Sliding charge density wave in manganites

The so-called stripe phase of the manganites is an important example of the complex behaviour of metal oxides, and has long been interpreted as the localisation of charge at atomic sites. Here, we demonstrate via resistance measurements on La_{0.50}Ca_{0.50}MnO_3 that this state is in fact a prototypical charge density wave (CDW) which undergoes collective transport. Dramatic resistance hysteresis effects and broadband noise properties are observed, both of which are typical of sliding CDW systems. Moreover, the high levels of disorder typical of manganites result in behaviour similar to that of well-known disordered CDW materials. Our discovery that the manganite superstructure is a CDW shows that unusual transport and structural properties do not require exotic physics, but can emerge when a well-understood phase (the CDW) coexists with disorder.Comment: 13 pages; 4 figure

A Unifying Framework for Evaluating the Predictive Power of Genetic Variants Based on the Level of Heritability Explained

An increasing number of genetic variants have been identified for many complex diseases. However, it is controversial whether risk prediction based on genomic profiles will be useful clinically. Appropriate statistical measures to evaluate the performance of genetic risk prediction models are required. Previous studies have mainly focused on the use of the area under the receiver operating characteristic (ROC) curve, or AUC, to judge the predictive value of genetic tests. However, AUC has its limitations and should be complemented by other measures. In this study, we develop a novel unifying statistical framework that connects a large variety of predictive indices together. We showed that, given the overall disease probability and the level of variance in total liability (or heritability) explained by the genetic variants, we can estimate analytically a large variety of prediction metrics, for example the AUC, the mean risk difference between cases and non-cases, the net reclassification improvement (ability to reclassify people into high- and low-risk categories), the proportion of cases explained by a specific percentile of population at the highest risk, the variance of predicted risks, and the risk at any percentile. We also demonstrate how to construct graphs to visualize the performance of risk models, such as the ROC curve, the density of risks, and the predictiveness curve (disease risk plotted against risk percentile). The results from simulations match very well with our theoretical estimates. Finally we apply the methodology to nine complex diseases, evaluating the predictive power of genetic tests based on known susceptibility variants for each trait

Interpreting systematic reviews: are we ready to make our own conclusions? A cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Independent evaluation of clinical evidence is advocated in evidence-based medicine (EBM). However, authors' conclusions are often appealing for readers who look for quick messages. We assessed how well a group of Malaysian hospital practitioners and medical students derived their own conclusions from systematic reviews (SRs) and to what extent these were influenced by their prior beliefs and the direction of the study results.</p> <p>Methods</p> <p>We conducted two cross-sectional studies: one with hospital practitioners (<it>n </it>= 150) attending an EBM course in June 2008 in a tertiary hospital and one with final-year medical students (<it>n </it>= 35) in November 2008. We showed our participants four Cochrane SR abstracts without the authors' conclusions. For each article, the participants chose a conclusion from among six options comprising different combinations of the direction of effect and the strength of the evidence. We predetermined the single option that best reflected the actual authors' conclusions and labelled this as our best conclusion. We compared the participants' choices with our predetermined best conclusions. Two chosen reviews demonstrated that the intervention was beneficial ("positive"), and two others did not ("negative"). We also asked the participants their prior beliefs about the intervention.</p> <p>Results</p> <p>Overall, 60.3% correctly identified the direction of effect, and 30.1% chose the best conclusions, having identified both the direction of effect and the strength of evidence. More students (48.2%) than practitioners (22.2%) chose the best conclusions (<it>P </it>< 0.001). Fewer than one-half (47%) correctly identified the direction of effect against their prior beliefs. "Positive" SRs were more likely than "negative" SRs to change the participants' beliefs about the effect of the intervention (relative risk (RR) 1.8, 95% confidence interval 1.3 to 2.6) and "convert" those who were previously unsure by making them choose the appropriate direction of effect (RR 1.9, 95% confidence interval 1.3 to 2.8).</p> <p>Conclusions</p> <p>The majority of our participants could not generate appropriate conclusions from SRs independently. Judicious direction from the authors' conclusions still appears crucial to guiding our health care practitioners in identifying appropriate messages from research. Authors, editors and reviewers should ensure that the conclusions of a paper accurately reflect the results. Similar studies should be conducted in other settings where awareness and application of EBM are different.</p> <p>Please see Commentary: <url>http://www.biomedcentral.com/1741-7015/9/31/</url>.</p

Unambiguous molecular detections with multiple genetic approach for the complicated chromosome 22q11 deletion syndrome

<p>Abstract</p> <p>Background</p> <p>Chromosome 22q11 deletion syndrome (22q11DS) causes a developmental disorder during the embryonic stage, usually because of hemizygous deletions. The clinical pictures of patients with 22q11DS vary because of polymorphisms: on average, approximately 93% of affected individuals have a de novo deletion of 22q11, and the rest have inherited the same deletion from a parent. Methods using multiple genetic markers are thus important for the accurate detection of these microdeletions.</p> <p>Methods</p> <p>We studied 12 babies suspected to carry 22q11DS and 18 age-matched healthy controls from unrelated Taiwanese families. We determined genomic variance using microarray-based comparative genomic hybridization (array-CGH), quantitative real-time polymerase chain reaction (qPCR) and multiplex ligation-dependent probe amplification (MLPA).</p> <p>Results</p> <p>Changes in genomic copy number were significantly associated with clinical manifestations for the classical criteria of 22q11DS using MPLA and qPCR (<it>p </it>< 0.01). An identical deletion was shown in three affected infants by MLPA. These reduced DNA dosages were also obtained partially using array-CGH and confirmed by qPCR but with some differences in deletion size.</p> <p>Conclusion</p> <p>Both MLPA and qPCR could produce a clearly defined range of deleted genomic DNA, whereas there must be a deleted genome that is not distinguishable using MLPA. These data demonstrate that such multiple genetic approaches are necessary for the unambiguous molecular detection of these types of complicated genomic syndromes.</p

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

Nitroxyl (HNO) Stimulates Soluble Guanylyl Cyclase to Suppress Cardiomyocyte Hypertrophy and Superoxide Generation

Background: New therapeutic targets for cardiac hypertrophy, an independent risk factor for heart failure and death, are essential. HNO is a novel redox sibling of NON attracting considerable attention for the treatment of cardiovascular disorders, eliciting cGMP-dependent vasodilatation yet cGMP-independent positive inotropy. The impact of HNO on cardiac hypertrophy (which is negatively regulated by cGMP) however has not been investigated. Methods: Neonatal rat cardiomyocytes were incubated with angiotensin II (Ang II) in the presence and absence of the HNO donor Angeli’s salt (sodium trioxodinitrate) or B-type natriuretic peptide, BNP (all 1 mmol/L). Hypertrophic responses and its triggers, as well as cGMP signaling, were determined. Results: We now demonstrate that Angeli’s salt inhibits Ang II-induced hypertrophic responses in cardiomyocytes, including increases in cardiomyocyte size, de novo protein synthesis and b-myosin heavy chain expression. Angeli’s salt also suppresses Ang II induction of key triggers of the cardiomyocyte hypertrophic response, including NADPH oxidase (on both Nox2 expression and superoxide generation), as well as p38 mitogen-activated protein kinase (p38MAPK). The antihypertrophic, superoxide-suppressing and cGMP-elevating effects of Angeli’s salt were mimicked by BNP. We also demonstrate that the effects of Angeli’s salt are specifically mediated by HNO (with no role for NON or nitrite), with subsequent activation of cardiomyocyte soluble guanylyl cyclase (sGC) and cGMP signaling (on both cGMP-dependen

The Hubbard model within the equations of motion approach

The Hubbard model has a special role in Condensed Matter Theory as it is considered as the simplest Hamiltonian model one can write in order to describe anomalous physical properties of some class of real materials. Unfortunately, this model is not exactly solved except for some limits and therefore one should resort to analytical methods, like the Equations of Motion Approach, or to numerical techniques in order to attain a description of its relevant features in the whole range of physical parameters (interaction, filling and temperature). In this manuscript, the Composite Operator Method, which exploits the above mentioned analytical technique, is presented and systematically applied in order to get information about the behavior of all relevant properties of the model (local, thermodynamic, single- and two- particle ones) in comparison with many other analytical techniques, the above cited known limits and numerical simulations. Within this approach, the Hubbard model is shown to be also capable to describe some anomalous behaviors of the cuprate superconductors.Comment: 232 pages, more than 300 figures, more than 500 reference

Structure-Based Rational Design of a Toll-like Receptor 4 (TLR4) Decoy Receptor with High Binding Affinity for a Target Protein

Repeat proteins are increasingly attracting much attention as alternative scaffolds to immunoglobulin antibodies due to their unique structural features. Nonetheless, engineering interaction interface and understanding molecular basis for affinity maturation of repeat proteins still remain a challenge. Here, we present a structure-based rational design of a repeat protein with high binding affinity for a target protein. As a model repeat protein, a Toll-like receptor4 (TLR4) decoy receptor composed of leucine-rich repeat (LRR) modules was used, and its interaction interface was rationally engineered to increase the binding affinity for myeloid differentiation protein 2 (MD2). Based on the complex crystal structure of the decoy receptor with MD2, we first designed single amino acid substitutions in the decoy receptor, and obtained three variants showing a binding affinity (KD) one-order of magnitude higher than the wild-type decoy receptor. The interacting modes and contributions of individual residues were elucidated by analyzing the crystal structures of the single variants. To further increase the binding affinity, single positive mutations were combined, and two double mutants were shown to have about 3000- and 565-fold higher binding affinities than the wild-type decoy receptor. Molecular dynamics simulations and energetic analysis indicate that an additive effect by two mutations occurring at nearby modules was the major contributor to the remarkable increase in the binding affinities