70 research outputs found

    HIV-1 full-genome phylogenetics of generalized epidemics in sub-Saharan Africa: impact of missing nucleotide characters in next-generation sequences.

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    To characterize HIV-1 transmission dynamics in regions where the burden of HIV-1 is greatest, the 'Phylogenetics and Networks for Generalised HIV Epidemics in Africa' consortium (PANGEA-HIV) is sequencing full-genome viral isolates from across sub-Saharan Africa. We report the first 3,985 PANGEA-HIV consensus sequences from four cohort sites (Rakai Community Cohort Study, n=2,833; MRC/UVRI Uganda, n=701; Mochudi Prevention Project, n=359; Africa Health Research Institute Resistance Cohort, n=92). Next-generation sequencing success rates varied: more than 80% of the viral genome from the gag to the nef genes could be determined for all sequences from South Africa, 75% of sequences from Mochudi, 60% of sequences from MRC/UVRI Uganda, and 22% of sequences from Rakai. Partial sequencing failure was primarily associated with low viral load, increased for amplicons closer to the 3' end of the genome, was not associated with subtype diversity except HIV-1 subtype D, and remained significantly associated with sampling location after controlling for other factors. We assessed the impact of the missing data patterns in PANGEA-HIV sequences on phylogeny reconstruction in simulations. We found a threshold in terms of taxon sampling below which the patchy distribution of missing characters in next-generation sequences has an excess negative impact on the accuracy of HIV-1 phylogeny reconstruction, which is attributable to tree reconstruction artifacts that accumulate when branches in viral trees are long. The large number of PANGEA-HIV sequences provides unprecedented opportunities for evaluating HIV-1 transmission dynamics across sub-Saharan Africa and identifying prevention opportunities. Molecular epidemiological analyses of these data must proceed cautiously because sequence sampling remains below the identified threshold and a considerable negative impact of missing characters on phylogeny reconstruction is expected

    High-level of viral genomic diversity in cervical cancers: a Brazilian study on human papillomavirus type 16

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    Invasive cervical cancer (ICC) is the third most frequent cancer among women worldwide and is associated with persistent infection by carcinogenic human papillomaviruses (HPVs). The combination of large populations of viral progeny and decades of sustained infection may allow for the generation of intra-patient diversity, in spite of the assumedly low mutation rates of PVs. While the natural history of chronic HPVs infections has been comprehensively described, within-host viral diversity remains largely unexplored. In this study we have applied next generation sequencing to the analysis of intra-host genetic diversity in ten ICC and one condyloma cases associated to single HPV16 infection. We retrieved from all cases near full-length genomic sequences. All samples analyzed contained polymorphic sites, ranging from 3 to 125 polymorphic positions per genome, and the median probability of a viral genome picked at random to be identical to the consensus sequence in the lesion was only 40%. We have also identified two independent putative duplication events in two samples, spanning the L2 and the L1 gene, respectively. Finally, we have identified with good support a chimera of human and viral DNA. We propose that viral diversity generated during HPVs chronic infection may be fueled by innate and adaptive immune pressures. Further research will be needed to understand the dynamics of viral DNA variability, differentially in benign and malignant lesions, as well as in tissues with differential intensity of immune surveillance. Finally, the impact of intralesion viral diversity on the long-term oncogenic potential may deserve closer attention.Funded by Grants # 2011/24035-2 and # 2012/23290-1, São Paulo Research Foundation (FAPESP

    DOR/Tp53inp2 and Tp53inp1 Constitute a Metazoan Gene Family Encoding Dual Regulators of Autophagy and Transcription

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    Human DOR/TP53INP2 displays a unique bifunctional role as a modulator of autophagy and gene transcription. However, the domains or regions of DOR that participate in those functions have not been identified. Here we have performed structure/function analyses of DOR guided by identification of conserved regions in the DOR gene family by phylogenetic reconstructions. We show that DOR is present in metazoan species. Invertebrates harbor only one gene, DOR/Tp53inp2, and in the common ancestor of vertebrates Tp53inp1 may have arisen by gene duplication. In keeping with these data, we show that human TP53INP1 regulates autophagy and that different DOR/TP53INP2 and TP53INP1 proteins display transcriptional activity. The use of molecular evolutionary information has been instrumental to determine the regions that participate in DOR functions. DOR and TP53INP1 proteins share two highly conserved regions (region 1, aa residues 28–42; region 2, 66–112 in human DOR). Mutation of conserved hydrophobic residues in region 1 of DOR (that are part of a nuclear export signal, NES) reduces transcriptional activity, and blocks nuclear exit and autophagic activity under autophagy-activated conditions. We also identify a functional and conserved LC3-interacting motif (LIR) in region 1 of DOR and TP53INP1 proteins. Mutation of conserved acidic residues in region 2 of DOR reduces transcriptional activity, impairs nuclear exit in response to autophagy activation, and disrupts autophagy. Taken together, our data reveal DOR and TP53INP1 as dual regulators of transcription and autophagy, and identify two conserved regions in the DOR family that concentrate multiple functions crucial for autophagy and transcription

    Molecular Phylogeny Restores the Supra-Generic Subdivision of Homoscleromorph Sponges (Porifera, Homoscleromorpha)

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    Homoscleromorpha is the fourth major sponge lineage, recently recognized to be distinct from the Demospongiae. It contains <100 described species of exclusively marine sponges that have been traditionally subdivided into 7 genera based on morphological characters. Because some of the morphological features of the homoscleromorphs are shared with eumetazoans and are absent in other sponges, the phylogenetic position of the group has been investigated in several recent studies. However, the phylogenetic relationships within the group remain unexplored by modern methods.Here we describe the first molecular phylogeny of Homoscleromorpha based on nuclear (18S and 28S rDNA) and complete mitochondrial DNA sequence data that focuses on inter-generic relationships. Our results revealed two robust clades within this group, one containing the spiculate species (genera Plakina, Plakortis, Plakinastrella and Corticium) and the other containing aspiculate species (genera Oscarella and Pseudocorticium), thus rejecting a close relationship between Pseudocorticium and Corticium. Among the spiculate species, we found affinities between the Plakortis and Plakinastrella genera, and between the Plakina and Corticium. The validity of these clades is furthermore supported by specific morphological characters, notably the type of spicules. Furthermore, the monophyly of the Corticium genus is supported while the monophyly of Plakina is not.As the result of our study we propose to restore the pre-1995 subdivision of Homoscleromorpha into two families: Plakinidae Schulze, 1880 for spiculate species and Oscarellidae Lendenfeld, 1887 for aspiculate species that had been rejected after the description of the genus Pseudocorticium. We also note that the two families of homoscleromorphs exhibit evolutionary stable, but have drastically distinct mitochondrial genome organizations that differ in gene content and gene order

    Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

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    Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations

    Variation in Structure and Process of Care in Traumatic Brain Injury: Provider Profiles of European Neurotrauma Centers Participating in the CENTER-TBI Study.

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    INTRODUCTION: The strength of evidence underpinning care and treatment recommendations in traumatic brain injury (TBI) is low. Comparative effectiveness research (CER) has been proposed as a framework to provide evidence for optimal care for TBI patients. The first step in CER is to map the existing variation. The aim of current study is to quantify variation in general structural and process characteristics among centers participating in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. METHODS: We designed a set of 11 provider profiling questionnaires with 321 questions about various aspects of TBI care, chosen based on literature and expert opinion. After pilot testing, questionnaires were disseminated to 71 centers from 20 countries participating in the CENTER-TBI study. Reliability of questionnaires was estimated by calculating a concordance rate among 5% duplicate questions. RESULTS: All 71 centers completed the questionnaires. Median concordance rate among duplicate questions was 0.85. The majority of centers were academic hospitals (n = 65, 92%), designated as a level I trauma center (n = 48, 68%) and situated in an urban location (n = 70, 99%). The availability of facilities for neuro-trauma care varied across centers; e.g. 40 (57%) had a dedicated neuro-intensive care unit (ICU), 36 (51%) had an in-hospital rehabilitation unit and the organization of the ICU was closed in 64% (n = 45) of the centers. In addition, we found wide variation in processes of care, such as the ICU admission policy and intracranial pressure monitoring policy among centers. CONCLUSION: Even among high-volume, specialized neurotrauma centers there is substantial variation in structures and processes of TBI care. This variation provides an opportunity to study effectiveness of specific aspects of TBI care and to identify best practices with CER approaches

    MRI in active surveillance: a critical review

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    INTRODUCTION: Recent technological advancements and the introduction of modern anatomical and functional sequences have led to a growing role for multiparametric magnetic resonance imaging (mpMRI) in the detection, risk assessment and monitoring of early prostate cancer. This includes men who have been diagnosed with lower-risk prostate cancer and are looking at the option of active surveillance (AS). The purpose of this paper is to review the recent evidence supporting the use of mpMRI at different time points in AS, as well as to discuss some of its potential pitfalls. METHODS: A combination of electronic and manual searching methods were used to identify recent, important papers investigating the role of mpMRI in AS. RESULTS: The high negative predictive value of mpMRI can be exploited for the selection of AS candidates. In addition, mpMRI can be efficiently used to detect higher risk disease in patients already on surveillance. CONCLUSION: Although there is an ongoing debate regarding the precise nature of its optimal implementation, mpMRI is a promising risk stratification tool and should be considered for men on AS

    Targeting cells with single vectors using multiple-feature Boolean logic

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    Precisely defining the roles of specific cell types is an intriguing frontier in the study of intact biological systems and has stimulated the rapid development of genetically encoded tools for observation and control. However, targeting these tools with adequate specificity remains challenging: most cell types are best defined by the intersection of two or more features such as active promoter elements, location and connectivity. Here we have combined engineered introns with specific recombinases to achieve expression of genetically encoded tools that is conditional upon multiple cell-type features, using Boolean logical operations all governed by a single versatile vector. We used this approach to target intersectionally specified populations of inhibitory interneurons in mammalian hippocampus and neurons of the ventral tegmental area defined by both genetic and wiring properties. This flexible and modular approach may expand the application of genetically encoded interventional and observational tools for intact-systems biology
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