Epidemic forecasting provides an opportunity to predict geographic disease spread and counts when an outbreak occurs and plays a key role in preventing or controlling their adverse impact. However, conventional prediction models based on complex mathematical modelling rely on the estimation of model parameters, which yields unreliable and unsustainable results. Herein, we proposed a simple model for predicting the epidemic transmission dynamics based on nonlinear regression of the epidemic growth rate and iterative methods, which is applicable to the progression of the COVID-19 outbreak under the strict control measures of the Chinese government. Our model yields reliable and accurate results as confirmed by the available data: we predicted that the total number of infections in mainland China would be 91 253, and the maximum number of beds required for hospitalised patients would be 62 794. We inferred that the inflection point (when the growth rate turns from positive to negative) of the epidemic across China would be mid-February, and the end of the epidemic would be in late March. This model is expected to contribute to resource allocation and planning in the health sector while providing a theoretical basis for governments to respond to future global health crises or epidemics.
Thionins are antimicrobial peptides that are involved in plant defence. Here, we present an in-depth analysis of the role of rice thionin genes in defence responses against two root pathogens: the root-knot nematode Meloidogyne graminicola and the oomycete Pythium graminicola. The expression of rice thionin genes was observed to be differentially regulated by defence-related hormones, whereas all analysed genes were consistently down-regulated in M. graminicola-induced galls, at least until 7 days post-inoculation (dpi). Transgenic lines of Oryza sativa cv. Nipponbare overproducing OsTHI7 revealed decreased susceptibility to M. graminicola infection and P. graminicola colonization. Taken together, these results demonstrate the role of rice thionin genes in defence against two of the most damaging root pathogens attacking rice.
Epidemic forecasting provides an opportunity to predict geographic disease spread and counts when an outbreak occurs and plays a key role in preventing or controlling their adverse impact. However, conventional prediction models based on complex mathematical modeling rely on the estimation of model parameters, which yields unreliable and unsustainable results. Herein, we proposed a simple model for predicting the epidemic transmission dynamics based on nonlinear regression of the epidemic growth rate and iterative methods, which is applicable to the progression of the COVID-19 outbreak under the strict control measures of the Chinese government. Our model yields reliable and accurate results as confirmed by the available data: we predicted that the total number of infections in mainland China would be 91,253, and the maximum number of beds required for hospitalized patients would be 62,794. We inferred that the inflection point (when the growth rate turns from positive to negative) of the epidemic across China would be mid-February, and the end of the epidemic would be in late March. This model is expected to contribute to resourceallocation and planning in the health sector while providing a theoretical basis forgovernments to respond to future global health crises or epidemics.
Although the protein translation inhibition activity of ribosome inactivating proteins (RIPs) is well documented, little is known about the contribution of the lectin chain to the biological activity of these proteins. In this study, we compared the in vitro and intracellular activity of several S. nigra (elderberry) RIPs and non-RIP lectins. Our data demonstrate that RIPs from elderberry are much more toxic to HeLa cells than to primary fibroblasts. Differences in the cytotoxicity between the elderberry proteins correlated with differences in glycan specificity of their lectin domain, cellular uptake efficiency and intracellular destination. Despite the fact that the bulk of the RIPs accumulated in the lysosomes and partly in the Golgi apparatus, we could demonstrate effective inhibition of protein synthesis in cellula. As we also observed cytotoxicity for non-RIP lectins, it is clear that the lectin chain triggers additional pathways heralding cell death. Our data suggest that one of these pathways involves the induction of autophagy.
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