduct an exploratory comparative case study of three transport firms that have implemented the same GPS during the same year in their operations. Our results highlight that increased use of GPS-enabled information can enhance information quality and make operational decision making more fact-based and collaborative. We also find that such transformations in operational decision making, driven by increased use of GPS-enabled information, can foster differential performance impacts. However, we warn scholars and practitioners that a firm’s information management capability (in terms of availability of quality information in decision making, software tools for connectivity and access to information, IT systems integration post-GPS adoption and adaptability of the infrastructure to emerging business needs) and organizational factors (such as top management support, project management of GPS implementation, financial support, end-user involvement, rewarding, training and employee resistance) can facilitate (or inhibit) effective use of GPS-enabled information in operational decision making, and thus moderate differential performance benefits of GPS adoption

Schwann cell hamartoma: case report

<p>Abstract</p> <p>Background</p> <p>Colorectal polyps of mesenchymal origin represent a small percentage of gastrointestinal (GI) lesions. Nevertheless, they are encountered with increasing frequency since the widespread adoption of colonoscopy screening.</p> <p>Case presentation</p> <p>We report a case of a small colonic polyp that presented as intramucosal diffuse spindle cell proliferation with a benign cytological appearance, strong and diffuse immunoreactivity for S-100 protein, and pure Schwann cell phenotype. Careful morphological, immunohistochemical and clinical evaluation emphasize the differences from other stromal colonic lesions and distinguish it from schwannoma, a circumscribed benign nerve sheath tumor that rarely arises in the GI tract.</p> <p>Conclusion</p> <p>As recently proposed, this lesion was finally described as mucosal Schwann cell hamartoma.</p

Dynamic behavior analysis via structured rank minimization

Human behavior and affect is inherently a dynamic phenomenon involving temporal evolution of patterns manifested through a multiplicity of non-verbal behavioral cues including facial expressions, body postures and gestures, and vocal outbursts. A natural assumption for human behavior modeling is that a continuous-time characterization of behavior is the output of a linear time-invariant system when behavioral cues act as the input (e.g., continuous rather than discrete annotations of dimensional affect). Here we study the learning of such dynamical system under real-world conditions, namely in the presence of noisy behavioral cues descriptors and possibly unreliable annotations by employing structured rank minimization. To this end, a novel structured rank minimization method and its scalable variant are proposed. The generalizability of the proposed framework is demonstrated by conducting experiments on 3 distinct dynamic behavior analysis tasks, namely (i) conflict intensity prediction, (ii) prediction of valence and arousal, and (iii) tracklet matching. The attained results outperform those achieved by other state-of-the-art methods for these tasks and, hence, evidence the robustness and effectiveness of the proposed approach

Microarray-Based Maps of Copy-Number Variant Regions in European and Sub-Saharan Populations

The genetic basis of phenotypic variation can be partially explained by the presence of copy-number variations (CNVs). Currently available methods for CNV assessment include high-density single-nucleotide polymorphism (SNP) microarrays that have become an indispensable tool in genome-wide association studies (GWAS). However, insufficient concordance rates between different CNV assessment methods call for cautious interpretation of results from CNV-based genetic association studies. Here we provide a cross-population, microarray-based map of copy-number variant regions (CNVRs) to enable reliable interpretation of CNV association findings. We used the Affymetrix Genome-Wide Human SNP Array 6.0 to scan the genomes of 1167 individuals from two ethnically distinct populations (Europe, N = 717; Rwanda, N = 450). Three different CNV-finding algorithms were tested and compared for sensitivity, specificity, and feasibility. Two algorithms were subsequently used to construct CNVR maps, which were also validated by processing subsamples with additional microarray platforms (Illumina 1M-Duo BeadChip, Nimblegen 385K aCGH array) and by comparing our data with publicly available information. Both algorithms detected a total of 42669 CNVs, 74% of which clustered in 385 CNVRs of a cross-population map. These CNVRs overlap with 862 annotated genes and account for approximately 3.3% of the haploid human genome

Nicotine Promotes Tumor Growth and Metastasis in Mouse Models of Lung Cancer

Nicotine is the major addictive component of tobacco smoke. Although nicotine is generally thought to have limited ability to initiate cancer, it can induce cell proliferation and angiogenesis in a variety of systems. These properties might enable nicotine to facilitate the growth of tumors already initiated. Here we show that nicotine significantly promotes the progression and metastasis of tumors in mouse models of lung cancer. This effect was observed when nicotine was administered through intraperitoneal injections, or through over-the-counter transdermal patches.In the present study, Line1 mouse adenocarcinoma cells were implanted subcutaneously into syngenic BALB/c mice. Nicotine administration either by intraperitoneal (i.p.) injection or transdermal patches caused a remarkable increase in the size of implanted Line1 tumors. Once the tumors were surgically removed, nicotine treated mice had a markedly higher tumor recurrence (59.7%) as compared to the vehicle treated mice (19.5%). Nicotine also increased metastasis of dorsally implanted Line1 tumors to the lungs by 9 folds. These studies on transplanted tumors were extended to a mouse model where the tumors were induced by the tobacco carcinogen, NNK. Lung tumors were initiated in A/J mice by i.p. injection of NNK; administration of 1 mg/kg nicotine three times a week led to an increase in the size and the number of tumors formed in the lungs. In addition, nicotine significantly reduced the expression of epithelial markers, E-Cadherin and beta-Catenin as well as the tight junction protein ZO-1; these tumors also showed an increased expression of the alpha(7) nAChR subunit. We believe that exposure to nicotine either by tobacco smoke or nicotine supplements might facilitate increased tumor growth and metastasis.Our earlier results indicated that nicotine could induce invasion and epithelial-mesenchymal transition (EMT) in cultured lung, breast and pancreatic cancer cells. This study demonstrates for the first time that administration of nicotine either by i.p. injection or through over-the-counter dermal patches can promote tumor growth and metastasis in immunocompetent mice. These results suggest that while nicotine has only limited capacity to initiate tumor formation, it can facilitate the progression and metastasis of tumors pre-initiated by tobacco carcinogens

Dysregulated Nephrin in Diabetic Nephropathy of Type 2 Diabetes: A Cross Sectional Study

Podocyte specific proteins are dysregulated in diabetic nephropathy, though the extent of their expression loss is not identical and may be subject to different regulatory factors. Quantifying the degree of loss may help identify the most useful protein to use as an early biomarker of diabetic nephropathy.Protein expression of synaptopodin, podocin and nephrin were quantified in 15 Type 2 diabetic renal biopsies and 12 control patients. We found statistically significant downregulation of synaptopodin (P<0.0001), podocin (P = 0.0002), and nephrin (P<0.0001) in kidney biopsies of diabetic nephropathy as compared with controls. Urinary nephrin levels (nephrinuria) were then measured in 66 patients with Type 2 diabetes and 10 healthy controls by an enzyme-linked immunosorbent assay (Exocell, Philadelphia, PA). When divided into groups according to normo-, micro-, and macroalbuminuria, nephrinuria was found to be present in 100% of diabetic patients with micro- and macroalbuminuria, as well as 54% of patients with normoalbuminuria. Nephrinuria also correlated significantly with albuminuria (rho = 0.89, p<0.001), systolic blood pressure (rho = 0.32, p = 0.007), and correlated negatively with serum albumin (rho = -0.48, p<0.0001) and eGFR (rho = -0.33, p = 0.005).These data suggest that key podocyte-specific protein expressions are significantly and differentially downregulated in diabetic nephropathy. The finding that nephrinuria is observed in a majority of these normoalbuminuric patients demonstrates that it may precede microalbuminuria. If further research confirms nephrinuria to be a biomarker of pre-clinical diabetic nephropathy, it would shed light on podocyte metabolism in disease, and raise the possibility of new and earlier therapeutic targets