Serum MicroRNA Expression Profile Distinguishes Enterovirus 71 and Coxsackievirus 16 Infections in Patients with Hand-Foot-and-Mouth Disease

Altered circulating microRNA (miRNA) profiles have been noted in patients with microbial infections. We compared host serum miRNA levels in patients with hand-foot-and-mouth disease (HFMD) caused by enterovirus 71 (EV71) and coxsackievirus 16 (CVA16) as well as in other microbial infections and in healthy individuals. Among 664 different miRNAs analyzed using a miRNA array, 102 were up-regulated and 26 were down-regulated in sera of patients with enteroviral infections. Expression levels of ten candidate miRNAs were further evaluated by quantitative real-time PCR assays. A receiver operating characteristic (ROC) curve analysis revealed that six miRNAs (miR-148a, miR-143, miR-324-3p, miR-628-3p, miR-140-5p, and miR-362-3p) were able to discriminate patients with enterovirus infections from healthy controls with area under curve (AUC) values ranged from 0.828 to 0.934. The combined six miRNA using multiple logistic regression analysis provided not only a sensitivity of 97.1% and a specificity of 92.7% but also a unique profile that differentiated enterovirial infections from other microbial infections. Expression levels of five miRNAs (miR-148a, miR-143, miR-324-3p, miR-545, and miR-140-5p) were significantly increased in patients with CVA16 versus those with EV71 (p<0.05). Combination of miR-545, miR-324-3p, and miR-143 possessed a moderate ability to discrimination between CVA16 and EV71 with an AUC value of 0.761. These data indicate that sera from patients with different subtypes of enteroviral infection express unique miRNA profiles. Serum miRNA expression profiles may provide supplemental biomarkers for diagnosing and subtyping enteroviral HFMD infections

AMPA Receptor Surface Expression Is Regulated by S-Nitrosylation of Thorase and Transnitrosylation of NSF

Umanah et al. show that the S-nitrosylation of Thorase and the transnitrosylation of NSF are responsible for NMDAR-activated trafficking of AMPARs underlying synaptic plasticity. © 2020 The Author(s) The regulation of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) trafficking affects multiple brain functions, such as learning and memory. We have previously shown that Thorase plays an important role in the internalization of AMPARs from the synaptic membrane. Here, we show that N-methyl-D-aspartate receptor (NMDAR) activation leads to increased S-nitrosylation of Thorase and N-ethylmaleimide-sensitive factor (NSF). S-nitrosylation of Thorase stabilizes Thorase-AMPAR complexes and enhances the internalization of AMPAR and interaction with protein-interacting C kinase 1 (PICK1). S-nitrosylated NSF is dependent on the S-nitrosylation of Thorase via trans-nitrosylation, which modulates the surface insertion of AMPARs. In the presence of the S-nitrosylation-deficient C137L Thorase mutant, AMPAR trafficking, long-term potentiation, and long-term depression are impaired. Overall, our data suggest that both S-nitrosylation and interactions of Thorase and NSF/PICK1 are required to modulate AMPAR-mediated synaptic plasticity. This study provides critical information that elucidates the mechanism underlying Thorase and NSF-mediated trafficking of AMPAR complexes. © 2020 The Author(s)1

Draft genome sequence of the mulberry tree Morus notabilis

Human utilization of the mulberry–silkworm interaction started at least 5,000 years ago and greatly influenced world history through the Silk Road. Complementing the silkworm genome sequence, here we describe the genome of a mulberry species Morus notabilis. In the 330-Mb genome assembly, we identify 128 Mb of repetitive sequences and 29,338 genes, 60.8% of which are supported by transcriptome sequencing. Mulberry gene sequences appear to evolve ~3 times faster than other Rosales, perhaps facilitating the species’ spread worldwide. The mulberry tree is among a few eudicots but several Rosales that have not preserved genome duplications in more than 100 million years; however, a neopolyploid series found in the mulberry tree and several others suggest that new duplications may confer benefits. Five predicted mulberry miRNAs are found in the haemolymph and silk glands of the silkworm, suggesting interactions at molecular levels in the plant–herbivore relationship. The identification and analyses of mulberry genes involved in diversifying selection, resistance and protease inhibitor expressed in the laticifers will accelerate the improvement of mulberry plants

Identifying intentional injuries among children and adolescents based on Machine Learning.

BackgroundCompared to other studies, the injury monitoring of Chinese children and adolescents has captured a low level of intentional injuries on account of self-harm/suicide and violent attacks. Intentional injuries in children and adolescents have not been apparent from the data. It is possible that there has been a misclassification of existing intentional injuries, and there is a lack of research literature on the misclassification of intentional injuries. This study aimed to discuss the feasibility of discriminating the intention of injury based on Machine Learning (ML) modelling and provided ideas for understanding whether there was a misclassification of intentional injuries.MethodsInformation entropy was used to determine the correlation between variables and the intention of injury, and Naive Bayes (NB), Decision Tree (DT), Random Forest (RF), Adaboost algorithms and Deep Neural Networks (DNN) were used to create an intention of injury discrimination model. The models were compared by comprehensively testing the discrimination effect to determine stability and consistency.ResultsFor the area under the ROC curve with different intentions of injuries, the NB model was 0.891, 0.880, and 0.897, respectively; the DT model was 0.870, 0.803, and 0.871, respectively; the RF model was 0.850, 0.809, and 0.845, respectively; the Adaboost model was 0.914, 0.846, and 0.914, respectively; the DNN model was 0.927, 0.835, and 0.934, respectively. In a comprehensive comparison of the five models, DNN and Adaboost models had higher values for the determination of the intention of injury. A discrimination of cases with unclear intentions of injury showed that on average, unintentional injuries, violent attacks, and self-harm/suicides accounted for 86.57%, 6.81%, and 6.62%, respectively.ConclusionIt was feasible to use the ML algorithm to determine the injury intention of children and adolescents. The research suggested that the DNN and Adaboost models had higher values for the determination of the intention of injury. This study could build a foundation for transforming the model into a tool for rapid diagnosis and excavating potential intentional injuries of children and adolescents by widely collecting the influencing factors, extracting the influence variables characteristically, reducing the complexity and improving the performance of the models in the future

Review of MAC Protocols for Vehicular Ad Hoc Networks

Vehicular ad hoc networks (VANETs) need to support the timely end-to-end transmissions of safety and non-safety messages. Medium access control (MAC) protocols can ensure fair and efficient sharing of channel resources among multiple vehicles for VANETs, which can provide timely packet transmissions and significantly improve road safety. In this paper, we review the standards of some countries for VANETs. Then, we divide the MAC protocols proposed for VANETs into single-channel MAC protocols and multi-channel MAC protocols according to the number of physical occupied spectrum resources. Both are further discussed based on their hierarchical structures, i.e., distributed and centralized structures. General design and optimization mechanisms of these commonly used MAC protocols for VANETs are reviewed. From the viewpoint of 7 aspects, we compare the advantages and disadvantages of these typical MAC protocols. Finally, we discuss the open issues to improve the MAC performance and future work on MAC design for VANETs

Recommendation Model Based on a Heterogeneous Personalized Spacey Embedding Method

The traditional heterogeneous embedding method based on a random walk strategy does not focus on the random walk fundamentally because of higher-order Markov chains. One of the important properties of Markov chains is stationary distributions (SDs). However, in large-scale network computation, SDs are not feasible and consume a lot of memory. So, we use a non-Markovian space strategy, i.e., a heterogeneous personalized spacey random walk strategy, to efficiently get SDs between nodes and skip some unimportant intermediate nodes, which allows for more accurate vector representation and memory savings. This heterogeneous personalized spacey random walk strategy was extended to heterogeneous space embedding methods in combination with vector learning, which is better than the traditional heterogeneous embedding methods for node classification tasks. As an excellent embedding method can obtain more accurate vector representations, it is important for the improvement of the recommendation model. In this article, recommendation algorithm research was carried out based on the heterogeneous personalized spacey embedding method. For the problem that the standard random walk strategy used to compute the stationary distribution consumes a large amount of memory, which may lead to inefficient node vector representation, we propose a meta-path-based heterogenous personalized spacey random walk for recommendation (MPHSRec). The meta-path-based heterogeneous personalized spacey random walk strategy is used to generate a meaningful sequence of nodes for network representation learning, and the learned embedded vectors of different meta-paths are transformed by a nonlinear fusion function and integrated into a matrix decomposition model for rating prediction. The experimental results demonstrate that MPHSRec not only improves the accuracy, but also reduces the memory cost compared with other excellent algorithms

Protective Effects of Elaeagnus angustifolia Leaf Extract against Myocardial Ischemia/Reperfusion Injury in Isolated Rat Heart

The purpose of this study is to clarify the cardioprotective property of the aqueous extract of Elaeagnus angustifolia L. leaf (EA) against myocardial ischemia/reperfusion injury in isolated rat heart. The myocardial ischemia/reperfusion (I/R) injury model of isolated rat heart was set up by the use of improved Langendorff retrograde perfusion technology. Compared with the ischemia/reperfusion (I/R) group, the aqueous extract of Elaeagnus angustifolia L. leaf (0.5 mg/mL, 1.0 mg/mL) pretreatment markedly improved the coronary flow (CF) and raised left ventricular developed pressure (LVDP) and maximum rise/down velocity (±dp/dtmax). The infarct size of the EA-treated hearts was smaller than that of I/R group. After treatment with EA, the superoxide dismutase (SOD) activity increased; malondialdehyde (MDA) and protein carbonyl content reduced more obviously (P<0.01) than that of I/R injury myocardial tissue. Conclusion. Results from the present study showed that the aqueous extract of Elaeagnus angustifolia L. leaf has obvious protective effects on myocardial I/R injury, which may be related to the improvement of myocardial oxidative stress states

The complete chloroplast genome sequence of the Pueraria lobata (Willd.) Ohwi (Leguminosae)

Pueraria lobata (Willd.) Ohwi is an essential traditional oriental medicine with therapeutic effects. In this study, we assembled the complete chloroplast genome of P. lobata. The total genome size was 153,442 bp in length, containing a large single-copy (LSC) region of 84,162 bp, a small single-copy (SSC) of 17,998 bp, and a pair of inverted repeats (IRs) of 25,641 bp, and possessing 35.41% GC content. In addition, the whole chloroplast genome encodes a total of 129 genes, including 84 protein-coding genes, 37 tRNA genes, and eight rRNA genes. Phylogenetic tree analysis of 48 species in the family Papilionoideae of Leguminosae indicated that P. lobata was belong to Papilionoideae and closely related to the genus, Pachyrhizus, Vigna and Phaseolus

Licochalcone A-Induced Human Bladder Cancer T24 Cells Apoptosis Triggered by Mitochondria Dysfunction and Endoplasmic Reticulum Stress

Licochalcone A (LCA), a licorice chalconoid, is considered to be a bioactive agent with chemopreventive potential. This study investigated the mechanisms involved in LCA-induced apoptosis in human bladder cancer T24 cells. LCA significantly inhibited cells proliferation, increased reactive oxygen species (ROS) levels, and caused T24 cells apoptosis. Moreover, LCA induced mitochondrial dysfunction, caspase-3 activation, and poly-ADP-ribose polymerase (PARP) cleavage, which displayed features of mitochondria-dependent apoptotic signals. Besides, exposure of T24 cells to LCA triggered endoplasmic reticulum (ER) stress; as indicated by the enhancement in 78 kDa glucose-regulated protein (GRP 78), growth arrest and DNA damage-inducible gene 153/C/EBP homology protein (GADD153/CHOP) expression, ER stress-dependent apoptosis is caused by the activation of ER-specific caspase-12. All the findings from our study suggest that LCA initiates mitochondrial ROS generation and induces oxidative stress that consequently causes T24 cell apoptosis via the mitochondria-dependent and the ER stress-triggered signaling pathways