Sweet Taste Signaling Functions as a Hypothalamic Glucose Sensor

Brain glucosensing is essential for normal body glucose homeostasis and neuronal function. However, the exact signaling mechanisms involved in the neuronal sensing of extracellular glucose levels remain poorly understood. Of particular interest is the identification of candidate membrane molecular sensors that would allow neurons to change firing rates independently of intracellular glucose metabolism. Here we describe for the first time the expression of the taste receptor genes Tas1r1, Tas1r2 and Tas1r3, and their associated G-protein genes, in the mammalian brain. Neuronal expression of taste genes was detected in different nutrient-sensing forebrain regions, including the paraventricular and arcuate nuclei of the hypothalamus, the CA fields and dentate gyrus of the hippocampus, the habenula, and cortex. Expression was also observed in the intra-ventricular epithelial cells of the choroid plexus. These same regions were found to express the corresponding gene products that form the heterodimeric T1R2/T1R3 and T1R1/T1R3 sweet and l-amino acid taste G-protein coupled receptors, respectively, along with the taste G-protein α-gustducin. Moreover, in vivo studies in mice demonstrated that the hypothalamic expression of taste-related genes is regulated by the nutritional state of the animal, with food deprivation significantly increasing expression levels of Tas1r1 and Tas1r2 in hypothalamus, but not in cortex. Furthermore, exposing mouse hypothalamic cells to a low-glucose medium, while maintaining normal l-amino acid concentrations, specifically resulted in higher expression levels of the sweet-associated gene Tas1r2. This latter effect was reversed by adding the non-metabolizable artificial sweetener sucralose to the low-glucose medium, indicating that taste-like signaling in hypothalamic neurons does not require intracellular glucose oxidation. Taken together, our findings suggest that the heterodimeric G-protein coupled sweet receptor T1R2/T1R3 is a candidate membrane-bound brain glucosensor

Percutaneous closure of the inadvertent subclavian artery cannulation during pacemaker implantation

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Effect of 1-MCP on storage quality and the mechanism involved in ethylene signal transduction in a new early-maturing apple variety ‘Taihangzaohong’ fruits during cold storage

1-Methylcyclopropene (1-MCP) can reduce the rate of fruit softening and prolong storage time. In this study, the fruit of a new early-maturing apple variety, ‘Taihangzaohong’, was treated with air (control), 2 μL/L 1-MCP, 100 μL/L ethylene (C 2H4) or 2 μL/L 1-MCP +100 μL/L C2H4 for 24 hours and then stored at 4 °C for 70 days. The postharvest physiological indices and the expression of 13 genes related to ethylene biosynthesis and signal transduction were monitored every 10 days. The results showed that 1-MCP can delay the softening rate and maintain the fruit quality of this early-maturing apple variety by reducing ethylene production by reducing the expression of MdACO1, MdACO2, and MdACS1, as well as by preventing ethylene signal transduction by decreasing the expression of MdETR2 and MdERS1 and increasing the expression of MdCTR1. Understanding the significant changes in these genes and their functions may help us explore the mechanisms controlling apple fruit softening and its response to exogenous 1-MCP and ethylene stimuli, as well as inhibition at the receptor level during ripening and senescence

Bacillus megaterium BMJBN02 induces the resistance of grapevine against downy mildew

Grape downy mildew caused by Plasmopara viticola is one of the most destructive diseases of grapes. All grape cultivars are susceptible to P. viticola. However, the resistance of grape plants could be induced in plant defense with some help of microbes. In this study, Bacillus megaterium BMJBN02 obtained from farmland soil was shown to regulate the resistance of grapevine against downy mildew. The salicylic acid (SA) content and the expression of pathogenesis-related (PR) genes of grapes under different treatments were examined using high-performance liquid chromatography-mass spectrometry (HPLC-MS) and reverse transcription- quantitative polymerase chain reaction (RT-qPCR), and it was found that SA content and the expression of PR genes could play a role in regulating the resistance of grapevine against downy mildew. The five-year plot experiment showed that the resistance effectiveness of isolate BMJBN02 was approximately equal to that of 0.1 % nicotinyl morpholine (commercial fungicide). Therefore, this study provides a valuable candidate method that uses B. megaterium BMJBN02 by regulating the resistance of grape against downy mildew for quality and yield of grape in commercial productivity

A Data Middleware for Obtaining Trusted Price Data for Blockchain

As a trusted middleware connecting the blockchain and the real world, the blockchain oracle can obtain trusted real-time price information for financial applications such as payment and settlement, and asset valuation on the blockchain. However, the current oracle schemes face the dilemma of security and service quality in the process of node selection, and the implicit interest relationship in financial applications leads to a significant conflict of interest between the task publisher and the executor, which reduces the participation enthusiasm of both parties and system security. Therefore, this paper proposes an anonymous node selection scheme that anonymously selects nodes with high reputations to participate in tasks to ensure the security and service quality of nodes. Then, this paper also details the interest requirements and behavioral motives of all parties in the payment settlement and asset valuation scenarios. Under the assumption of rational participants, an incentive mechanism based on the Stackelberg game is proposed. It can achieve equilibrium under the pursuit of the interests of task publishers and executors, thereby ensuring the interests of all types of users and improving the enthusiasm of participation. Finally, we verify the security of the proposed scheme through security analysis. The experimental results show that the proposed scheme can reduce the variance of obtaining price data by about 55\% while ensuring security, and meeting the interests of all parties.Comment: 12 pages,8 figure

Recommending Analogical APIs via Knowledge Graph Embedding

Library migration, which re-implements the same software behavior by using a different library instead of using the current one, has been widely observed in software evolution. One essential part of library migration is to find an analogical API that could provide the same functionality as current ones. However, given the large number of libraries/APIs, manually finding an analogical API could be very time-consuming and error-prone. Researchers have developed multiple automated analogical API recommendation techniques. Documentation-based methods have particularly attracted significant interest. Despite their potential, these methods have limitations, such as a lack of comprehensive semantic understanding in documentation and scalability challenges. In this work, we propose KGE4AR, a novel documentation-based approach that leverages knowledge graph (KG) embedding to recommend analogical APIs during library migration. Specifically, KGE4AR proposes a novel unified API KG to comprehensively and structurally represent three types of knowledge in documentation, which can better capture the high-level semantics. Moreover, KGE4AR then proposes to embed the unified API KG into vectors, enabling more effective and scalable similarity calculation. We build KGE4AR' s unified API KG for 35,773 Java libraries and assess it in two API recommendation scenarios: with and without target libraries. Our results show that KGE4AR substantially outperforms state-of-the-art documentation-based techniques in both evaluation scenarios in terms of all metrics (e.g., 47.1%-143.0% and 11.7%-80.6% MRR improvements in each scenario). Additionally, we explore KGE4AR' s scalability, confirming its effective scaling with the growing number of libraries.Comment: Accepted by FSE 202

Developing vision-based analytic algorithms and software to dynamically measure key traits in seed germination

[Objectives] Seed is one of the most important research topics in plant research. The ability of dynamically detecting key seed germination traits provides important phenotypic evidence for researchers to understand plant survival, growth, development, and reproduction. Here, we proposed a set of algorithms for quantifying germination-related traits by combining automated image analysis, graph theory and supervised machine learning techniques. [Methods] Utilizing Poaceae such as wheat (Triticum aestivum) as a model plant, we applied automated image analysis together with machine learning algorithms (e.g. K-Nearest Neighbors, Support Vector Machine, Random forests) to train foreground and background objects, followed by background segmentation and object extraction based on image series collected from three weak gluten wheat varieties. Then, graph theory and two-dimensional skeletonization were employed to dynamically analyze changes of radicles and radicle tip positions to measure key germination-related traits in a high- throughput manner. [Results] We have collected a range of phenotypic traits in this study that were difficult to obtain through traditional approaches, including seed length, width, area, perimeter, radicle and seedling length, and their growth rates. We applied a linear regression analysis to validate the computational results with manual scoring, the square of the correlation coefficient, R2, computed for traits such as radical length, radical growth rate and seedling length are 0.922 (n=188, P<0.001, ，RMSE=1.727), 0.719 (n=191, P<0.001, RMSE=0.406), 0.897 (n=115, P<0.001, RMSE=2.726), respectively. [Conclusions] The results suggest that the algorithm and open-source software presented here can reliably obtain dynamic seed germination traits, which can also be extended to other crop species such as cotton (Gossypium barbadense) and oilseed rape (Brassica napus), providing phenotypic evidence and smart analytic solutions to enable studies in plant genetics and crop breeding

Integrated transcriptome and metabolome analysis reveals the anthocyanin biosynthesis mechanisms in blueberry (Vaccinium corymbosum L.) leaves under different light qualities

IntroductionBlueberry (Vaccinium corymbosum L.) is a popular fruit with an abundance of anthocyanins in its leaves and fruits. Light is one of the pivotal environmental elements that affects plant growth and development, but the regulatory mechanism between light quality and anthocyanin formation is poorly understood.MethodsAn integrated transcriptome and metabolome analysis was performed to investigate the effects of white (control), blue (B), red (R), and red/blue (60R/40B) light on blueberry growth and reveal the potential pathway controlling anthocyanin biosynthesis in blueberry leaves.ResultsThe anthocyanin content was significantly improved by the blue and red/blue light when compared with white light, whereas there was a significant reduction in the photosynthesis under the blue light, showing an inverse trend to that of anthocyanin accumulation. Transcriptomic analysis resulted in the assembly of 134,709 unigenes. Of these, 22 were differentially expressed genes (DEGs) that participate in the anthocyanin biosynthesis pathway, with the majority being significantly up-regulated under the blue light. Most of the photosynthesis-related genes that were down-regulated were expressed during anthocyanin accumulation. Targeted metabolome profiling identified 44 metabolites associated with anthocyanin biosynthesis. The contents of most of these metabolites were higher under blue light than the other light conditions, which was consistent with the transcriptome results. The integrated transcriptome and metabolome analysis suggested that, under blue light, leucoanthocyanidin dioxygenase (LDOX), O-methyltransferase (OMT), and UDP-glucose flavonoid glucosyltransferase (UFGT) were the most significantly expressed, and they promoted the synthesis of cyanidin (Cy), malvidin (Mv), and pelargonidin (Pg) anthocyanidins, respectively. The expression levels of dihydroflavonol 4-reductase (DFR) and OMT, as well as the accumulation of delphinidin (Dp), peonidin (Pn), and petunidin (Pt), were significantly increased by the red/blue light.DiscussionThe blue and red/blue lights promoted anthocyanin biosynthesis via inducing the expression of key structural genes and accumulation of metabolites involved in anthocyanin synthesis pathway. Moreover, there was a possible feedback regulating correlation between anthocyanin biosynthesis and photosynthesis under different light qualities in blueberry leaves. This study would provide a theoretical basis for elucidating the underlying regulatory mechanism of anthocyanin biosynthesis of V. corymbosum