Epidemiology of rhizomania disease of sugar beet = Epidemiologie van rhizomanie bij suikerbiet

Rhizomania disease of sugar beet is caused by beet necrotic yellow vein virus (BNYVV). The virus is transmitted by the soil-borne fungus Polymyxa betae. The disease can cause severe losses in sugar yield, depending on the level of infestation in the soil, the environmental conditions during the growing season and the susceptibility of the beet cultivar. Several aspects of the epidemiology of the disease were studied. A quantitative bioassay was developed to assess inoculum potentials of virus and vector in soil. The bioassay allowed to estimate most probable numbers (MPN) of infective units of P.betae with or without virus from the incidence of infected bait plants in a dilution series of infested soil. The recovery of P.betae by bioassay, the effect of duration of the bioassay on detection level of BNYVV and the effect of soil treatments on infectivity of viruliferous resting spores of the vector were assessed. The MPN method enabled the establishment of a nonlinear relationship between inoculum potential of BNYVV in soil before sowing and disease incidence and yield parameters at harvest in an artificially infested field. In the same field, the dynamics of pathogen and vector populations during two successive beet crops in the absence or presence of drip irrigation was studied. A rapid increase of inoculum of BNYVV was found and, at the highest initial inoculum level (inoculum applied in 50 g infested soil m -2), sugar yield was reduced by 10% in the first and by 66% in the second year. Horizontal dispersal of viruliferous inoculum and spread of disease by movement of zoospores of the vector and by root growth of the host was limited to small distances. Displacement of infested soil by tillage practices resulted in spread over larger distances. Newly formed resting spores in roots of BNYVV-resistant plants were less viruliferous than those formed in roots of susceptible plants. A high level of BNYVV-resistance will be needed to reduce the build-up of virus inoculum in the field, which will contribute to the durability of disease resistance

Functional or not functional; that's the question Can we predict the diagnosis functional movement disorder based on associated features?

Background and purpose Functional movement disorders (FMDs) pose a diagnostic challenge for clinicians. Over the years several associated features have been shown to be suggestive for FMDs. Which features mentioned in the literature are discriminative between FMDs and non-FMDs were examined in a large cohort. In addition, a preliminary prediction model distinguishing these disorders was developed based on differentiating features. Method Medical records of all consecutive patients who visited our hyperkinetic outpatient clinic from 2012 to 2019 were retrospectively reviewed and 12 associated features in FMDs versus non-FMDs were compared. An independentttest for age of onset and Pearson chi-squared analyses for all categorical variables were performed. Multivariate logistic regression analysis was performed to develop a preliminary predictive model for FMDs. Results A total of 874 patients were eligible for inclusion, of whom 320 had an FMD and 554 a non-FMD. Differentiating features between these groups were age of onset, sex, psychiatric history, family history, more than one motor phenotype, pain, fatigue, abrupt onset, waxing and waning over long term, and fluctuations during the day. Based on these a preliminary predictive model was computed with a discriminative value of 91%. Discussion Ten associated features are shown to be not only suggestive but also discriminative between hyperkinetic FMDs and non-FMDs. Clinicians can use these features to identify patients suspected for FMDs and can subsequently alert them to test for positive symptoms at examination. Although a first preliminary model has good predictive accuracy, further validation should be performed prospectively in a multi-center study