Fructose-1,6-bisphosphate and aldolase mediate glucose sensing by AMPK.

The major energy source for most cells is glucose, from which ATP is generated via glycolysis and/or oxidative metabolism. Glucose deprivation activates AMP-activated protein kinase (AMPK), but it is unclear whether this activation occurs solely via changes in AMP or ADP, the classical activators of AMPK. Here, we describe an AMP/ADP-independent mechanism that triggers AMPK activation by sensing the absence of fructose-1,6-bisphosphate (FBP), with AMPK being progressively activated as extracellular glucose and intracellular FBP decrease. When unoccupied by FBP, aldolases promote the formation of a lysosomal complex containing at least v-ATPase, ragulator, axin, liver kinase B1 (LKB1) and AMPK, which has previously been shown to be required for AMPK activation. Knockdown of aldolases activates AMPK even in cells with abundant glucose, whereas the catalysis-defective D34S aldolase mutant, which still binds FBP, blocks AMPK activation. Cell-free reconstitution assays show that addition of FBP disrupts the association of axin and LKB1 with v-ATPase and ragulator. Importantly, in some cell types AMP/ATP and ADP/ATP ratios remain unchanged during acute glucose starvation, and intact AMP-binding sites on AMPK are not required for AMPK activation. These results establish that aldolase, as well as being a glycolytic enzyme, is a sensor of glucose availability that regulates AMPK.

ReIPS: A Secure Cloud-Based Reputation Evaluation System for IoT-Enabled Pumped Storage Power Stations.

Reputation evaluation is an effective measure for maintaining secure Internet of Things (IoT) ecosystems, but there are still several challenges when applied in IoT-enabled pumped storage power stations (PSPSs), such as the limited resources of intelligent inspection devices and the threat of single-point and collusion attacks. To address these challenges, in this paper we present ReIPS, a secure cloud-based reputation evaluation system designed to manage intelligent inspection devices' reputations in IoT-enabled PSPSs. Our ReIPS incorporates a resource-rich cloud platform to collect various reputation evaluation indexes and perform complex evaluation operations. To resist single-point attacks, we present a novel reputation evaluation model that combines backpropagation neural networks (BPNNs) with a point reputation-weighted directed network model (PR-WDNM). The BPNNs objectively evaluate device point reputations, which are further integrated into PR-WDNM to detect malicious devices and obtain corrective global reputations. To resist collusion attacks, we introduce a knowledge graph-based collusion device identification method that calculates behavioral and semantic similarities to accurately identify collusion devices. Simulation results show that our ReIPS outperforms existing systems regarding reputation evaluation performance, particularly in single-point and collusion attack scenarios.

The interactions and adsorption mechanisms of ternary heavy metals on boron nitride.

In this work, the interactions and adsorption mechanisms of Cu2+, Cd2+, and Ni2+ on boron nitride (BN) were tested by the simultaneous removal of metal ions from synthetic wastewater. BN was characterized using XRD, SEM, and FTIR spectroscopy. The adsorption differences between BN and the metal ions were explored through comparative studies in a single and ternary system. In the ternary system, adsorption occurs rapidly in the first 2 min for the metal ions, and the affinity order follows Cu2+>Cd2+>Ni2+. However, adsorption behavior changes due to the interaction between metal ions in the ternary system. Cu2+ showed an antagonistic effect on the adsorption of Cd2+ and Ni2+, while Cd2+ and Ni2+ produced a synergistic effect on Cu2+. In addition, the effect of metal ion concentration on the interaction between ions was studied based on a surface response experiment. An increase in Ni2+ or Cd2+ concentrations plays a synergistic effect on the adsorption of Cu2+, while an antagonistic adsorption for Ni2+ occurred with increasing Cu2+ or Cd2+ concentrations. We also discussed the various adsorption mechanisms as complexation, ion exchange, and electrostatic adsorption based on XPS analysis.

Virtual Network Embedding for Multi-Domain Heterogeneous Converged Optical Networks: Issues and Challenges.

The emerging 5G applications and the connectivity of billions of devices have driven the investigation of multi-domain heterogeneous converged optical networks. To support emerging applications with their diverse quality of service requirements, network slicing has been proposed as a promising technology. Network virtualization is an enabler for network slicing, where the physical network can be partitioned into different configurable slices in the multi-domain heterogeneous converged optical networks. An efficient resource allocation mechanism for multiple virtual networks in network virtualization is one of the main challenges referred as virtual network embedding (VNE). This paper is a survey on the state-of-the-art works for the VNE problem towards multi-domain heterogeneous converged optical networks, providing the discussion on future research issues and challenges. In this paper, we describe VNE in multi-domain heterogeneous converged optical networks with enabling network orchestration technologies and analyze the literature about VNE algorithms with various network considerations for each network domain. The basic VNE problem with various motivations and performance metrics for general scenarios is discussed. A VNE algorithm taxonomy is presented and discussed by classifying the major VNE algorithms into three categories according to existing literature. We analyze and compare the attributes of algorithms such as node and link embedding methods, objectives, and network architecture, which can give a selection or baseline for future work of VNE. Finally, we explore some broader perspectives in future research issues and challenges on 5G scenario, field trail deployment, and machine learning-based algorithms.

Lightweight and Resource-Constrained Learning Network for Face Recognition with Performance Optimization.

Despite considerable progress in face recognition technology in recent years, deep learning (DL) and convolutional neural networks (CNN) have revealed commendable recognition effects with the advent of artificial intelligence and big data. FaceNet was presented in 2015 and is able to significantly improve the accuracy of face recognition, while also being powerfully built to counteract several common issues, such as occlusion, blur, illumination change, and different angles of head pose. However, not all hardware can sustain the heavy computing load in the execution of the FaceNet model. In applications in the security industry, lightweight and efficient face recognition are two key points for facilitating the deployment of DL and CNN models directly in field devices, due to their limited edge computing capability and low equipment cost. To this end, this paper provides a lightweight learning network improved from FaceNet, which is called FN13, to break through the hardware limitation of constrained computational resources. The proposed FN13 takes the advantage of center loss to reduce the variations of the between-class features and enlarge the difference of the within-class features, instead of the triplet loss by using FaceNet. The resulting model reduces the number of parameters and maintains a high degree of accuracy, only requiring few grayscale reference images per subject. The validity of FN13 is demonstrated by conducting experiments on the Labeled Faces in the Wild (LFW) dataset, as well as an analytical discussion regarding specific disguise problems.

[Application of traditional Chinese medicine(TCM) traceability system based on TCM quality characteristics and HACCP system].

It is crucial to establish a complete set of traditional Chinese medicine(TCM) quality traceability management process system, in order to stabilize the pricing order of TCM market and reconstruct the transmission path of TCM quality signals. In this study, we reviewed the mature experience of food and drug supervision at home and abroad, analyzed the quality characteristics of TCM, and put forward that the quality control of TCM products can learn from the hazard analysis and critical control point(HACCP) system in food safety quality control. This study points out that the HACCP system provides not only technical guidance for the traceability management of TCM, but also ideas for improving the quality of TCM products and the safety risk control of TCM. The application of the HACCP system in TCM quality control can help establish an international dialogue platform for TCM and help realize the modernization and internationalization of TCM industry.

Delays in Coccidioidomycosis Diagnosis and Associated Healthcare Utilization, Tucson, Arizona, USA.

Tucson, Arizona, USA, is a highly coccidioidomycosis-endemic area. We conducted a retrospective review of 815 patients in Tucson over 2.7 years. Of 276 patients with coccidioidomycosis, 246 had a delay in diagnosis; median delay was 23 days. Diagnosis delay was associated with coccidioidomycosis-related costs totaling $589,053 and included extensive antibacterial drug use.

[Research of classical prescription based on QbD concept:optimization of extraction process for modified Siwu Decoction].

As an advanced concept in international pharmaceutical research,quality by design( QbD) can fulfill the strategic requirements of drug quality from testing to design. In this paper,the extraction process of Yanggong Prescription which was the modified Siwu Decoction was optimized based on QbD concept. With the extraction amount of solid matter,the content of ferulic acid and the content of paeoniflorin as critical quality attributes( CQAs),the failure mode and effect analysis( FMEA) was used to screen potential critical process parameters( p CPPs). The mathematical model was established by Box-Behnken experimental design to investigate the interaction between critical process parameters( CPPs) and CQAs. Then the design space for the extraction process of Yanggong Prescription was further established and optimized. Analysis of variance showed that the variance of all models was significant( P<0. 01),and the lack-of-fit value was not significant,indicating that the model was statistically significant. The relationship between various factors and the response values could be functionalized by the established models. Finally,through the optimization of the design space,the optimum extraction process of Yanggong Prescription was obtained as follows: 3 extraction times,122 minutes extraction,and 7 times of water adding. The extraction process of Yanggong Prescription based on the QbD concept was robust and reliable,which would provide guidance for the process development and quality control of its formulations.

[Study on famous prescription of prestigious traditional Chinese medicine master Lu Zhizheng based on QbD concept: optimization of extraction process and granule forming process of Meiyan Shuqi Prescription].

Based on the concept of quality by design( QbD),the design space of Meiyan Shuqi Prescription extraction process was established,and its granules forming process was optimized. The content of total flavonoids was the critical quality attribute( CQA).The amount of water,extraction time and frequency were used as the critical process parameters( CPPs). Box-Behnken experimental design was used to optimize the extraction process. The design space of Meiyan Shuqi Prescription extraction process was established and verified. The results of variance analysis showed that the P value of the quadratic regression model was less than 0. 01,which indicated that the model had a statistical significance,and the relationship between each factor and response value could be functionalized by the established model. Through further optimization of design space,the optimal extraction process of Meiyan Shuqi prescription was13-fold volume of water,extraction for 3 times and each extraction time of 1. 4 hours. Furthermore,the forming process optimized by single factor was as follows: the excipient was dextrin; the ratio of extract powder to excipient was 1 ∶1; the wetting agent was 70% ethanol; and the amount of wetting agent was 0. 3 m L·g-1. The Meiyan Shuqi Prescription extraction process and the forming process based on QbD concept provide reference for the study of other traditional Chinese medicine prescriptions.

The trapping problem of the weighted scale-free treelike networks for two kinds of biased walks.

It has been recently reported that trapping problem can characterize various dynamical processes taking place on complex networks. However, most works focused on the case of binary networks, and dynamical processes on weighted networks are poorly understood. In this paper, we study two kinds of biased walks including standard weight-dependent walk and mixed weight-dependent walk on the weighted scale-free treelike networks with a trap at the central node. Mixed weight-dependent walk including non-nearest neighbor jump appears in many real situations, but related studies are much less. By the construction of studied networks in this paper, we determine all the eigenvalues of the fundamental matrix for two kinds of biased walks and show that the largest eigenvalue has an identical dominant scaling as that of the average trapping time (ATT). Thus, we can obtain the leading scaling of ATT by a more convenient method and avoid the tedious calculation. The obtained results show that the weight factor has a significant effect on the ATT, and the smaller the value of the weight factor, the more efficient the trapping process is. Comparing the standard weight-dependent walk with mixed weight-dependent walk, although next-nearest-neighbor jumps have no main effect on the trapping process, they can modify the coefficient of the dominant term for the ATT.

Coherence analysis of a class of weighted networks.

This paper investigates consensus dynamics in a dynamical system with additive stochastic disturbances that is characterized as network coherence by using the Laplacian spectrum. We introduce a class of weighted networks based on a complete graph and investigate the first- and second-order network coherence quantifying as the sum and square sum of reciprocals of all nonzero Laplacian eigenvalues. First, the recursive relationship of its eigenvalues at two successive generations of Laplacian matrix is deduced. Then, we compute the sum and square sum of reciprocal of all nonzero Laplacian eigenvalues. The obtained results show that the scalings of first- and second-order coherence with network size obey four and five laws, respectively, along with the range of the weight factor. Finally, it indicates that the scalings of our studied networks are smaller than other studied networks when 1d

The effects of exercise on FGF21 in adults: a systematic review and meta-analysis.

Background: Fibroblast growth factor 21 (FGF21) is a key hormone factor that regulates glucose and lipid homeostasis. Exercise may regulate its effects and affect disease states. Therefore, we sought to determine how exercise affects FGF21 concentrations in adults. Methods: The review was registered in the International Prospective Systematic Review (PROSPERO, CRD42023471163). The Cochrane Library, PubMed, and Web of Science databases were searched for studies through July 2023. Studies that assessed the effects of exercise training on FGF21 concentration in adults were included. The random effect model, data with standardized mean difference (SMD), and 95% confidence intervals (CI) were used to evaluate the pooled effect size of exercise training on FGF21. The risk of heterogeneity and bias were evaluated. A total of 12 studies involving 401 participants were included. Results: The total effect size was 0.3 (95% CI [-0.3-0.89], p = 0.33) when comparing participants who exercised to those who were sedentary. However, subgroup analysis indicated that concurrent exercise and a duration ≥10 weeks significantly decreased FGF21 concentrations with an effect size of -0.38 (95% CI [-0.74--0.01], p < 0.05) and -0.38 (95% CI [-0.63--0.13], p < 0.01), respectively. Conclusion: Concurrent exercise and longer duration may be more efficient way to decrease FGF21 concentrations in adults with metabolic disorder.

Unraveling the Nanoscale Segregation Mechanism in N-Doped Niobium for Enhanced SRF Performance.

The nitrogen doping (N-doping) treatment for niobium superconducting radio-frequency (SRF) cavities is one of the key enabling technologies that support the development of more efficient future large accelerators. However, the N-doping results have diverged due to a complex chemical profile under the nitrogen-doped surface. Particularly, under industrial-scale production conditions, it is difficult to understand the underlying mechanism thus hindering performance improvement. Herein, a combination of spatially resolved and surface-sensitive approaches is employed to establish the detailed near-surface phase composition of thermally processed niobium. The results show that intermediate phase segregations, particularly the nanometric carbon-rich phase, can impede the nitridation process and limit the interactions between nitrogen and the niobium sub-surface. In comparison, the removal of the carbon-rich layer at the Nb surface leads to enhanced nitrogen binding at the Nb surface. Combining the RF test results, it is shown that the complex uniformity and grain boundary penetrations of impurity elements have a direct correlation with the mid-field quench behavior in the N-doped Nb cavities. Therefore, proper control of the nanometric intermediate phase formation in discrete thermal steps is critical in improving the ultimate performance and production yield of the Nb cavities.

Multifunctional Nano-Realgar Hydrogel for Enhanced Glioblastoma Synergistic Chemotherapy and Radiotherapy: A New Paradigm of an Old Drug.

Purpose: Realgar, as a kind of traditional mineral Chinese medicine, can inhibit multiple solid tumor growth and serve as an adjuvant drug in cancer therapy. However, the extremely low solubility and poor body absorptive capacity limit its application in clinical medicine. To overcome this therapeutic hurdle, realgar can here be fabricated into a nano-realgar hydrogel with enhanced chemotherapy and radiotherapy (RT) ability. Our objective is to evaluate the superior biocompatibility and anti-tumor activity of nano-realgar hydrogel. Methods: We have successfully synthesized nano-realgar quantum dots (QDs) coupling with 6-AN molecules (NRA QDs) and further encapsulated with a pH-sensitive dextran hydrogel carrier with hyaluronic acid coating (DEX-HA gel) to promote bioavailability, eventually forming a multifunctional nano-realgar hydrogel (NRA@DH Gel). To better investigate the tumor therapy efficiency of the NRA@DH Gel, we have established the mice in situ bearing GL261 brain glioblastoma as animal models assigned to receive intratumor injection of NRA@DH Gel. Results: The designed NRA@DH Gel as an antitumor drug can not only exert the prominent chemotherapy effect but also as a "sustainable reactive oxygen species (ROS) generator" can inhibit in the pentose phosphate pathway (PPP) metabolism and reduce the production of nicotinamide adenine dinucleotide phosphate (NADPH), thereby inhibiting the conversion of glutathione disulfide (GSSG) to glutathione (GSH), reducing GSH concentrations in tumor cells, triggering the accumulation of ROS, and finally enhancing the effectiveness of RT. Conclusion: Through the synergistic effect of chemotherapy and RT, NRA@DH Gel effectively inhibited the proliferation and migration of tumor cells, suppressed tumor growth, improved motor coordination, and prolonged survival in tumor-bearing mice. Our work aims to improve the NRA@DH Gel-mediated synergistic chemotherapy and RT will endow a "promising future" for the old drug in clinically comprehensive applications.

Discovery of Benzothiazolylpyrazole-4-Carboxamides as Potent Succinate Dehydrogenase Inhibitors through Active Fragment Exchange and Link Approach.

Succinate dehydrogenase (SDH) is an attractive target for developing green fungicides to manage agricultural pathogens in modern agriculture research. Herein, in this work, we report the discovery of benzothiazolylpyrazole-4-carboxamides I-III as potent SDH inhibitors using active fragment exchange and link approach. The results of the fungicidal activity assays showed that some of the synthesized compounds exhibited excellent inhibition against the tested fungi. Systematic structure-activity relationship studies led to the discovery of compound Ip, N-(1-((4,6-difluorobenzo[d]thiazol-2-yl)thio)propan-2-yl)-3-(difluoromethyl)-N-methoxy-1-methyl-1H-pyrazole-4-carboxamide, which showed higher fungicidal activity against Fusarium graminearum Schw (EC50 = 0.93 µg/mL) than the commercial fungicides thifluzamide (EC50 > 50 µg/mL) and boscalid (EC50 > 50 µg/mL). The molecular simulation studies suggested that hydrophobic interactions were the primary driving forces between ligands and SDH. Promisingly, we found that Ip could stimulate the growth of wheat seedlings and Arabidopsis thaliana and increase the biomass of the treated plants. Preliminary studies on the plant growth promoter mechanism of Ip indicated that it could increase nitrate reductase activity in planta, that, in turn, stimulates the growth of plants.

Calorie Restriction Enhanced Glycogen Metabolism to Compensate for Lipid Insufficiency.

SCOPE: This study aims to investigate the metabolic phenotype and mechanism of 40% calorie restriction (CR) in mice. METHODS AND RESULTS: CR mice exhibit super-stable blood glucose, as evidenced by increased fasting blood glucose (FBG), decreased postprandial blood glucose, and reduced glucose fluctuations. Additionally, both fasting plasma insulin and the homeostasis model assessment of insulin resistance increase significantly in CR mice. Compared with control, the phosphorylation of insulin receptor substrates-1 and serine/threonine kinase decreases in liver and fat but increases in muscle of CR mice after insulin administration, indicating hepatic and adipose insulin resistance, and muscle insulin sensitization. CR reduces visceral fat much more than subcutaneous fat. The elevated FBG is negatively correlated with low-level fasting ß-hydroxybutyrate, which may result from insufficient free fatty acids and diminishes ketogenic ability in CR mice. Furthermore, liver glycogen increases dramatically in CR mice. Analysis of glycogen metabolism related proteins indicates active glycogen synthesis and decomposition. Additionally, CR elevates plasma corticosterone and hypothalamic orexigenic gene expression. CONCLUSION: CR induces lipid insufficiency and stress, resulting in global physiological insulin resistance except muscle and enhances glycogen metabolism, culminating in the stability of blood glucose manifests in increased FBG, which compensates for insufficient blood ketones.

[Effects of the removal of invasive Moso bamboo on soil microbial biomass and enzyme activities in subtropical forests]. / å ¥ä¾µæ¯›ç«¹çš†ä¼å¯¹äºšçƒ­å¸¦æ£®æž—åœŸå£¤å¾®ç”Ÿç‰©ç”Ÿç‰©é‡å’Œé ¶æ´»æ€§çš„å½±å“.

Removal of invasive plant species is the first step to restoring the invaded ecosystems. The soil microbial biomass and extracellular enzyme activities were measured in Moso bamboo (Phyllostachys edulis) pure forest (completely invasion), invasive P. edulis removal forest (secondary succession 5 years after clear cutting), and the evergreen broadleaved forest (no invasion) in Tianmu Mountain. The results showed that compared with P. edulis pure forest, invasive P. edulis removal significantly increased the contents of soil organic carbon (SOC), nitrate nitrogen, available phosphorus and potassium, as well as microbial biomass carbon (MBC) and microbial biomass phosphorus (MBP), while significantly decreased microbial biomass nitrogen (MBN). The activities of α-glucosidase (AG), ß-glucosidase (BG), leucine aminopeptidase (LAP) and phenol oxidase (POX) in the forest with removal of invasive P. edulis were significantly higher than those in P. edulis pure forest, while invasive P. edulis removal did not change the activities of cellodisaccharide hydrolase (CBH), ß-N-acetyl-glucosaminopeptidase (NAG), acid phosphatase (ACP) and peroxidase (PER). Furthermore, the activities of AG, BG and LAP were positively correlated with SOC and MBC, while the increase in POX activity was positively correlated with soil nitrate content. In addition, MBC, MBN and MBP, and activities of AG, BG, NAG, LAP and ACP in P. edulis removal forest forest were significantly higher than those in evergreen broadleaved forests. Taken together, the removal of invasive P. edulis could increase soil nutrient contents, microbial biomass and extracellular enzyme activities, thus could be considered as an effective way to restore the invaded forests. Our results provide important theoretical basis for controlling P. edulis invasion in subtropical forests.

The aldolase inhibitor aldometanib mimics glucose starvation to activate lysosomal AMPK.

The activity of 5'-adenosine monophosphate-activated protein kinase (AMPK) is inversely correlated with the cellular availability of glucose. When glucose levels are low, the glycolytic enzyme aldolase is not bound to fructose-1,6-bisphosphate (FBP) and, instead, signals to activate lysosomal AMPK. Here, we show that blocking FBP binding to aldolase with the small molecule aldometanib selectively activates the lysosomal pool of AMPK and has beneficial metabolic effects in rodents. We identify aldometanib in a screen for aldolase inhibitors and show that it prevents FBP from binding to v-ATPase-associated aldolase and activates lysosomal AMPK, thereby mimicking a cellular state of glucose starvation. In male mice, aldometanib elicits an insulin-independent glucose-lowering effect, without causing hypoglycaemia. Aldometanib also alleviates fatty liver and nonalcoholic steatohepatitis in obese male rodents. Moreover, aldometanib extends lifespan and healthspan in both Caenorhabditis elegans and mice. Taken together, aldometanib mimics and adopts the lysosomal AMPK activation pathway associated with glucose starvation to exert physiological roles, and might have potential as a therapeutic for metabolic disorders in humans.

A quantitative enzyme-linked immunoassay (ELISA) to approximate complement-fixing antibody titers in serum from patients with coccidioidomycosis.

Coccidioidomycosis is most frequently diagnosed serologically, and the quantitative test for complement-fixing antibodies is considered prognostically useful. Because complement-fixing antibody testing is complex, labor-intensive, and poorly standardized, an enzyme-linked immunoassay (ELISA) alternative would be attractive. In this report, we restrict the complement-fixing, antibody-binding domain to a 200-amino-acid recombinant peptide of the known antigen. Over-lapping truncations of this peptide do not bind complement-fixing antibodies, suggesting that the responsible epitope(s) are conformational. Further, anchoring the antigenic peptide to the ELISA plate by means of a C-terminal biotin-mimic peptide tag instead of allowing the peptide to randomly adhere to the plastic plate improves sensitivity of antibody detection by 1-2 logs in different sera. The newly developed ELISA shows a significant quantitative correlation with complement-fixing antibody titers. This ELISA shows potential as the basis for a new quantitative assay for coccidioidal antibodies.

[Association analysis between SNPs of the growth hormone receptor gene and growth traits in arctic fox].

Using single-strand conformation polymorphism (PCR-SSCP) and DNA sequencing, single nucleotide polymorphisms (SNPs) of growth hormone receptor (GHR) gene were detected in an arctic fox population. Correlation analysis between GHR polymorphisms and growth traits were carried out using the appropriate model. Four SNPs, G3A in the 5'UTR, C99T in the first exon, T59C and G65A in the fifth exon were identified on the arctic fox GHR gene. The G3A and C99T polymorphisms of GHR were associated with female fox body weight (Pamp;0.05) and the T59C and G65A polymorphisms of GHR were associated with male fox body weight (Pamp;0.05) and the skin length of the female fox (Pamp;0.01). Therefore, marker assistant selection on body weight and skin length of arctic foxes using these SNPs can be applied to get big and high quality arctic foxes.