104 research outputs found

    Soil classification from visible/near-infrared diffuse reflectance spectra at multiple depths.

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    Abstract : Visible/near-infrared diffuse reflectance spectroscopy (VNIRS) offers an alternative to conventional analytical methods to estimate various soil attributes. However, the use of VNIRS in soil survey and taxonomic classification is still underexplored. We investigated the potential use of VNIRS to classify soils in a region with variable soils, geology, and topography in southeastern Brazil. We combined principal component (PC) analysis, and multinomial logistic regression to classify 291 soils at the levels of suborder (second highest), and suborder with textural classification (STC), described in the field according to the Brazilian Soil Classification System. Soil visible/near-infrared (400-2500 nm) spectra were collected from three depth intervals (0-20, 40-60, and 80-100 cm), and combined in sequence to compose a pseudo multi-depth spectral curve, which was used to derive the classification models. The percent of correctly classified soils at the suborder level was 79% using 20 PCs, and 96% using 30 PCs. At the STC level, soils were correctly classified in 100%, and 78% of the cases using 20, and 30 PCs, respectively. Given the inherent complexity and variability within soil taxonomic groups, and in contrast the similarity among different groups, combining spectral data from different depths in multivariate classification offered a simple and inexpensive solution to adequately distinguish soils. This novel approach could improve soil classification and survey in a cost-efficient manner, supporting sustainable use, and management of tropical soils

    GENIE: a software package for gene-gene interaction analysis in genetic association studies using multiple GPU or CPU cores

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    <p>Abstract</p> <p>Background</p> <p>Gene-gene interaction in genetic association studies is computationally intensive when a large number of SNPs are involved. Most of the latest Central Processing Units (CPUs) have multiple cores, whereas Graphics Processing Units (GPUs) also have hundreds of cores and have been recently used to implement faster scientific software. However, currently there are no genetic analysis software packages that allow users to fully utilize the computing power of these multi-core devices for genetic interaction analysis for binary traits.</p> <p>Findings</p> <p>Here we present a novel software package GENIE, which utilizes the power of multiple GPU or CPU processor cores to parallelize the interaction analysis. GENIE reads an entire genetic association study dataset into memory and partitions the dataset into fragments with non-overlapping sets of SNPs. For each fragment, GENIE analyzes: 1) the interaction of SNPs within it in parallel, and 2) the interaction between the SNPs of the current fragment and other fragments in parallel. We tested GENIE on a large-scale candidate gene study on high-density lipoprotein cholesterol. Using an NVIDIA Tesla C1060 graphics card, the GPU mode of GENIE achieves a speedup of 27 times over its single-core CPU mode run.</p> <p>Conclusions</p> <p>GENIE is open-source, economical, user-friendly, and scalable. Since the computing power and memory capacity of graphics cards are increasing rapidly while their cost is going down, we anticipate that GENIE will achieve greater speedups with faster GPU cards. Documentation, source code, and precompiled binaries can be downloaded from <url>http://www.cceb.upenn.edu/~mli/software/GENIE/</url>.</p

    Efficient Parallel Statistical Model Checking of Biochemical Networks

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    We consider the problem of verifying stochastic models of biochemical networks against behavioral properties expressed in temporal logic terms. Exact probabilistic verification approaches such as, for example, CSL/PCTL model checking, are undermined by a huge computational demand which rule them out for most real case studies. Less demanding approaches, such as statistical model checking, estimate the likelihood that a property is satisfied by sampling executions out of the stochastic model. We propose a methodology for efficiently estimating the likelihood that a LTL property P holds of a stochastic model of a biochemical network. As with other statistical verification techniques, the methodology we propose uses a stochastic simulation algorithm for generating execution samples, however there are three key aspects that improve the efficiency: first, the sample generation is driven by on-the-fly verification of P which results in optimal overall simulation time. Second, the confidence interval estimation for the probability of P to hold is based on an efficient variant of the Wilson method which ensures a faster convergence. Third, the whole methodology is designed according to a parallel fashion and a prototype software tool has been implemented that performs the sampling/verification process in parallel over an HPC architecture

    Influenza A(H1N1)pdm09 vaccination policies and coverage in Europe

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    In August 2010 the Vaccine European New Integrated Collaboration Effort (VENICE) project conducted a survey to collect information on influenza A(H1N1) pdm09 vaccination policies and vaccination coverage in the European Union (EU), Norway and Iceland. Of 29 responding countries, 26 organised national pandemic influenza vaccination and one country had recommendations for vaccination but did not have a specific programme. Of the 27 countries with vaccine recommendations, all recommended it for healthcare workers and pregnant women. Twelve countries recommended vaccine for all ages. Six and three countries had recommendations for specific age groups in children and in adults, countries for specific adult age groups. Most countries recommended vaccine for those in new risk groups identified early in the pandemic such as morbid obese and people with neurologic diseases. Two thirds of countries started their vaccination campaigns within a four week period after week 40/2009. The reported vaccination coverage varied between countries from 0.4% to 59% for the entire population (22 countries); 3% to 68% for healthcare workers (13 countries); 0% to 58% for pregnant women (12 countries); 0.2% to 74% for children (12 countries). Most countries identified similar target groups for pandemic vaccine, but substantial variability in vaccination coverage was seen. The recommendations were in accordance with policy advice from the EU Health Security Committee and the World Health Organization

    The current state of introduction of human papillomavirus vaccination into national immunisation schedules in Europe: first results of the VENICE2 2010 survey.

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    The Venice 2 human papillomavirus vaccination survey evaluates the state of introduction of the HPV vaccination into the national immunisation schedules in the 29 participating countries. As of July 2010, 18 countries have integrated this vaccination. The vaccination policy and achievements vary among those countries regarding target age groups, delivery infrastructures and vaccination coverage reached. Financial constraints remain the major obstacle for the 11 countries who have not yet introduced the vaccination

    The local and systemic response to SARS-CoV-2 infection in children and adults

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    While a substantial proportion of adults infected with SARS-CoV-2 progress to develop severe disease, children rarely manifest respiratory complications. Therefore, understanding differences in the local and systemic response to SARS-CoV-2 infection between children and adults may provide important clues about the pathogenesis of SARS-CoV-2 infection. To address this, we first generated a healthy reference multi-omics single cell data set from children (n=30) in whom we have profiled triple matched samples: nasal and tracheal brushings and PBMCs, where we track the developmental changes for 42 airway and 31 blood cell populations from infancy, through childhood to adolescence. This has revealed the presence of naive B and T lymphocytes in neonates and infants with a unique gene expression signature bearing hallmarks of innate immunity. We then contrast the healthy reference with equivalent data from severe paediatric and adult COVID-19 patients (total n=27), from the same three types of samples: upper and lower airways and blood. We found striking differences: children with COVID-19 as opposed to adults had a higher proportion of innate lymphoid and non-clonally expanded naive T cells in peripheral blood, and a limited interferon-response signature. In the airway epithelium, we found the highest viral load in goblet and ciliated cells and describe a novel inflammatory epithelial cell population. These cells represent a transitional regenerative state between secretory and ciliated cells; they were found in healthy children and were enriched in paediatric and adult COVID-19 patients. Epithelial cells display an antiviral and neutrophil-recruiting gene signature that is weaker in severe paediatric versus adult COVID-19. Our matched blood and airway samples allowed us to study the spatial dynamics of infection. Lastly, we provide a user-friendly interface for this data1 as a highly granular reference for the study of immune responses in airways and blood in children

    Local and systemic responses to SARS-CoV-2 infection in children and adults

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    It is not fully understood why COVID-19 is typically milder in children1–3. To examine differences in response to SARS-CoV-2 infection in children and adults, we analysed paediatric and adult COVID-19 patients and healthy controls (total n=93) using single-cell multi-omic profiling of matched nasal, tracheal, bronchial and blood samples. In healthy paediatric airways, we observed cells already in an interferon-activated state, that upon SARS-CoV-2 infection was further induced especially in airway immune cells. We postulate that higher paediatric innate interferon-responses restrict viral replication and disease progression. The systemic response in children was characterised by increases in naive lymphocytes and a depletion of natural killer cells, while in adults cytotoxic T cells and interferon-stimulated subpopulations were significantly increased. We provide evidence that dendritic cells initiate interferon signaling in early infection, and identify novel epithelial cell states that associate with COVID-19 and age. Our matching nasal and blood data showed a strong interferon response in the airways with the induction of systemic interferon-stimulated populations, which were massively reduced in paediatric patients. Together, we provide several mechanisms that explain the milder clinical syndrome observed in children

    Transcriptional Regulation Is a Major Controller of Cell Cycle Transition Dynamics

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    DNA replication, mitosis and mitotic exit are critical transitions of the cell cycle which normally occur only once per cycle. A universal control mechanism was proposed for the regulation of mitotic entry in which Cdk helps its own activation through two positive feedback loops. Recent discoveries in various organisms showed the importance of positive feedbacks in other transitions as well. Here we investigate if a universal control system with transcriptional regulation(s) and post-translational positive feedback(s) can be proposed for the regulation of all cell cycle transitions. Through computational modeling, we analyze the transition dynamics in all possible combinations of transcriptional and post-translational regulations. We find that some combinations lead to ‘sloppy’ transitions, while others give very precise control. The periodic transcriptional regulation through the activator or the inhibitor leads to radically different dynamics. Experimental evidence shows that in cell cycle transitions of organisms investigated for cell cycle dependent periodic transcription, only the inhibitor OR the activator is under cyclic control and never both of them. Based on these observations, we propose two transcriptional control modes of cell cycle regulation that either STOP or let the cycle GO in case of a transcriptional failure. We discuss the biological relevance of such differences

    Nintedanib for Systemic Sclerosis-Associated Interstitial Lung Disease

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    BACKGROUND: Interstitial lung disease (ILD) is a common manifestation of systemic sclerosis and a leading cause of systemic sclerosis-related death. Nintedanib, a tyrosine kinase inhibitor, has been shown to have antifibrotic and antiinflammatory effects in preclinical models of systemic sclerosis and ILD. METHODS: We conducted a randomized, double-blind, placebo-controlled trial to investigate the efficacy and safety of nintedanib in patients with ILD associated with systemic sclerosis. Patients who had systemic sclerosis with an onset of the first non-Raynaud's symptom within the past 7 years and a high-resolution computed tomographic scan that showed fibrosis affecting at least 10% of the lungs were randomly assigned, in a 1:1 ratio, to receive 150 mg of nintedanib, administered orally twice daily, or placebo. The primary end point was the annual rate of decline in forced vital capacity (FVC), assessed over a 52-week period. Key secondary end points were absolute changes from baseline in the modified Rodnan skin score and in the total score on the St. George's Respiratory Questionnaire (SGRQ) at week 52. RESULTS: A total of 576 patients received at least one dose of nintedanib or placebo; 51.9% had diffuse cutaneous systemic sclerosis, and 48.4% were receiving mycophenolate at baseline. In the primary end-point analysis, the adjusted annual rate of change in FVC was 1252.4 ml per year in the nintedanib group and 1293.3 ml per year in the placebo group (difference, 41.0 ml per year; 95% confidence interval [CI], 2.9 to 79.0; P=0.04). Sensitivity analyses based on multiple imputation for missing data yielded P values for the primary end point ranging from 0.06 to 0.10. The change from baseline in the modified Rodnan skin score and the total score on the SGRQ at week 52 did not differ significantly between the trial groups, with differences of 120.21 (95% CI, 120.94 to 0.53; P=0.58) and 1.69 (95% CI, 120.73 to 4.12 [not adjusted for multiple comparisons]), respectively. Diarrhea, the most common adverse event, was reported in 75.7% of the patients in the nintedanib group and in 31.6% of those in the placebo group. CONCLUSIONS: Among patients with ILD associated with systemic sclerosis, the annual rate of decline in FVC was lower with nintedanib than with placebo; no clinical benefit of nintedanib was observed for other manifestations of systemic sclerosis. The adverse-event profile of nintedanib observed in this trial was similar to that observed in patients with idiopathic pulmonary fibrosis; gastrointestinal adverse events, including diarrhea, were more common with nintedanib than with placebo
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