80 research outputs found

    Spectral Methods from Tensor Networks

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    A tensor network is a diagram that specifies a way to "multiply" a collection of tensors together to produce another tensor (or matrix). Many existing algorithms for tensor problems (such as tensor decomposition and tensor PCA), although they are not presented this way, can be viewed as spectral methods on matrices built from simple tensor networks. In this work we leverage the full power of this abstraction to design new algorithms for certain continuous tensor decomposition problems. An important and challenging family of tensor problems comes from orbit recovery, a class of inference problems involving group actions (inspired by applications such as cryo-electron microscopy). Orbit recovery problems over finite groups can often be solved via standard tensor methods. However, for infinite groups, no general algorithms are known. We give a new spectral algorithm based on tensor networks for one such problem: continuous multi-reference alignment over the infinite group SO(2). Our algorithm extends to the more general heterogeneous case.Comment: 30 pages, 8 figure

    Investigation of the 6He cluster structures

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    The 4He+2n and t+t clustering of the 6He ground state were investigated by means of the transfer reaction 6He(p,t)4He at 25 MeV/nucleon. The experiment was performed in inverse kinematics at GANIL with the SPEG spectrometer coupled to the MUST array. Experimental data for the transfer reaction were analyzed by a DWBA calculation including the two neutrons and the triton transfer. The couplings to the 6He --> 4He + 2n breakup channels were taken into account with a polarization potential deduced from a coupled-discretized-continuum channels analysis of the 6He+1H elastic scattering measured at the same time. The influence on the calculations of the 4He+t exit potential and of the triton sequential transfer is discussed. The final calculation gives a spectroscopic factor close to one for the 4He+2n configuration as expected. The spectroscopic factor obtained for the t+t configuration is much smaller than the theoretical predictions.Comment: 10 pages, 11 figures, accepted in PR

    Genomic characterization of individuals presenting extreme phenotypes of high and low risk to develop tobacco-induced lung cancer

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    Single nucleotide polymorphisms (SNPs) may modulate individual susceptibility to carcinogens. We designed a genome-wide association study to characterize individuals presenting extreme phenotypes of high and low risk to develop tobacco-induced non-small cell lung cancer (NSCLC), and we validated our results. We hypothesized that this strategy would enrich the frequencies of the alleles that contribute to the observed traits. We genotyped 2.37 million SNPs in 95 extreme phenotype individuals, that is: heavy smokers that either developed NSCLC at an early age (extreme cases); or did not present NSCLC at an advanced age (extreme controls), selected from a discovery set (n=3631). We validated significant SNPs in 133 additional subjects with extreme phenotypes selected from databases including >39,000 individuals. Two SNPs were validated: rs12660420 (p(combined)=5.66x10(-5); ORcombined=2.80), mapping to a noncoding transcript exon of PDE10A; and rs6835978 (p(combined)=1.02x10(-4); ORcombined=2.57), an intronic variant in ATP10D. We assessed the relevance of both proteins in early-stage NSCLC. PDE10A and ATP10D mRNA expressions correlated with survival in 821 stage I-II NSCLC patients (p=0.01 and p<0.0001). PDE10A protein expression correlated with survival in 149 patients with stage I-II NSCLC (p=0.002). In conclusion, we validated two variants associated with extreme phenotypes of high and low risk of developing tobacco-induced NSCLC. Our findings may allow to identify individuals presenting high and low risk to develop tobacco-induced NSCLC and to characterize molecular mechanisms of carcinogenesis and resistance to develop NSCLC

    Lipid profile, cardiovascular disease and mortality in a Mediterranean high-risk population: the ESCARVAL-RISK study

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    The potential impact of targeting different components of an adverse lipid profile in populations with multiple cardiovascular risk factors is not completely clear. This study aims to assess the association between different components of the standard lipid profile with all cause mortality and hospitalization due to cardiovascular events in a high-risk population. Methods This prospective registry included high risk adults over 30 years old free of cardiovascular disease (2008±2012). Diagnosis of hypertension, dyslipidemia or diabetes mellitus was inclusion criterion. Lipid biomarkers were evaluated. Primary endpoints were all-cause mortality and hospital admission due to coronary heart disease or stroke. We estimated adjusted rate ratios (aRR), absolute risk differences and population attributable risk associated with adverse lipid profiles. Results 51,462 subjects were included with a mean age of 62.6 years (47.6% men). During an average follow-up of 3.2 years, 919 deaths, 1666 hospitalizations for coronary heart disease and 1510 hospitalizations for stroke were recorded. The parameters that showed an increased rate for total mortality, coronary heart disease and stroke hospitalization were, respectively, low HDL-Cholesterol: aRR 1.25, 1.29 and 1.23; high Total/HDL-Cholesterol: aRR 1.22, 1.38 and 1.25; and high Triglycerides/HDL-Cholesterol: aRR 1.21, 1.30, 1.09. The parameters that showed highest population attributable risk (%) were, respectively, low HDL-Cholesterol: 7.70, 11.42, 8.40; high Total/HDL-Cholesterol: 6.55, 12.47, 8.73; and high Triglycerides/ HDL-Cholesterol: 8.94, 15.09, 6.92. Conclusions In a population with cardiovascular risk factors, HDL-cholesterol, Total/HDL-cholesterol and triglycerides/HDL-cholesterol ratios were associated with a higher population attributable risk for cardiovascular disease compared to other common biomarkers

    Suicide attempts and related factors in patients admitted to a general hospital: a ten-year cross-sectional study (1997-2007)

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    [Abstract] Background: Suicide and suicide attempts represent a severe problem for public health services. The aim of this study is to determine the socio-demographic and psychopathological variables associated with suicide attempts in the population admitted to a General Hospital. Methods: An observational-descriptive study of patients admitted to the A Coruña University Hospital (Spain) during the period 1997-2007, assessed by the Consultation and Liaison Psychiatric Unit. We include n = 5,234 admissions from 4,509 patients. Among these admissions, n = 361 (6.9%) were subsequent to a suicide attempt. Admissions arising from a suicide attempt were compared with admissions occurring due to other reasons.Multivariate generalised estimating equation logistic regression models were used to examine factors associated with suicide attempts. Results: Adjusting by age, gender, educational level, cohabitation status, being employed or unemployed, the psychiatric diagnosis at the time of the interview and the information on previous suicide attempts, we found that the variables associated with the risk of a suicide attempt were: age, psychiatric diagnosis and previous suicide attempts. The risk of suicide attempts decreases with age (OR = 0.969). Psychiatric diagnosis was associated with a higher risk of suicide attempts, with the highest risk being found for Mood or Affective Disorders (OR = 7.49), followed by Personality Disorders (OR = 7.31), and Schizophrenia and Other Psychotic Disorders (OR = 5.03).The strongest single predictive factor for suicide attempts was a prior history of attempts (OR = 23.63). Conclusions: Age, psychopathological diagnosis and previous suicide attempts are determinants of suicide attempts

    Hemolymph microbiome of Pacific oysters in response to temperature, temperature stress and infection

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    Microbiota provide their hosts with a range of beneficial services, including defense from external pathogens. However, host-associated microbial communities themselves can act as a source of opportunistic pathogens depending on the environment. Marine poikilotherms and their microbiota are strongly influenced by temperature, but experimental studies exploring how temperature affects the interactions between both parties are rare. To assess the effects of temperature, temperature stress and infection on diversity, composition and dynamics of the hemolymph microbiota of Pacific oysters (Crassostrea gigas), we conducted an experiment in a fully-crossed, three-factorial design, in which the temperature acclimated oysters (8 or 22 °C) were exposed to temperature stress and to experimental challenge with a virulent Vibrio sp. Strain. We monitored oyster survival and repeatedly collected hemolymph of dead and alive animals to determine the microbiome composition by 16s rRNA gene amplicon pyrosequencing. We found that the microbial dynamics and composition of communities in healthy animals (including infection survivors) were significantly affected by temperature and temperature stress, but not by infection. The response was mediated by changes in the incidence and abundance of operational taxonomic units (OTUs) and accompanied by little change at higher taxonomic levels, indicating dynamic stability of the hemolymph microbiome. Dead and moribund oysters, on the contrary, displayed signs of community structure disruption, characterized by very low diversity and proliferation of few OTUs. We can therefore link short-term responses of host-associated microbial communities to abiotic and biotic factors and assess the potential feedback between microbiota dynamics and host survival during disease
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