48 research outputs found

    RNAi Effector Diversity in Nematodes

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    While RNA interference (RNAi) has been deployed to facilitate gene function studies in diverse helminths, parasitic nematodes appear variably susceptible. To test if this is due to inter-species differences in RNAi effector complements, we performed a primary sequence similarity survey for orthologs of 77 Caenorhabditis elegans RNAi pathway proteins in 13 nematode species for which genomic or transcriptomic datasets were available, with all outputs subjected to domain-structure verification. Our dataset spanned transcriptomes of Ancylostoma caninum and Oesophagostomum dentatum, and genomes of Trichinella spiralis, Ascaris suum, Brugia malayi, Haemonchus contortus, Meloidogyne hapla, Meloidogyne incognita and Pristionchus pacificus, as well as the Caenorhabditis species C. brenneri, C. briggsae, C. japonica and C. remanei, and revealed that: (i) Most of the C. elegans proteins responsible for uptake and spread of exogenously applied double stranded (ds)RNA are absent from parasitic species, including RNAi-competent plant-nematodes; (ii) The Argonautes (AGOs) responsible for gene expression regulation in C. elegans are broadly conserved, unlike those recruited during the induction of RNAi by exogenous dsRNA; (iii) Secondary Argonautes (SAGOs) are poorly conserved, and the nuclear AGO NRDE-3 was not identified in any parasite; (iv) All five Caenorhabditis spp. possess an expanded RNAi effector repertoire relative to the parasitic nematodes, consistent with the propensity for gene loss in nematode parasites; (v) In spite of the quantitative differences in RNAi effector complements across nematode species, all displayed qualitatively similar coverage of functional protein groups. In summary, we could not identify RNAi effector deficiencies that associate with reduced susceptibility in parasitic nematodes. Indeed, similarities in the RNAi effector complements of RNAi refractory and competent nematode parasites support the broad applicability of this research genetic tool in nematodes

    Geoeconomic variations in epidemiology, ventilation management, and outcomes in invasively ventilated intensive care unit patients without acute respiratory distress syndrome: a pooled analysis of four observational studies

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    Background: Geoeconomic variations in epidemiology, the practice of ventilation, and outcome in invasively ventilated intensive care unit (ICU) patients without acute respiratory distress syndrome (ARDS) remain unexplored. In this analysis we aim to address these gaps using individual patient data of four large observational studies. Methods: In this pooled analysis we harmonised individual patient data from the ERICC, LUNG SAFE, PRoVENT, and PRoVENT-iMiC prospective observational studies, which were conducted from June, 2011, to December, 2018, in 534 ICUs in 54 countries. We used the 2016 World Bank classification to define two geoeconomic regions: middle-income countries (MICs) and high-income countries (HICs). ARDS was defined according to the Berlin criteria. Descriptive statistics were used to compare patients in MICs versus HICs. The primary outcome was the use of low tidal volume ventilation (LTVV) for the first 3 days of mechanical ventilation. Secondary outcomes were key ventilation parameters (tidal volume size, positive end-expiratory pressure, fraction of inspired oxygen, peak pressure, plateau pressure, driving pressure, and respiratory rate), patient characteristics, the risk for and actual development of acute respiratory distress syndrome after the first day of ventilation, duration of ventilation, ICU length of stay, and ICU mortality. Findings: Of the 7608 patients included in the original studies, this analysis included 3852 patients without ARDS, of whom 2345 were from MICs and 1507 were from HICs. Patients in MICs were younger, shorter and with a slightly lower body-mass index, more often had diabetes and active cancer, but less often chronic obstructive pulmonary disease and heart failure than patients from HICs. Sequential organ failure assessment scores were similar in MICs and HICs. Use of LTVV in MICs and HICs was comparable (42\ub74% vs 44\ub72%; absolute difference \u20131\ub769 [\u20139\ub758 to 6\ub711] p=0\ub767; data available in 3174 [82%] of 3852 patients). The median applied positive end expiratory pressure was lower in MICs than in HICs (5 [IQR 5\u20138] vs 6 [5\u20138] cm H2O; p=0\ub70011). ICU mortality was higher in MICs than in HICs (30\ub75% vs 19\ub79%; p=0\ub70004; adjusted effect 16\ub741% [95% CI 9\ub752\u201323\ub752]; p<0\ub70001) and was inversely associated with gross domestic product (adjusted odds ratio for a US$10 000 increase per capita 0\ub780 [95% CI 0\ub775\u20130\ub786]; p<0\ub70001). Interpretation: Despite similar disease severity and ventilation management, ICU mortality in patients without ARDS is higher in MICs than in HICs, with a strong association with country-level economic status. Funding: No funding

    Proceedings - International Symposium on Biomedical Imaging

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    © 2016 IEEE.Computer-based analysis is highly effective in information retrieval from Dynamic Contrast Enhance Magnetic Resonance Images (DCE-MRI) for prostate cancer recognition. Quantification and modelling of perfusion curves to extract higher order informative features for use in classification algorithms, is a major step in DCE-MRI analysis where inter-scan independent semi-quantitative models are highly desirable. This paper presents a semi-quantitative analysis model for prostate DCE-MRI, that is independent of inter-scan intensity variations, where the significance of the derived features is maximised by preserving the original shape of the perfusion curve to a maximum degree. The proposed model is evaluated on three different classifiers and 82 annotated prostate peripheral zone lesions in 3T DCE-MRI datasets of 40 patients. Random Forest Classifier yields a promising accuracy of 97.6% and a sensitivity of 92.3%

    Rule-Based Recommendation System for Phylogenetic Inference

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    Phylogenetic Inference is the reconstruction of a phylogenetic tree that depicts the evolutionary relationship among a group of taxa. This evolutionary relationship between different groups of species is useful for fields such as medicine, forensics, and drug discovery. With the availability of multiple phylogenetic inference algorithms, it is challenging to select the optimal algorithm for novice users. Moreover, it is essential to compare the accuracy and efficiency of different algorithms for a given dataset. Thus, there is a need for a recommendation system to identify the most appropriate phylogenetic inference algorithm for each dataset. This paper presents a Rule-based recommendation component that suggests users with suitable algorithms for inferencing. The evaluation results show the recommendations suggested by the system are 86.7% relevant and accurate
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