2,076 research outputs found

    Towards pocket-sized genomic analyses: cross-platform benchmark of multi-organism genomic data indexing and alignment

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    The current socio-economic situation as well as international objectives set by the United Nation (2030 Sustainable Agenda) underline the urgency of low-cost and environmental-friendly computational alternatives. Moreover, in recent years the bioinformatic community has shown renewed interest for Raspberry Pi (RPi) application in teaching and research projects. In the context of the BioVRPi project - which aims to develop and offer a low-cost, stable and tested bioinformatic environment - we propose an exploratory cross-platform benchmarking of multi-organism genomic analyses. The benchmark of indexing and alignment processes was carried out on the following devices: RPi 4 (Raspberry Pi OS 04-04-2022) RAM 8GB HDD storage, laptop (MacOS Big Sur v11.2.3) Intel Core i5 2GHz quad-core processor RAM 16GB SSD, and desktop (Ubuntu 20.04.4 LTS) Intel Core i7 3GHz octa-core processor RAM 32GB HDD storage. Performance assessment was evaluated on SARS-CoV-2 virus, Escherichia coli and Caenorhabditis elegans genome sequences (respective RefSeq accessions: GCF_009858895.2, GCF_000005845.2, GCF_000002985.6) since they present different degrees of genomic complexity: virus, bacterium, and nematode. To minimize variability and possible biases due to sequencing technologies used, sample reads were generated in silico from their respective reference genomes using ART Illumina v2.5.8 with the following parameters: read length 150, paired end, coverage 30X, mean fragment length 200, standard deviation 10, HiSeqX v2.5 TruSeq built-in profile. Indexing and alignment were performed with 3 alignment tools: BWA v0.7.17-r1188, Bowtie2 v2.4.5, and Minimap2 v2.17, using default parameters and scaling from 1 up to 4 threads. Benchmarking was evaluated using Hyperfine v1.13.0 with a warmup step of 3 simulations and 10 runs for each process. We performed a cross-platform benchmark of multi-organism genomic indexing and short reads alignment to evaluate RPi as a viable alternative to common bioinformatic devices. To assess its performance, we tested some of the most widely used alignment tools on SARS-CoV-2, E. coli and C. elegans genomic data (respective genome sizes: 29.9Kbp, 4.6Mbp, 100.3Mbp). The computational times for indexing and alignment are reported in Table 1. As regards indexing, we observed comparable runtimes among RPi and other platforms using BWA and Bowtie2 for SARS-CoV-2 and E. coli, whereas Minimap2 indexing showed an increase of one order of magnitude in runtimes for RPi. Nonetheless, Minimap2 showed the fastest runtimes for indexing overall. In addition, we found an increase of one order of magnitude in RPi runtimes for C. elegans for all considered tools, even though differences in runtimes across platforms showed to be stable across organisms. As regards the alignment process, we observed consistency in runtimes differences across all organisms and tools. Overall, Minimap2 performances proved to be the fastest whereas Bowtie2 displayed poor performances across all platforms, exacerbating its inefficiency on RPi. Even though BWA seems to work more efficiently on RPi than on desktop for SARS-COV-2 data, desktop and laptop showed better performances on more complex organisms as expected. Benchmarking analyses considered multi-threading up to 4 threads, the maximum available on RPi. As regards indexing on Bowtie2, multi-threading proved to be effective for C. elegans data, showing no improvement in runtimes for SARS-CoV-2 and E. coli. Conversely, alignment showed the best performances using multi-threading as expected. In conclusion, RPi showed promising results, proved to be a viable low-cost and environmental-friendly alternative to perform genomic data analysis on different organisms and turned out to be particularly efficient for microorganisms. Further advances and tools optimization for RPi ARM architecture will lead to a greater scalability for complex organisms and will be carried out by the BioVRPi project in future exploratory analyses

    Vilanterol trifenatate for the treatment of COPD

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    Introduction: Currently the treatment of chronic obstructive pulmonary disease (COPD) has limited effectiveness and there is a need to develop new drugs. International guidelines recommend the use of long-acting bronchodilators (β2 agonists and anti-cholinergics/muscarinics), inhaled steroids and associations between these drugs in the maintenance treatment of moderate-to-severe COPD. Area covered: Vilanterol trifenate is a new once-daily highly selective β2-agonist available in USA and Europe in association with umeclidinium bromide (a long-acting anti-muscarnic agent) and fluticasone furoate (an inhaled corticosteroid) for the once-daily maintenance treatment of COPD. Vilanterol combined in fixed-dose treatments has been tested in numerous clinical trials involving thousands of patients. Expert commentary: These new once-daily formulations have the potential to improve compliance to long-term inhaled therapy. This paper will review the clinical and experimental data regarding vilanterol use in the regular treatment of COPD as well as provide a critical discussion of possible future treatment settings

    JKarma: A Highly-Modular Framework for Pattern-Based Change Detection on Evolving Data

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    Pattern-based change detection (PBCD) describes a class of change detection algorithms for evolving data. Contrary to conventional solutions, PBCD seeks changes exhibited by the patterns over time and therefore works on an abstract form of the data, which prevents the search for changes on the raw data. Moreover, PBCD provides arguments on the validity of the results because patterns mirror changes occurred with any form of evidence. However, the existing solutions differ on data representation, mining algorithm and change identification strategy, which we can deem as main modules of a general architecture, so that any PBCD task could be designed by accommodating custom implementations for those modules. This is what we propose in this paper through jKarma, a highly-modular framework for designing and performing PBCD

    Platelet activation and cardiovascular co-morbidities in patients with chronic obstructive pulmonary disease.

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    Objective: Platelet activation in COPD patients is associated with an increased risk of cardiovascular events. Aim of the study: to assess the mean platelet volume (MPV), as an index of platelet activation, in patients with COPD both when stable or during exacerbation. Research design and methods: 478 patients with COPD (75 with exacerbation) and 72 age-matched healthy controls were enrolled. Medical history, co-morbidities, medications, pulmonary function tests, MPV and blood cell count, erythrocyte sedimentation rate (ERS) and C reactive protein (CRP) were recorded. Results: MPV was higher in COPD patients than in controls (8.7 \ub1 1.1 fL and 8.4 \ub1 0.8 fL respectively, p = 0.025) and increased across the severity of the diseases as assessed by the GOLD post bronchodilator FEV1 categorized I to IV (p>0.05). MPV was higher in COPD patients during acute exacerbation as compared with stable condition (8.7 \ub1 1.0 fL and 8.9 \ub1 1.0 fL, p = 0.021). MPV 65 10.5 fL correlated with the presence of at least one co-existing cardiovascular disease (p = 0.008) . No correlation was observed between MPV and CRP or ERS in patients or in controls. An inverse significant correlation was found between platelets count and MPV in COPD patients. Conclusions: Elevated MPV is associated with lower platelet count and with cardiovascular co-morbidity in COPD patients. MPV value is higher in more severe COPD and during acute exacerbation. Present findings warrant future studies to confirm a possible clinically relevant role for platelet activation and cardiovascular risk in the population of COPD

    Cellular automata approach to durability analysis of concrete structures in aggressive environments

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    This paper presents a novel approach to the problem of durability analysis and lifetime assessment of concrete structures under the diffusive attack from external aggressive agents. The proposed formulation mainly refers to beams and frames, but it can be easily extended also to other types of structures. The diffusion process is modeled by using cellular automata. The mechanical damage coupled to diffusion is evaluated by introducing suitable material degradation laws. Since the rate of mass diffusion usually depends on the stress state, the interaction between the diffusion process and the mechanical behavior of the damaged structure is also taken into account by a proper modeling of the stochastic effects in the mass transfer. To this aim, the nonlinear structural analyses during time are performed within the framework of the finite element method by means of a deteriorating reinforced concrete beam element. The effectiveness of the proposed methodology in handling complex geometrical and mechanical boundary conditions is demonstrated through some applications. Firstly, a reinforced concrete box girder cross section is considered and the damaging process is described by the corresponding evolution of both bending moment-curvature diagrams and axial force-bending moment resistance domains. Secondly, the durability analysis of a reinforced concrete continuous T-beam is developed. Finally, the proposed approach is applied to the analysis of an existing arch bridge and to the identification of its critical members

    Resistome, mobilome and virulome analysis of Shewanellaalgae and Vibrio spp. strains isolated in italian aquaculture centers

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    Antimicrobial resistance is a major public health concern restricted not only to healthcare settings but also to veterinary and environmental ones. In this study, we analyzed, by whole genome sequencing (WGS) the resistome, mobilome and virulome of 12 multidrug-resistant (MDR) marine strains belonging to Shewanellaceae and Vibrionaceae families collected at aquaculture centers in Italy. The results evidenced the presence of several resistance mechanisms including enzyme and efflux pump systems conferring resistance to beta-lactams, quinolones, tetracyclines, macrolides, polymyxins, chloramphenicol, fosfomycin, erythromycin, detergents and heavy metals. Mobilome analysis did not find circular elements but class I integrons, integrative and conjugative element (ICE) associated modules, prophages and different insertion sequence (IS) family transposases. These mobile genetic elements (MGEs) are usually present in other aquatic bacteria but also in Enterobacteriaceae suggesting their transferability among autochthonous and allochthonous bacteria of the resilient microbiota. Regarding the presence of virulence factors, hemolytic activity was detected both in the Shewanella algae and in Vibrio spp. strains. To conclude, these data indicate the role as a reservoir of resistance and virulence genes in the environment of the aquatic microbiota present in the examined Italian fish farms that potentially might be transferred to bacteria of medical interest
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