Comparative plant transcriptome profiling of Arabidopsis and Camelina infested with Myzus persicae aphids acquiring circulative and non-circulative viruses reveals virus- and plant-specific alterations relevant to aphid feeding behavior and transmission

Background: Evidence accumulates that plant viruses alter host-plant traits in ways that modify their insect vectors' behavior. These alterations often enhance virus transmission, which has led to the hypothesis that these effects are manipulations caused by viral adaptation. However, the genetic basis of these indirect, plant-mediated effects on vectors and their dependence on the plant host and the mode of virus transmission is hardly known. Results: Transcriptome profiling of Arabidopsis thaliana and Camelina sativa plants infected with turnip yellows virus (TuYV) or cauliflower mosaic virus (CaMV) and infested with the common aphid vector Myzus persicae revealed strong virus- and host-specific differences in the gene expression patterns. CaMV infection caused more severe effects on the phenotype of both plant hosts than did TuYV infection, and the severity of symptoms correlated strongly with the proportion of differentially expressed genes, especially photosynthesis genes. Accordingly, CaMV infection modified aphid behavior and fecundity stronger than did infection with TuYV. Conclusions: Overall, infection with CaMV — relying on the non-circulative transmission mode — tends to have effects on metabolic pathways with strong potential implications for insect-vector / plant-host interactions (e.g. photosynthesis, jasmonic acid, ethylene and glucosinolate biosynthetic processes), while TuYV — using the circulative transmission mode — alters these pathways only weakly. These virus-induced deregulations of genes that are related to plant physiology and defense responses might impact aphid probing and feeding behavior on both infected host plants, with potentially distinct effects on virus transmission. Keywords: Caulimovirus, polerovirus, aphid vector, transmission, feeding behavior, insect-plant interactions, transcriptome profiling, RNA-seq.

Visual syntax in social media

Modern technologies have fundamentally changed the sphere of communication. One of the interesting social media characteristics is the prevalence of the visual transmission mode. Regardless of the fact that photo-rhetoric in social networks usually lacks complexity and is often limited to the statement of facts, there exist more complex forms of visual syntax. The article analyses the options for creating a twofold semantic conception of images, enabling communication to expand temporally. Moreover, there have been demonstrated the visual metaphors in social networks as exemplified by 2020 gestalt.

Multiplexed Conformationally-Selective, Localized Gas-Phase Hydrogen Deuterium Exchange of Protein Ions Enabled by Transmission-Mode Electron Capture Dissociation

In this article, we present an approach for conformationally multiplexed localized hydrogen deuterium exchange (HDX) of gas-phase protein ions facilitated by ion mobility (IM) followed by electron capture dissociation (ECD). A quadrupole-ion mobility-time of flight instrument previously modified to enable ECD in transmission mode (without ion trapping) immediately following a mobility separation was further modified to allow for deuterated ammonia (ND3) to be leaked in after m/z selection. Collisional activation was minimized to prevent deuterium scrambling from giving structurally irrelevant results. This arrangement was demonstrated with the extensively studied protein folding models ubiquitin and cytochrome c. Ubiquitin was ionized from conditions that stabilize the native state and conditions that stabilize the partially-folded A-state. IM of deuterated ubiquitin 6+ ions allowed the separation of more compact conformers from more extended conformers. ECD of the separated subpopulations revealed that the more extended (later arriving) conformers had significant, localized differences in the amount of HDX observed. The 5+ charge state showed greater protection against HDX than the compact 6+ conformer, and the 11+ charge state, ionized from conditions that stabilize the A-state, showed much greater deuterium incorporation. The 7+ ions of cytochrome c ionized from aqueous conditions showed greater HDX with exterior and more unstructured regions of the protein, while interior, structured regions, especially those involved in heme binding, were more protected against exchange. These results, as well as potential future methods and experiments, are discussed herein.

Classifier Selection for the Prediction of Dominant Transmission Mode of Coronavirus Within Localities

The coronavirus disease-2019 (COVID-19) pandemic is an ongoing concern that requires research in all disciplines to tame its spread. Nine classification algorithms were selected for evaluating the most appropriate in predicting the prevalent COVID-19 transmission mode in a geographic area. These include; multinomial logistic regression, k-nearest neighbour, support vector machines, linear discriminant analysis, naïve Bayes, C5.0, bagged classification and regression trees, random forest, and stochastic gradient boosting. Five COVID-19 datasets were employed for classification. Predictive accuracy was determined using 10-fold cross validation with three repeats. The Friedman’s test was conducted and the outcome showed the performance of each algorithm is significantly different. The stochastic gradient boosting yielded the highest predictive accuracy, 81%. This finding should be valuable to health informaticians, health analysts and others regarding which machine learning tool to adopt in the efforts to detect dominant transmission mode of the virus within localities.

Classifier Selection for the Prediction of Dominant Transmission Mode of Coronavirus within Localities

The coronavirus disease-2019 (COVID-19) pandemic is an ongoing concern that requires research in all disciplines to tame its spread. Nine classification algorithms were selected for evaluating the most appropriate in predicting the prevalent COVID-19 transmission mode in a geographic area. These include; multinomial logistic regression, k-nearest neighbour, support vector machines, linear discriminant analysis, naïve Bayes, C5.0, bagged classification and regression trees, random forest, and stochastic gradient boosting. Five COVID-19 datasets were employed for classification. Predictive accuracy was determined using 10-fold cross validation with three repeats. The Friedman’s test was conducted and the outcome showed the performance of each algorithm is significantly different. The stochastic gradient boosting yielded the highest predictive accuracy, 81%. This finding should be valuable to health informaticians, health analysts and others regarding which machine learning tool to adopt in the efforts to detect dominant transmission mode of the virus within localities.

Reactions of MoCl5 with 4-Methylpyridine, 2-Methylpyridine and 1-Methylimidazole in Tetrahydrofuran

MoCl5 reactions with 4-methylpyridine/2-methylpyridine/1-methylimidazole in THF in 1:1/1:2 stoichiometric ratios, at room temperature were carried out. The following products were synthesized: MoO2Cl(C6H7N), 1;Mo2O2Cl5(C6H7N)2(C4H8O)2,2; Mo4O4Cl4(C6H7N)3(C4H8O)2, 3 and Mo2O4Cl4(C4H6N)2(C4H8O), 4. These compounds have been investigated by FT-IR (transmission mode), FT-1H NMR, FT -13C NMR, microbiological, LC-MS and elemental (C, H, N, Mo, Cl) studies. In view of the sensitivity of all the reactants and products towards oxidation/hydrolysis by air/moisture, all the reactions and products were handled using dry nitrogen atmosphere in vacuum line. LC-MS and elemental studies agree with the formulae of compounds.