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Tea (Camellia sinensis L.) leaves synthesize and concentrate a vast array of galloylated catechins (e.g., EGCG and ECG) and non-galloylated catechins (e.g., EGC, catechin, and epicatechin), together constituting 8%–24% of the dry leaf mass. Galloylated catechins account for a major portion of soluble catechins in tea leaves (up to 75%) and make a major contribution to the astringency and bitter taste of the green tea, and their pharmacological activity for human health. However, the catechin galloylation mechanism in tea plants is largely unknown at molecular levels. Previous studies indicated that glucosyltransferases and serine carboxypeptidase-like acyltransferases (SCPL) might be involved in the process. However, details about the roles of SCPLs in the biosynthesis of galloylated catechins remain to be elucidated. Here, we performed the genome-wide identification of SCPL genes in the tea plant genome. Several SCPLs were grouped into clade IA, which encompasses previously characterized SCPL-IA enzymes with an acylation function. Twenty-eight tea genes in this clade were differentially expressed in young leaves and vegetative buds. We characterized three SCPL-IA enzymes (CsSCPL11-IA, CsSCPL13-IA, CsSCPL14-IA) with galloylation activity toward epicatechins using recombinant enzymes. Not only the expression levels of these SCPLIA genes coincide with the accumulation of galloylated catechins in tea plants, but their recombinant enzymes also displayed β-glucogallin:catechin galloyl acyltransferase activity. These findings provide the first insights into the identities of genes encoding glucogallin:catechin galloyl acyltransferases with an active role in the biosynthesis of galloylated catechins in tea plants.

The paper presents bamboo scrimber bars as a reinforcing material instead of steel reinforcement in low-strength concrete columns. Twelve short concrete columns with different reinforcements are tested under axial compression load to study the axial compressive behavior of short concrete columns reinforced by bamboo scrimber. Three columns are reinforced concrete columns, and the other nine columns are bamboo scrimber reinforced concrete columns. The failure process, bearing capacity, axial deformation, and strain of the specimens are compared and analyzed. The results show that the bonding performance between the bamboo scrimber bars by surface treatment and low-strength concrete is excellent. In low-strength concrete columns, the material properties of bamboo bars play more thoroughly than those of steel bars. When the bamboo reinforcement ratio is increased, the concrete column ductility is significantly improved, but the bearing capacity of the concrete column is not increased. The bamboo scrimber bars with the size of 10 mm × 10 mm or 15 mm × 15 mm can be used as longitudinal bars of low-strength concrete columns. The ductility of the short concrete column with 2.56% bamboo scrimber reinforcement is close to that of the short concrete column with 0.72% steel reinforcement.

Abstract Background Many viruses depend on the extensive membranous network of the endoplasmic reticulum (ER) for their translation, replication, and packaging. Certain membrane modifications of the ER can be a trigger for ER stress, as well as the accumulation of viral protein in the ER by viral infection. Then, unfolded protein response (UPR) is activated to alleviate the stress. Zika virus (ZIKV) is a mosquito-borne flavivirus and its infection causes microcephaly in newborns and serious neurological complications in adults. Here, we investigated ER stress and the regulating model of UPR in ZIKV-infected neural cells in vitro and in vivo. Methods Mice deficient in type I and II IFN receptors were infected with ZIKV via intraperitoneal injection and the nervous tissues of the mice were assayed at 5 days post-infection. The expression of phospho-IRE1, XBP1, and ATF6 which were the key markers of ER stress were analyzed by immunohistochemistry assay in vivo. Additionally, the nuclear localization of XBP1s and ATF6n were analyzed by immunohistofluorescence. Furthermore, two representative neural cells, neuroblastoma cell line (SK-N-SH) and astrocytoma cell line (CCF-STTG1), were selected to verify the ER stress in vitro. The expression of BIP, phospho-elF2α, phospho-IRE1, and ATF6 were analyzed through western blot and the nuclear localization of XBP1s was performed by confocal immunofluorescence microscopy. RT-qPCR was also used to quantify the mRNA level of the UPR downstream genes in vitro and in vivo. Results ZIKV infection significantly upregulated the expression of ER stress markers in vitro and in vivo. Phospho-IRE1 and XBP1 expression significantly increased in the cerebellum and mesocephalon, while ATF6 expression significantly increased in the mesocephalon. ATF6n and XBP1s were translocated into the cell nucleus. The levels of BIP, ATF6, phospho-elf2α, and spliced xbp1 also significantly increased in vitro. Furthermore, the downstream genes of UPR were detected to investigate the regulating model of the UPR during ZIKV infection in vitro and in vivo. The transcriptional levels of atf4, gadd34, chop, and edem-1 in vivo and that of gadd34 and chop in vitro significantly increased. Conclusion Findings in this study demonstrated that ZIKV infection activates ER stress in neural cells. The results offer clues to further study the mechanism of neuropathogenesis caused by ZIKV infection.

Abstract Background Strigolactones (SLs) play important roles in controlling root growth, shoot branching, and plant-symbionts interaction. Despite the importance, the components of SL biosynthesis and signaling have not been unequivocally explored in soybean. Results Here we identified the putative components of SL synthetic enzymes and signaling proteins in soybean genome. Soybean genome contains conserved MORE AXILLARY BRANCHING (MAX) orthologs, GmMAX1s, GmMAX2s, GmMAX3s, and GmMAX4s. The tissue expression patterns are coincident with SL synthesis in roots and signaling in other tissues under normal conditions. GmMAX1a, GmMAX2a, GmMAX3b, and GmMAX4a expression in their Arabidopsis orthologs’ mutants not only restored most characteristic phenotypes, such as shoot branching and shoot height, leaf shape, primary root length, and root hair growth, but also restored the significantly changed hormone contents, such as reduced JA and ABA contents in all mutant leaves, but increased auxin levels in atmax1, atmax3 and atmax4 mutants. Overexpression of these GmMAXs also altered the hormone contents in wild-type Arabidopsis. GmMAX3b was further characterized in soybean nodulation with overexpression and knockdown transgenic hairy roots. GmMAX3b overexpression (GmMAX3b-OE) lines exhibited increased nodule number while GmMAX3b knockdown (GmMAX3b-KD) decreased the nodule number in transgenic hairy roots. The expression levels of several key nodulation genes were also altered in GmMAX3b transgenic hairy roots. GmMAX3b overexpression hairy roots had reduced ABA, but increased JA levels, with no significantly changed auxin content, while the contrast changes were observed in GmMAX3b-KD lines. Global gene expression in GmMAX3b-OE or GmMAX3b-KD hairy roots also revealed that altered expression of GmMAX3b in soybean hairy roots changed several subsets of genes involved in hormone biosynthesis and signaling and transcriptional regulation of nodulation processes. Conclusions This study not only revealed the conservation of SL biosynthesis and signaling in soybean, but also showed possible interactions between SL and other hormone synthesis and signaling during controlling plant development and soybean nodulation. GmMAX3b-mediated SL biosynthesis and signaling may be involved in soybean nodulation by affecting both root hair formation and its interaction with rhizobia.

The data center has become the infrastructure of most Internet services, and its network carries different types of business flow, such as query, data backup, control information, etc. At the same time, the throughput-sensitive large flows occupy a lot of bandwidth, resulting in the small flow’s longer completion time, finally affecting the performance of the applications. Recent proposals consider only dynamically adjusting the ECN threshold or reversing the ECN packet priority. This paper combines these two improvements and presents the HDCQ method for coordinating data center queuing, separating large and small flows, and scheduling in order to ensure flow completion time. It uses the ECN mechanism to design load-adaptive marking threshold update algorithms for small flows to prevent micro-bursts from occurring. At the same time, packets marked with ECN or ACK are raised in priority, prompting these packets to be fed back to the sender as soon as possible, effectively reducing the TCP control loop delay. Extensive experimental analysis on the network simulator (NS-2) shows that the HDCQ algorithm has better performance in the face of micro-burst traffic, reducing the average flow completion time by up to 24% compared with the PIAS.

The increase in network applications diversity and different service quality requirements lead to service differentiation, making it more important than ever. In Wide Area Network (WAN), the non-responsive Long-Term Fast (LTF) flows are the main contributors to network congestion. Therefore, detecting and suppressing non-responsive LTF flows represent one of the key points for providing data transmission with controllable delay and service differentiation. However, the existing single-queue management algorithms are designed to serve only a small number of applications with similar requirements (low latency, high throughput, etc.). The lack of mechanisms to distinguish different traffic makes it difficult to implement differentiated services. This paper proposes an active queue management scheme, namely, SQM-LRU, which realizes service differentiation based on Shadow Queue (SQ) and improved Least-Recently-Used (LRU) strategy. The algorithm consists of three essential components: First, the flow detection module is based on the SQ and improved LRU. This module is used to detect non-responsive LTF flows. Second, different flows will be put into corresponding high or low priority sub-queues depending on the flow detection results. Third, the dual-queue adopts CoDel and RED, respectively, to manage packets. SQM-LRU intends to satisfy the stringent delay requirements of responsive flow while maximizing the throughput of non-responsive LTF flow. Our simulation results show that SQM-LRU outperforms traditional solutions with significant improvement in flow detection and reduces the delay, jitter, and Flow Completion Time (FCT) of responsive flow. As a result, it reduced the FCT by up to 50% and attained 95% of the link utilization. Additionally, the low overhead and the operations incur O(1) cost per packet, making it practical for the real network.

As one of the key factors that limit the development of vanadium redox flow battery (VRFB), the positive redox couple of VO2+/VO2+ plays an important role on the overall performance of VRFB. To improve the kinetics of a positive reaction, a new designed nitrogen-doped reduced graphene oxide-modified graphite felt (N-rGO/GF) electrode was prepared by coupling the methods of freeze-drying and pyrolysis. The characteristics of the prepared electrode were measured by scanning electron microscope (SEM), Brunauer–Emmett–Teller (BET) analysis, Raman spectroscopy (Raman), X-ray diffraction (XRD), cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and charge-discharge tests. By coupling the methods of freeze-drying and pyrolysis, the N-rGO can be evenly dispersed on the surface of GF electrode, resulting in an excellent catalytic activity. The results demonstrate that the proposed N-rGO/GF electrode with pyrolysis temperature of 900°C shows excellent electrochemical performance and significantly improves the catalytic activity and electrochemical reversibility for the positive VO2+/VO2+ reaction, indicating that the proposed composite electrode has potential applications in the improvement of VRFB performance.

A new lightweight traffic sign detection algorithm based on YOLOv4 has been proposed to address the time-consuming issue of existing algorithms when training more parameters. The algorithm involves several key improvements to YOLOv4's backbone network and feature pyramid. Specifically, MobileNetv3 is used as the backbone feature extraction network, replacing standard convolution with depthwise separable convolution to reduce the number of parameters and computation in both the backbone network and feature pyramid. Furthermore, two SPP modules are added to the feature pyramid part to improve the detection accuracy of the model. The MobileNetv3 network is also improved by dropping the modules after layer 17 and performing PW (PointWise) convolution operations on feature layers to convert their dimensions and connect them with the detection layer. Finally, the a priori frame is initialized by applying the K-means++ algorithm to further enhance the detection accuracy of the algorithm. Experimental results on the CCTSDB dataset indicate that the proposed algorithm achieves a 1.7% increase in mAP (mean average precision), reduces the parameter amount by 197M, and increases detection speed by 25% compared to YOLOv4. These results demonstrate that the improved lightweight algorithm performs exceptionally well in traffic sign detection. [ABSTRACT FROM AUTHOR]