1,821 research outputs found

    Evaluation of decellularization of porcine pericardium: Decellularization of porcine pericardium

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    The porcine pericardium has been used for its great potential as a biological scaffold, produced from the extracellular matrix (ECM) and used mainly in surgeries reconstructive, tissue repair and surgical procedures for corneal reconstruction. The adequate preservation and biocompatibility of the pericardial ECM structure during the decellularization process is fundamental, the biggest challenge being the total removal of cellular material without damage to the structure. All agents used in decellularization change the composition and cause some damage to the ultrastructure. Sodium Dodecil Sulfate (SDS) is the most effective for removing cell residue from tissue compared to other detergents, which is also the most used for the decellularization process. This work aimed to test 3 different concentrations of SDS, in order to assess the concentration (0.1, 0.5 and 1%) that best preserves the structure of the ECM pericardial. In addition, we listed the type of daily wash to make the process more effective (only distilled water or PBS 1x), in order to assess the concentration capable of decellularizing the tissue and better preserving the pericardial ECM. The concentration of SDS at 1%, when compared to the lowest concentrations of 0.1 and 0.5%, was more effective in the decellularization process, however it did not obtain good results in the preservation of the ECM. Regarding daily washing, there was no difference in the frequency assessed in the experimental groups

    Decrease of virulence for BALB/c mice produced by continuous subculturing of Nocardia brasiliensis

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    <p>Abstract</p> <p>Background</p> <p>Subculturing has been extensively used to attenuate human pathogens. In this work we studied the effect of continuous subculturing of <it>Nocardia brasiliensis </it>HUJEG-1 on virulence in a murine model.</p> <p>Methods</p> <p><it>Nocardia brasiliensis </it>HUJEG-1 was subcultured up to 130 times on brain heart infusion over four years. BALB/c mice were inoculated in the right foot pad with the bacteria subcultured 0, 40, 80, 100 and 130 times (T<sub>0</sub>, T<sub>40</sub>, T<sub>80 </sub>T<sub>100 </sub>and T<sub>130</sub>). The induction of resistance was tested by using T<sub>130 </sub>to inoculate a group of mice followed by challenge with T0 12 weeks later. Biopsies were taken from the newly infected foot-pad and immunostained with antibodies against CD4, CD8 and CD14 in order to analyze the in situ immunological changes.</p> <p>Results</p> <p>When using T<sub>40</sub>, T<sub>80 </sub>T<sub>100 </sub>and T<sub>130 </sub>as inoculums we observed lesions in 10, 5, 0 and 0 percent of the animals, respectively, at the end of 12 weeks. In contrast, their controls produced mycetoma in 80, 80, 70 and 60% of the inoculated animals. When studying the protection of T<sub>130</sub>, we observed a partial resistance to the infection. Immunostaining revealed an intense CD4+ lymphocytic and macrophage infiltrate in healing lesions.</p> <p>Conclusions</p> <p>After 130 in vitro passages of <it>N. brasiliensis </it>HUJEG-1 a severe decrease in its virulence was observed. Immunization of BALB/c mice, with these attenuated cells, produced a state of partial resistance to infection with the non-subcultured isolate.</p

    A continuous mapping of sleep states through association of EEG with a mesoscale cortical model

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    Here we show that a mathematical model of the human sleep cycle can be used to obtain a detailed description of electroencephalogram (EEG) sleep stages, and we discuss how this analysis may aid in the prediction and prevention of seizures during sleep. The association between EEG data and the cortical model is found via locally linear embedding (LLE), a method of dimensionality reduction. We first show that LLE can distinguish between traditional sleep stages when applied to EEG data. It reliably separates REM and non-REM sleep and maps the EEG data to a low-dimensional output space where the sleep state changes smoothly over time. We also incorporate the concept of strongly connected components and use this as a method of automatic outlier rejection for EEG data. Then, by using LLE on a hybrid data set containing both sleep EEG and signals generated from the mesoscale cortical model, we quantify the relationship between the data and the mathematical model. This enables us to take any sample of sleep EEG data and associate it with a position among the continuous range of sleep states provided by the model; we can thus infer a trajectory of states as the subject sleeps. Lastly, we show that this method gives consistent results for various subjects over a full night of sleep and can be done in real time

    Mining Virulence Genes Using Metagenomics

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    When a bacterial genome is compared to the metagenome of an environment it inhabits, most genes recruit at high sequence identity. In free-living bacteria (for instance marine bacteria compared against the ocean metagenome) certain genomic regions are totally absent in recruitment plots, representing therefore genes unique to individual bacterial isolates. We show that these Metagenomic Islands (MIs) are also visible in bacteria living in human hosts when their genomes are compared to sequences from the human microbiome, despite the compartmentalized structure of human-related environments such as the gut. From an applied point of view, MIs of human pathogens (e.g. those identified in enterohaemorragic Escherichia coli against the gut metagenome or in pathogenic Neisseria meningitidis against the oral metagenome) include virulence genes that appear to be absent in related strains or species present in the microbiome of healthy individuals. We propose that this strategy (i.e. recruitment analysis of pathogenic bacteria against the metagenome of healthy subjects) can be used to detect pathogenicity regions in species where the genes involved in virulence are poorly characterized. Using this approach, we detect well-known pathogenicity islands and identify new potential virulence genes in several human pathogens

    First observations of separated atmospheric nu_mu and bar{nu-mu} events in the MINOS detector

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    The complete 5.4 kton MINOS far detector has been taking data since the beginning of August 2003 at a depth of 2070 meters water-equivalent in the Soudan mine, Minnesota. This paper presents the first MINOS observations of nuµ and [overline nu ]µ charged-current atmospheric neutrino interactions based on an exposure of 418 days. The ratio of upward- to downward-going events in the data is compared to the Monte Carlo expectation in the absence of neutrino oscillations, giving Rup/downdata/Rup/downMC=0.62-0.14+0.19(stat.)±0.02(sys.). An extended maximum likelihood analysis of the observed L/E distributions excludes the null hypothesis of no neutrino oscillations at the 98% confidence level. Using the curvature of the observed muons in the 1.3 T MINOS magnetic field nuµ and [overline nu ]µ interactions are separated. The ratio of [overline nu ]µ to nuµ events in the data is compared to the Monte Carlo expectation assuming neutrinos and antineutrinos oscillate in the same manner, giving R[overline nu ][sub mu]/nu[sub mu]data/R[overline nu ][sub mu]/nu[sub mu]MC=0.96-0.27+0.38(stat.)±0.15(sys.), where the errors are the statistical and systematic uncertainties. Although the statistics are limited, this is the first direct observation of atmospheric neutrino interactions separately for nuµ and [overline nu ]µ

    Interactive effects of ambient fine particulate matter and ozone on daily mortality in 372 cities: two stage time series analysis

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    Objective To investigate potential interactive effects of fine particulate matter (PM2.5) and ozone (O3) on daily mortality at global level. Design Two stage time series analysis. Setting 372 cities across 19 countries and regions. Population Daily counts of deaths from all causes, cardiovascular disease, and respiratory disease. Main outcome measure Daily mortality data during 1994-2020. Stratified analyses by co-pollutant exposures and synergy index (>1 denotes the combined effect of pollutants is greater than individual effects) were applied to explore the interaction between PM2.5 and O3 in association with mortality. Results During the study period across the 372 cities, 19.3 million deaths were attributable to all causes, 5.3 million to cardiovascular disease, and 1.9 million to respiratory disease. The risk of total mortality for a 10 μg/m3 increment in PM2.5 (lag 0-1 days) ranged from 0.47% (95% confidence interval 0.26% to 0.67%) to 1.25% (1.02% to 1.48%) from the lowest to highest fourths of O3 concentration; and for a 10 μg/m3 increase in O3 ranged from 0.04% (−0.09% to 0.16%) to 0.29% (0.18% to 0.39%) from the lowest to highest fourths of PM2.5 concentration, with significant differences between strata (P for interaction <0.001). A significant synergistic interaction was also identified between PM2.5 and O3 for total mortality, with a synergy index of 1.93 (95% confidence interval 1.47 to 3.34). Subgroup analyses showed that interactions between PM2.5 and O3 on all three mortality endpoints were more prominent in high latitude regions and during cold seasons. Conclusion The findings of this study suggest a synergistic effect of PM2.5 and O3 on total, cardiovascular, and respiratory mortality, indicating the benefit of coordinated control strategies for both pollutants

    Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

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    SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation

    Properties of Graphene: A Theoretical Perspective

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    In this review, we provide an in-depth description of the physics of monolayer and bilayer graphene from a theorist's perspective. We discuss the physical properties of graphene in an external magnetic field, reflecting the chiral nature of the quasiparticles near the Dirac point with a Landau level at zero energy. We address the unique integer quantum Hall effects, the role of electron correlations, and the recent observation of the fractional quantum Hall effect in the monolayer graphene. The quantum Hall effect in bilayer graphene is fundamentally different from that of a monolayer, reflecting the unique band structure of this system. The theory of transport in the absence of an external magnetic field is discussed in detail, along with the role of disorder studied in various theoretical models. We highlight the differences and similarities between monolayer and bilayer graphene, and focus on thermodynamic properties such as the compressibility, the plasmon spectra, the weak localization correction, quantum Hall effect, and optical properties. Confinement of electrons in graphene is nontrivial due to Klein tunneling. We review various theoretical and experimental studies of quantum confined structures made from graphene. The band structure of graphene nanoribbons and the role of the sublattice symmetry, edge geometry and the size of the nanoribbon on the electronic and magnetic properties are very active areas of research, and a detailed review of these topics is presented. Also, the effects of substrate interactions, adsorbed atoms, lattice defects and doping on the band structure of finite-sized graphene systems are discussed. We also include a brief description of graphane -- gapped material obtained from graphene by attaching hydrogen atoms to each carbon atom in the lattice.Comment: 189 pages. submitted in Advances in Physic

    Diffractive Dijet Production at sqrt(s)=630 and 1800 GeV at the Fermilab Tevatron

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    We report a measurement of the diffractive structure function FjjDF_{jj}^D of the antiproton obtained from a study of dijet events produced in association with a leading antiproton in pˉp\bar pp collisions at s=630\sqrt s=630 GeV at the Fermilab Tevatron. The ratio of FjjDF_{jj}^D at s=630\sqrt s=630 GeV to FjjDF_{jj}^D obtained from a similar measurement at s=1800\sqrt s=1800 GeV is compared with expectations from QCD factorization and with theoretical predictions. We also report a measurement of the ξ\xi (xx-Pomeron) and β\beta (xx of parton in Pomeron) dependence of FjjDF_{jj}^D at s=1800\sqrt s=1800 GeV. In the region 0.035<ξ<0.0950.035<\xi<0.095, t<1|t|<1 GeV2^2 and β<0.5\beta<0.5, FjjD(β,ξ)F_{jj}^D(\beta,\xi) is found to be of the form β1.0±0.1ξ0.9±0.1\beta^{-1.0\pm 0.1} \xi^{-0.9\pm 0.1}, which obeys β\beta-ξ\xi factorization.Comment: LaTeX, 9 pages, Submitted to Phys. Rev. Letter
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