Response of Three Kinds of Detoxifying Enzymes from Odontotermes formosanus (Shiraki) to the Stress Caused by Serratia marcescens Bizio (SM1)

Subterranean termite Odontotermes formosanus (Shiraki) (Blattodea: Isoptera: Termitidae), is a pest species found in forests and dams. Serratia marcescens Bizio (SM1) has a potential pathogenic effect on O. formosanus. However, the response of detoxifying enzymes to exposure by S. marcescens in O. formosanus has not been studied. In the present work, 20 detoxifying enzyme genes, including 6 glutathione S-transferases (GSTs), 5 UDP glycosyltransferases (UGTs) and 9 Cytochrome P450s (CYPs), were identified from the O. formosanus transcriptome dataset by bioinformatics analysis. Furthermore, the effects of SM1 infection on the transcription levels of detoxifying enzyme genes (GSTs, UGTs and CYPs) in O. formosanus were determined. The results showed that the expression of all detoxifying enzyme gene, except one GST, in O. formosanus were altered in response to the infection by SM1. The response of GSTs, UGTs and CYPs to SM1 in O. formosanus suggested that they may play an important role in the defense against bacterial infection such as SM1, and implies that termites have evolved a complex immune response to potential pathogens

Equilibrium Melting Temperature of Polymorphic Poly(L-lactide) and Its Supercooling Dependence on Growth Kinetics

In this study, the isothermal crystallization process of poly(l-lactide) (PLLA) has been investigated using in situ XRD, differential scanning calorimetry (DSC), and polarized optical microscopy (POM). Linear and nonlinear extrapolation methods have been deployed to estimate the equilibrium melting temperature ( T m 0 ), which is used for analyzing the supercooling dependence of the PLLA spherulitic growth rate (G). A double-melting behavior observed for PLLA under crystallization Tc < 120 °C has been attributed to the formation of both α′ and α crystals. The T m 0 values of both α′ and α crystals have been evaluated using the linear method (172.8 °C) and nonlinear method (196.4 °C), with the nonlinear estimate being 23.6 °C higher. A discontinuity in the temperature dependence of spherulite growth rate is observed around 128.3 °C. Regime II–III transition is found to occur at 128.3 °C when T m 0 = 196.4 °C as estimated by the nonlinear extrapolation method

City branding in China's Northeastern region

The past decade has seen a surge in the use of city branding, which is used to attract specific target groups of investors, high-tech green firms and talented workforce and reflects a desired shift from old, polluting manufacturing industries to new, clean service industries. Previous studies in the Chinese mega-city regions Pearl River Delta, Yangtze River Delta a

Performing group-level functional image analyses based on homologous functional regions mapped in individuals

Functional MRI (fMRI) studies have traditionally relied on intersubject normalization based on global brain morphology, which cannot establish proper functional correspondence between subjects due to substantial intersubject variability in functional organization. Here, we reliably identified a set of discrete, homologous functional regions in individuals to improve intersubject alignment of fMRI data. These functional regions demonstrated marked intersubject variability in size, position, and connectivity. We found that previously reported intersubject variability in functional connectivity maps could be partially explained by variability in size and position of the functional regions. Importantly, individual differences in network topography are associated with individual differences in task-evoked activations, suggesting that these individually specified regions may serve as the localizer to improve the alignment of task-fMRI data. We demonstrated that aligning task-fMRI data using the regions derived from resting state fMRI may lead to increased statistical power of task-fMRI analyses. In addition, resting state functional connectivity among these homologous regions is able to capture the idiosyncrasies of subjects and better predict fluid intelligence (gF) than connectivity measures derived from group-level brain atlases. Critically, we showed that not only the connectivity but also the size and position of functional regions are related to human behavior. Collectively, these findings suggest that identifying homologous functional regions across individuals can benefit a wide range of studies in the investigation of connectivity, task activation, and brain-behavior associations. Author summary No two individuals are alike. The size, shape, position, and connectivity patterns of brain functional regions can vary drastically between individuals. While interindividual differences in functional organization are well recognized, to date, standard procedures for functional neuroimaging research still rely on aligning different subjects' data to a nominal average brain based on global brain morphology. We developed an approach to reliably identify homologous functional regions in each individual and demonstrated that aligning data based on these homologous functional regions can significantly improve the study of resting state functional connectivity, task-fMRI activations, and brain-behavior associations. Moreover, we showed that individual differences in size, position, and connectivity of brain functional regions are dissociable, and each can provide nonredundant information in explaining human behavior

Identification of membrane protein types via deep residual hypergraph neural network

A membrane protein's functions are significantly associated with its type, so it is crucial to identify the types of membrane proteins. Conventional computational methods for identifying the species of membrane proteins tend to ignore two issues: High-order correlation among membrane proteins and the scenarios of multi-modal representations of membrane proteins, which leads to information loss. To tackle those two issues, we proposed a deep residual hypergraph neural network (DRHGNN), which enhances the hypergraph neural network (HGNN) with initial residual and identity mapping in this paper. We carried out extensive experiments on four benchmark datasets of membrane proteins. In the meantime, we compared the DRHGNN with recently developed advanced methods. Experimental results showed the better performance of DRHGNN on the membrane protein classification task on four datasets. Experiments also showed that DRHGNN can handle the over-smoothing issue with the increase of the number of model layers compared with HGNN. The code is available at https://github.com/yunfighting/Identification-of-Membrane-Protein-Types-via-deep-residual-hypergraph-neural-network

Genome-wide gene phylogeny of CIPK family in cassava and expression analysis of partial drought-induced genes

Cassava is an important food and potential biofuel crop that is tolerant to multiple abiotic stressors. The mechanisms underlying these tolerances are currently less known. CBL-interacting protein kinases (CIPKs) have been shown to play crucial roles in plant developmental processes, hormone signaling transduction, and in the response to abiotic stress. However, no data is currently available about the CPK family in cassava. In this study, a total of 25 CIPK genes were identified from cassava genome based on our previous genome sequencing data. Phylogenetic analysis suggested that 25 MeCIPKs could be classified into four subfamilies, which was supported by exon-intron organizations and the architectures of conserved protein motifs. Transcriptomic analysis of a wild subspecies and two cultivated varieties showed that most MeCIPKs had different expression patterns between wild subspecies and cultivatars in different tissues or in response to drought stress. Some orthologous genes involved in CIPK interaction networks were identified between Arabidopsis and cassava. The interaction networks and co-expression patterns of these orthologous genes revealed that the crucial pathways controlled by CIPK networks may be involved in the differential response to drought stress in different accessions of cassava. Nine MeCIPK genes were selected to investigate their transcriptional response to various stimuli and the results showed the comprehensive response of the tested MeCIPK genes to osmotic, salt, cold, oxidative stressors, and ABA signaling. The identification and expression analysis of CIPK family suggested that CIPK genes are important components of development and multiple signal transduction pathways in cassava. The findings of this study will help lay a foundation for the functional characterization of the CIPK gene family and provide an improved understanding of abiotic stress responses and signaling transduction in cassava