The presence of extracellular microRNAs in the media of cultured Drosophila cells

While regulatory RNA pathways, such as RNAi, have commonly been described at an intracellular level, studies investigating extracellular RNA species in insects are lacking. In the present study, we demonstrate the presence of extracellular microRNAs (miRNAs) in the cell-free conditioned media of two Drosophila cell lines. More specifically, by means of quantitative real-time PCR (qRT-PCR), we analysed the presence of twelve miRNAs in extracellular vesicles (EVs) and in extracellular Argonaute-1 containing immunoprecipitates, obtained from the cell-free conditioned media of S2 and Cl. 8 cell cultures. Next-generation RNA-sequencing data confirmed our qRT-PCR results and provided evidence for selective miRNA secretion in EVs. To our knowledge, this is the first time that miRNAs have been identified in the extracellular medium of cultured cells derived from insects, the most speciose group of animals

Generation of virus- and dsRNA-derived siRNAs with species-dependent length in insects

Double-stranded RNA (dsRNA) molecules of viral origin trigger a post-transcriptional gene-silencing mechanism called RNA interference (RNAi). Specifically, virally derived dsRNA is recognized and cleaved by the enzyme Dicer2 into short interfering RNAs (siRNAs), which further direct sequence-specific RNA silencing, ultimately silencing replication of the virus. Notably, RNAi can also be artificially triggered by the delivery of gene-specific dsRNA, thereby leading to endogenous gene silencing. This is a widely used technology that holds great potential to contribute to novel pest control strategies. In this regard, research efforts have been set to find methods to efficiently trigger RNAi in the field. In this article, we demonstrate the generation of dsRNA- and/or virus-derived siRNAs-the main RNAi effectors-in six insect species belonging to five economically important orders (Lepidoptera, Orthoptera, Hymenoptera, Coleoptera, and Diptera). In addition, we describe that the siRNA length distribution is species-dependent. Taken together, our results reveal interspecies variability in the (antiviral) RNAi mechanism in insects and show promise to contribute to future research on (viral-based) RNAi-triggering mechanisms in this class of animals

Multiple imputation in Cox regression when there are time-varying effects of covariates.

In Cox regression, it is important to test the proportional hazards assumption and sometimes of interest in itself to study time-varying effects (TVEs) of covariates. TVEs can be investigated with log hazard ratios modelled as a function of time. Missing data on covariates are common and multiple imputation is a popular approach to handling this to avoid the potential bias and efficiency loss resulting from a "complete-case" analysis. Two multiple imputation methods have been proposed for when the substantive model is a Cox proportional hazards regression: an approximate method (Imputing missing covariate values for the Cox model in Statistics in Medicine (2009) by White and Royston) and a substantive-model-compatible method (Multiple imputation of covariates by fully conditional specification: accommodating the substantive model in Statistical Methods in Medical Research (2015) by Bartlett et al). At present, neither accommodates TVEs of covariates. We extend them to do so for a general form for the TVEs and give specific details for TVEs modelled using restricted cubic splines. Simulation studies assess the performance of the methods under several underlying shapes for TVEs. Our proposed methods give approximately unbiased TVE estimates for binary covariates with missing data, but for continuous covariates, the substantive-model-compatible method performs better. The methods also give approximately correct type I errors in the test for proportional hazards when there is no TVE and gain power to detect TVEs relative to complete-case analysis. Ignoring TVEs at the imputation stage results in biased TVE estimates, incorrect type I errors, and substantial loss of power in detecting TVEs. We also propose a multivariable TVE model selection algorithm. The methods are illustrated using data from the Rotterdam Breast Cancer Study. R code is provided

Implementing the sterile insect technique with RNA interference – a review

RNA interference (RNAi) of insect pests is reviewed and its potential for implementing Sterile Insect Technique (SIT)-related control is considered. The molecular mechanisms that support RNAi in pest species are reviewed in detail, drawing on literature from a range of species including Drosophila melanogaster and Homo sapiens. The underlying genes that enable RNAi are generally conserved across taxa, although variance exists in both their form and function. RNAi represents a plausible, non-GM system for targeting populations of insects for control purposes, if RNA interference (RNAi) effector molecules can be delivered environmentally (eRNAi). We consider studies of eRNAi from across several insect orders and review to what extent taxonomy, genetics and differing methods of double stranded (ds)RNA synthesis and delivery can influence the efficiency of gene knockdown. Several factors, including the secondary structure of the target mRNA and the specific nucleotide sequence of dsRNA effector molecules, can affect the potency of eRNAi. However, taxonomic relationships between insects cannot be used to reliably forecast the efficiency of an eRNAi response. The mechanisms by which insects acquire dsRNA from their environment require further research, but the evidence to date suggests that endocytosis and transport channels both play key roles. Delivery of RNA molecules packaged in intermediary carriers such as bacteria or nanoparticles may facilitate their entry into and through the gut, and enable the evasion of host defense systems, such as toxic pH, that would otherwise attenuate the potential for RNAi

The development and validation of a multivariable prognostic model to predict foot ulceration in diabetes using a systematic review and individual patient data meta-analyses

AIMS: Diabetes guidelines recommend screening for the risk of foot ulceration but vary substantially in the underlying evidence base. Our purpose was to derive and validate a prognostic model of independent risk factors for foot ulceration in diabetes using all available individual patient data from cohort studies conducted worldwide. METHODS: We conducted a systematic review and meta-analysis of individual patient data from 10 cohort studies of risk factors in the prediction of foot ulceration in diabetes. Predictors were selected for plausibility, availability and low heterogeneity. Logistic regression produced adjusted odds ratios (ORs) for foot ulceration by ulceration history, monofilament insensitivity, any absent pedal pulse, age, sex and diabetes duration. RESULTS: The 10 studies contained data from 16 385 participants. A history of foot ulceration produced the largest OR [6.59 (95% CI 2.49 to 17.45)], insensitivity to a 10 g monofilament [3.18 (95% CI 2.65 to 3.82)] and any absent pedal pulse [1.97 (95% CI 1.62 to 2.39)] were consistently, independently predictive. Combining three predictors produced sensitivities between 90.0% (95% CI 69.9% to 97.2%) and 95.3% (95% CI 84.5% to 98.7%); the corresponding specificities were between 12.1% (95% CI 8.2% to 17.3%) and 63.9% (95% CI 61.1% to 66.6%). CONCLUSIONS: This prognostic model of only three risk factors, a history of foot ulceration, an inability to feel a 10 g monofilament and the absence of any pedal pulse, compares favourably with more complex approaches to foot risk assessment recommended in clinical diabetes guidelines

Nucleases as a barrier to gene silencing in the cotton boll weevil, Anthonomus grandis.

Made available in DSpace on 2018-01-04T23:23:41Z (GMT). No. of bitstreams: 1 journal.pone.0189600.pdf: 7131320 bytes, checksum: ece3da5d8a008843e58701868100618d (MD5) Previous issue date: 2018-01-04bitstream/item/170309/1/journal.pone.0189600.pd

Estimating an individual's probability of revision surgery after knee replacement : a comparison of modeling approaches using a national dataset

Tools that provide personalized risk prediction of the outcomes after surgical procedures help patients to make preference-based decisions amongst the available treatment options. However, it is unclear which modeling approach provides the most accurate risk estimation. We constructed and compared several parametric and non-parametric models for predicting prosthesis survivorship after knee replacement surgery for osteoarthritis. We used 430,455 patient-procedure episodes between April 2003 and September 2015 from the National Joint Registry for England, Wales, Northern Ireland and the Isle of Man. The flexible parametric survival and random survival forest models most accurately captured the observed probability of remaining event-free. The concordance index for the flexible parametric model was the highest (0.705; 95% confidence interval: 0.702, 0.707) for total knee replacement, 0.639 (95% confidence interval: 0.634, 0.643) for unicondylar knee replacement and 0.589 (95% confidence interval: 0.586, 0.592) for patellofemoral replacement. The observed-to-predicted ratios for both the flexible parametric and the random survival forest approaches indicated that models tended to underestimate the risks for most risk groups. Our results show that the flexible parametric model has a better overall performance compared to other tested parametric methods, and better discrimination compared to the random survival forest approach

Characterization of fossilized relatives of the White Spot Syndrome Virus in genomes of decapod crustaceans

$\bf Background:$ The White Spot Syndrome Virus (WSSV) is an important pathogen that infects a variety of decapod species and causes a highly contagious disease in penaeid shrimps. Mass mortalities caused by WSSV have pronounced commercial impact on shrimp aquaculture. Until now WSSV is the only known member of the virus family Nimaviridae, a group with obscure phylogenetic affinities. Its isolated position makes WSSV studies challenging due to large number of genes without homology in other viruses or cellular organisms. $\bf Results:$ Here we report the discovery of an unusually large amount of sequences with high similarity to WSSV in a genomic library from the Jamaican bromeliad crab $\textit {Metopaulias depressus}$. $\textit {De novo}$ assembly of these sequences allowed for the partial reconstruction of the genome of this endogenized virus with total length of 200 kbp encompassed in three scaffolds. The genome includes at least 68 putative open reading frames with homology in WSSV, most of which are intact. Among these, twelve orthologs of WSSV genes coding for non-structural proteins and nine genes known to code for the major components of the WSSV virion were discovered. Together with reanalysis of two similar cases of WSSV-like sequences in penaeid shrimp genomic libraries, our data allowed comparison of gene composition and gene order between different lineages related to WSSV. Furthermore, screening of published sequence databases revealed sequences with highest similarity to WSSV and the newly described virus in genomic libraries of at least three further decapod species. Analysis of the viral sequences detected in decapods suggests that they are less a result of contemporary WSSV infection, but rather originate from ancestral infection events. Phylogenetic analyses suggest that genes were acquired repeatedly by divergent viruses or viral strains of the Nimaviridae. $\bf Conclusions:$ Our results shed new light on the evolution of the Nimaviridae and point to a long association of this viral group with decapod crustaceans