Topological Homogeneity for Electron Microscopy Images

In this paper, the concept of homogeneity is defined, from a topological perspective, in order to analyze how uniform is the material composition in 2D electron microscopy images. Topological multiresolution parameters are taken into account to obtain better results than classical techniques.Ministerio de Economía y Competitividad MTM2016-81030-PMinisterio de Economía y Competitividad TEC2012-37868-C04-0

Charge 4e4e superconductivity from pair density wave order in certain high temperature superconductors

A number of spectacular experimental anomalies\cite{li-2007,fujita-2005} have recently been discovered in certain cuprates, notably {\LBCO} and {\LNSCO}, which exhibit unidirectional spin and charge order (known as ``stripe order''). We have recently proposed to interpret these observations as evidence for a novel ``striped superconducting'' state, in which the superconducting order parameter is modulated in space, such that its average is precisely zero. Here, we show that thermal melting of the striped superconducting state can lead to a number of unusual phases, of which the most novel is a charge $4e$ superconducting state, with a corresponding fractional flux quantum $hc/4e$. These are never-before observed states of matter, and ones, moreover, that cannot arise from the conventional Bardeen-Cooper-Schrieffer (BCS) mechanism. Thus, direct confirmation of their existence, even in a small subset of the cuprates, could have much broader implications for our understanding of high temperature superconductivity. We propose experiments to observe fractional flux quantization, which thereby could confirm the existence of these states.Comment: 5 pages, 2 figures; new version in Nature Physics format with a discussion of the effective Josephson coupling J2 and minor changes. Mildly edited abstract. v3: corrected versio

A one-year trial of lamivudine for chronic hepatitis B

Background and Methods: In preliminary trials, lamivudine, an oral nucleoside analogue, has shown promise for the treatment of chronic hepatitis B. We conducted a one-year double-blind trial of lamivudine in 358 Chinese patients with chronic hepatitis B. The patients were randomly assigned to receive 25 mg of lamivudine (142 patients), 100 mg of lamivudine (143), or placebo (73) orally once daily. The patients underwent liver biopsies before entering the study and after completing the assigned treatment regimen. The primary end point was a reduction of at least two points in the Knodell necroinflammatory score. Results: Hepatic necroinflammatory activity improved by two points or more in 56 percent of the patients receiving 100 mg of lamivudine, 49 percent of those receiving 25 mg of lamivudine, and 25 percent of those receiving placebo (P<0.001 and P=0.001, respectively, for the comparisons of lamivudine treatment with placebo). Necroinflammatory activity worsened in 7 percent of the patients receiving 100 mg of lamivudine, 8 percent of those receiving 25 mg, and 26 percent of those receiving placebo. The 100mg dose of lamivudine was associated with a reduced progression of fibrosis (P=0.01 for the comparison with placebo) and with the highest rate of hepatitis B e antigen (HBeAg) seroconversion (loss of HBeAg, development of antibody to HBeAg, and undetectable HBV DNA) (16 percent), the greatest suppression of HBV DNA (98 percent reduction at week 52 as compared with the base-line value), and the highest rate of sustained normalization of alanine aminotransferase levels (72 percent). Ninety-six percent of the patients completed the study. The incidence of adverse events was similar in all groups, and there were few serious events. Conclusions: In a one-year study, lamivudine was associated with substantial histologic improvement in many patients with chronic hepatitis B. A daily dose of 100 mg was more effective than a daily dose of 25 mg.published_or_final_versio

A new concept for the combination of optical interferometers and high-resolution spectrographs

The combination of high spatial and spectral resolution in optical astronomy enables new observational approaches to many open problems in stellar and circumstellar astrophysics. However, constructing a high-resolution spectrograph for an interferometer is a costly and time-intensive undertaking. Our aim is to show that, by coupling existing high-resolution spectrographs to existing interferometers, one could observe in the domain of high spectral and spatial resolution, and avoid the construction of a new complex and expensive instrument. We investigate in this article the different challenges which arise from combining an interferometer with a high-resolution spectrograph. The requirements for the different sub-systems are determined, with special attention given to the problems of fringe tracking and dispersion. A concept study for the combination of the VLTI (Very Large Telescope Interferometer) with UVES (UV-Visual Echelle Spectrograph) is carried out, and several other specific instrument pairings are discussed. We show that the proposed combination of an interferometer with a high-resolution spectrograph is indeed feasible with current technology, for a fraction of the cost of building a whole new spectrograph. The impact on the existing instruments and their ongoing programs would be minimal.Comment: 27 pages, 9 figures, Experimental Astronomy; v2: accepted versio

Early malaria resurgence in pre-elimination areas in Kokap Subdistrict, Kulon Progo, Indonesia

BACKGROUND: Indonesia is among those countries committed to malaria eradication, with a continuously decreasing incidence of malaria. However, at district level the situation is different. This study presents a case of malaria resurgence Kokap Subdistrict of the Kulon Progo District in Yogyakarta Province, Java after five years of low endemicity. This study also aims to describe the community perceptions and health services delivery situation that contribute to this case. METHODS: All malaria cases (2007–2011) in Kulon Progo District were stratified to annual parasite incidence (API). Two-hundred and twenty-six cases during an outbreak (May 2011 to April 2012) were geocoded by household addresses using a geographic information system (GIS) technique and clusters were identified by SaTScan software analysis (Arc GIS 10.1). Purposive random sampling was conducted on respondents living inside the clusters to identify community perceptions and behaviour related to malaria. Interviews were conducted with malaria health officers to understand the challenges of malaria surveillance and control. RESULTS: After experiencing three consecutive years with API less than 1 per thousand, malaria in Kokap subdistrict increased almost ten times higher than API in the district level and five times higher than national API. Malaria cases were found in all five villages in 2012. One primary and two secondary malaria clusters in Hargotirto and Kalirejo villages were identified during the 2011–2012 outbreak. Most of the respondents were positively aware with malaria signs and activities of health workers to prevent malaria, although some social economic activities could not be hindered. Return transmigrants or migrant workers entering to their villages, reduced numbers of village malaria workers and a surge in malaria cases in the neighbouring district contributed to the resurgence. CONCLUSION: Community perception, awareness and participation could constitute a solid foundation for malaria elimination in Kokap. However, decreasing number of village malaria workers and ineffective communication between primary health centres (PHCs) within boundary areas with similar malaria problems needs attention. Decentralization policy was allegedly the reason for the less integrated malaria control between districts, especially in the cross border areas. Malaria resurgence needs attention particularly when it occurs in an area that is entering the elimination phase

A Bayesian method for evaluating and discovering disease loci associations

Background: A genome-wide association study (GWAS) typically involves examining representative SNPs in individuals from some population. A GWAS data set can concern a million SNPs and may soon concern billions. Researchers investigate the association of each SNP individually with a disease, and it is becoming increasingly commonplace to also analyze multi-SNP associations. Techniques for handling so many hypotheses include the Bonferroni correction and recently developed Bayesian methods. These methods can encounter problems. Most importantly, they are not applicable to a complex multi-locus hypothesis which has several competing hypotheses rather than only a null hypothesis. A method that computes the posterior probability of complex hypotheses is a pressing need. Methodology/Findings: We introduce the Bayesian network posterior probability (BNPP) method which addresses the difficulties. The method represents the relationship between a disease and SNPs using a directed acyclic graph (DAG) model, and computes the likelihood of such models using a Bayesian network scoring criterion. The posterior probability of a hypothesis is computed based on the likelihoods of all competing hypotheses. The BNPP can not only be used to evaluate a hypothesis that has previously been discovered or suspected, but also to discover new disease loci associations. The results of experiments using simulated and real data sets are presented. Our results concerning simulated data sets indicate that the BNPP exhibits both better evaluation and discovery performance than does a p-value based method. For the real data sets, previous findings in the literature are confirmed and additional findings are found. Conclusions/Significance: We conclude that the BNPP resolves a pressing problem by providing a way to compute the posterior probability of complex multi-locus hypotheses. A researcher can use the BNPP to determine the expected utility of investigating a hypothesis further. Furthermore, we conclude that the BNPP is a promising method for discovering disease loci associations. © 2011 Jiang et al

MCL-CAw: A refinement of MCL for detecting yeast complexes from weighted PPI networks by incorporating core-attachment structure

Abstract Background The reconstruction of protein complexes from the physical interactome of organisms serves as a building block towards understanding the higher level organization of the cell. Over the past few years, several independent high-throughput experiments have helped to catalogue enormous amount of physical protein interaction data from organisms such as yeast. However, these individual datasets show lack of correlation with each other and also contain substantial number of false positives (noise). Over these years, several affinity scoring schemes have also been devised to improve the qualities of these datasets. Therefore, the challenge now is to detect meaningful as well as novel complexes from protein interaction (PPI) networks derived by combining datasets from multiple sources and by making use of these affinity scoring schemes. In the attempt towards tackling this challenge, the Markov Clustering algorithm (MCL) has proved to be a popular and reasonably successful method, mainly due to its scalability, robustness, and ability to work on scored (weighted) networks. However, MCL produces many noisy clusters, which either do not match known complexes or have additional proteins that reduce the accuracies of correctly predicted complexes. Results Inspired by recent experimental observations by Gavin and colleagues on the modularity structure in yeast complexes and the distinctive properties of "core" and "attachment" proteins, we develop a core-attachment based refinement method coupled to MCL for reconstruction of yeast complexes from scored (weighted) PPI networks. We combine physical interactions from two recent "pull-down" experiments to generate an unscored PPI network. We then score this network using available affinity scoring schemes to generate multiple scored PPI networks. The evaluation of our method (called MCL-CAw) on these networks shows that: (i) MCL-CAw derives larger number of yeast complexes and with better accuracies than MCL, particularly in the presence of natural noise; (ii) Affinity scoring can effectively reduce the impact of noise on MCL-CAw and thereby improve the quality (precision and recall) of its predicted complexes; (iii) MCL-CAw responds well to most available scoring schemes. We discuss several instances where MCL-CAw was successful in deriving meaningful complexes, and where it missed a few proteins or whole complexes due to affinity scoring of the networks. We compare MCL-CAw with several recent complex detection algorithms on unscored and scored networks, and assess the relative performance of the algorithms on these networks. Further, we study the impact of augmenting physical datasets with computationally inferred interactions for complex detection. Finally, we analyse the essentiality of proteins within predicted complexes to understand a possible correlation between protein essentiality and their ability to form complexes. Conclusions We demonstrate that core-attachment based refinement in MCL-CAw improves the predictions of MCL on yeast PPI networks. We show that affinity scoring improves the performance of MCL-CAw.http://deepblue.lib.umich.edu/bitstream/2027.42/78256/1/1471-2105-11-504.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/2/1471-2105-11-504-S1.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/3/1471-2105-11-504-S2.ZIPhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/4/1471-2105-11-504.pdfPeer Reviewe

Proteomics: in pursuit of effective traumatic brain injury therapeutics

Effective traumatic brain injury (TBI) therapeutics remain stubbornly elusive. Efforts in the field have been challenged by the heterogeneity of clinical TBI, with greater complexity among underlying molecular phenotypes than initially conceived. Future research must confront the multitude of factors comprising this heterogeneity, representing a big data challenge befitting the coming informatics age. Proteomics is poised to serve a central role in prescriptive therapeutic development, as it offers an efficient endpoint within which to assess post-TBI biochemistry. We examine rationale for multifactor TBI proteomic studies and the particular importance of temporal profiling in defining biochemical sequences and guiding therapeutic development. Lastly, we offer perspective on repurposing biofluid proteomics to develop theragnostic assays with which to prescribe, monitor and assess pharmaceutics for improved translation and outcome for TBI patients

Anti-epileptic effect of Ganoderma lucidum polysaccharides by inhibition of intracellular calcium accumulation and stimulation of expression of CaMKII a in epileptic hippocampal neurons

Purpose: To investigate the mechanism of the anti-epileptic effect of Ganoderma lucidum polysaccharides (GLP), the changes of intracellular calcium and CaMK II a expression in a model of epileptic neurons were investigated. Method: Primary hippocampal neurons were divided into: 1) Control group, neurons were cultured with Neurobasal medium, for 3 hours; 2) Model group I: neurons were incubated with Mg2+ free medium for 3 hours; 3) Model group II: neurons were incubated with Mg2+ free medium for 3 hours then cultured with the normal medium for a further 3 hours; 4) GLP group I: neurons were incubated with Mg2+ free medium containing GLP (0.375 mg/ml) for 3 hours; 5) GLP group II: neurons were incubated with Mg2+ free medium for 3 hours then cultured with a normal culture medium containing GLP for a further 3 hours. The CaMK II a protein expression was assessed by Western-blot. Ca2+ turnover in neurons was assessed using Fluo-3/AM which was added into the replacement medium and Ca2+ turnover was observed under a laser scanning confocal microscope. Results: The CaMK II a expression in the model groups was less than in the control groups, however, in the GLP groups, it was higher than that observed in the model group. Ca2+ fluorescence intensity in GLP group I was significantly lower than that in model group I after 30 seconds, while in GLP group II, it was reduced significantly compared to model group II after 5 minutes. Conclusion: GLP may inhibit calcium overload and promote CaMK II a expression to protect epileptic neuron

Study protocol to investigate the effect of a lifestyle intervention on body weight, psychological health status and risk factors associated with disease recurrence in women recovering from breast cancer treatment

Background Breast cancer survivors often encounter physiological and psychological problems related to their diagnosis and treatment that can influence long-term prognosis. The aim of this research is to investigate the effects of a lifestyle intervention on body weight and psychological well-being in women recovering from breast cancer treatment, and to determine the relationship between changes in these variables and biomarkers associated with disease recurrence and survival. Methods/design Following ethical approval, a total of 100 patients will be randomly assigned to a lifestyle intervention (incorporating dietary energy restriction in conjunction with aerobic exercise training) or normal care control group. Patients randomised to the dietary and exercise intervention will be given individualised healthy eating dietary advice and written information and attend moderate intensity aerobic exercise sessions on three to five days per week for a period of 24 weeks. The aim of this strategy is to induce a steady weight loss of up to 0.5 Kg each week. In addition, the overall quality of the diet will be examined with a view to (i) reducing the dietary intake of fat to ~25% of the total calories, (ii) eating at least 5 portions of fruit and vegetables a day, (iii) increasing the intake of fibre and reducing refined carbohydrates, and (iv) taking moderate amounts of alcohol. Outcome measures will include body weight and body composition, psychological health status (stress and depression), cardiorespiratory fitness and quality of life. In addition, biomarkers associated with disease recurrence, including stress hormones, estrogen status, inflammatory markers and indices of innate and adaptive immune function will be monitored. Discussion This research will provide valuable information on the effectiveness of a practical, easily implemented lifestyle intervention for evoking positive effects on body weight and psychological well-being, two important factors that can influence long-term prognosis in breast cancer survivors. However, the added value of the study is that it will also evaluate the effects of the lifestyle intervention on a range of biomarkers associated with disease recurrence and survival. Considered together, the results should improve our understanding of the potential role that lifestyle-modifiable factors could play in saving or prolonging lives