Revisiting a pollen-transmitted ilarvirus previously associated with angular mosaic of grapevine

We report the characterization of a novel tri-segmented RNA virus infecting Mercurialis annua, a common crop weed and model species in plant science. The virus, named "Mercurialis latent virus" (MeLaV) was first identified in a mixed infection with the recently described Mercurialis orthotospovirus 1 (MerV1) on symptomatic plants grown in glasshouses in Lausanne (Switzerland). Both viruses were found to be transmitted by Thrips tabaci, which presumably help the inoculation of infected pollen in the case of MeLaV. Complete genome sequencing of the latter revealed a typical ilarviral architecture and close phylogenetic relationship with members of the Ilarvirus subgroup 1. Surprisingly, a short portion of MeLaV replicase was found to be identical to the partial sequence of grapevine angular mosaic virus (GAMV) reported in Greece in the early 1990s. However, we have compiled data that challenge the involvement of GAMV in angular mosaic of grapevine, and we propose alternative causal agents for this disorder. In parallel, three highly-conserved MeLaV isolates were identified in symptomatic leaf samples in The Netherlands, including a herbarium sample collected in 1991. The virus was also traced in diverse RNA sequencing datasets from 2013-2020, corresponding to transcriptomic analyses of M. annua and other plant species from five European countries, as well as metaviromics analyses of bees in Belgium. Additional hosts are thus expected for MeLaV, yet we argue that infected pollen grains have likely contaminated several sequencing datasets and may have caused the initial characterization of MeLaV as GAMV

First case of meningoencephalitis and bacteraemia with Flavobacterium lindanitolerans

Purpose: Flavobacterium lindanitolerans is an environmental Gram-negative, non-spore-forming rod which is usually not considered to be a human pathogen. Isolation from human clinical samples has been described only once. We report the first case of meningoencephalitis and bacteraemia with Flavobacterium lindanitolerans. Case description: A 76-year-old female presented with fever, headache, alteration of mental status, marked meningism and dysarthria. A lumbar puncture demonstrated cerebrospinal fluid findings consistent with bacterial meningitis, and a broad-spectrum antibiotic therapy was initiated. Blood and cerebrospinal fluid cultures revealed a growth of Flavobacterium lindanitolerans. Based on antimicrobial susceptibilities testing, antibiotic treatment was changed to levofloxacin, resulting in a remission of the clinical symptoms after 21 days of treatment. Conclusion: Flavobacterium species are extremely rare human pathogens. However, some of them have been reported to cause opportunistic infections. We describe the first case of meningoencephalitis and bacteraemia caused by Flavobacterium lindanitolerans which was effectively treated with levofloxacin for 21 days

Multidimensional signals and analytic flexibility: Estimating degrees of freedom in human speech analyses

Recent empirical studies have highlighted the large degree of analytic flexibility in data analysis which can lead to substantially different conclusions based on the same data set. Thus, researchers have expressed their concerns that these researcher degrees of freedom might facilitate bias and can lead to claims that do not stand the test of time. Even greater flexibility is to be expected in fields in which the primary data lend themselves to a variety of possible operationalizations. The multidimensional, temporally extended nature of speech constitutes an ideal testing ground for assessing the variability in analytic approaches, which derives not only from aspects of statistical modeling, but also from decisions regarding the quantification of the measured behavior. In the present study, we gave the same speech production data set to 46 teams of researchers and asked them to answer the same research question, resulting insubstantial variability in reported effect sizes and their interpretation. Using Bayesian meta-analytic tools, we further find little to no evidence that the observed variability can be explained by analysts’ prior beliefs, expertise or the perceived quality of their analyses. In light of this idiosyncratic variability, we recommend that researchers more transparently share details of their analysis, strengthen the link between theoretical construct and quantitative system and calibrate their (un)certainty in their conclusions