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Ultrasound–microwave combined extraction (UMCE), gradient ethanol precipitation, chemical characterization, and antioxidant and hypoglycemic activities of Lycium barbarum leaf polysaccharides (LLP) were systematically studied. The optimal conditions for UMCE of LLP achieved by response surface method (RSM) were as follows: microwave time of 16 min, ultrasonic time of 20 min, particle size of 100 mesh, and ratio of liquid to solid of 55:1. Three novel polysaccharide fractions (LLP30, LLP50, LLP70) with different molecular weights were obtained by gradient ethanol precipitation. Polysaccharide samples exhibited scavenging capacities against ABTS and DPPH radicals and inhibitory activities against α-glucosidase and α-amylase. Among the three fractions, LLP30 possessed relatively high antioxidant and hypoglycemic activities in vitro, which showed a potential for becoming a nutraceutical or a phytopharmaceutical for prevention and treatment of hyperglycemia or diabetes.

Human control is characterized by its flexibility and adaptability in response to the conditional probability in the environment. Previous studies have revealed that efficient conflict control could be attained by predicting and adapting to the changing control demand. However, it is unclear whether cognitive flexibility could also be gained by predicting and adapting to the changing control demand. The present study aimed to explore this issue by combining the model-based analyses of behavioral and neuroimaging data with a probabilistic cued task switching paradigm. We demonstrated that the Bayesian surprise (i.e. unsigned precision-weighted prediction error [PE]) negatively modulated the connections among stimulus processing brain regions and control regions/networks. The effect of Bayesian surprise modulation on these connections guided control engagement as reflected by the control PE effect on behavior, which in turn facilitated cognitive flexibility. These results bridge a gap in the literature by illustrating the neural and behavioral effect of control demand prediction (or PE) on cognitive flexibility and offer novel insights into the source of switch cost and the mechanism of cognitive flexibility.

Compiler testing is the most widely used way to assure compiler quality. However, since compilers require a large number of sophisticated test programs as inputs, the existing approaches in compiler testing still have a limited capability in generating both syntactically valid and diverse test programs. In this paper, we propose DeepGen, a deep learning-based approach to support compiler testing through the inference of a generative model for compiler inputs. First, DeepGen trains a Transformer-XL model based on a large corpus of seed programs, and uses the trained model to generate syntactically valid programs. Then, DeepGen adopts a sampling strategy in the inference phase to generate diverse test programs. Finally, DeepGen leverages differential testing on the generated programs to discover compiler bugs. We have evaluated DeepGen over two popular C++ compilers GCC and LLVM, and the results confirm the effectiveness of our approach. DeepGen detects 35.29%, 53.33%, and 187.50% more bugs than three existing approaches, i.e. DeepSmith, DeepFuzz, and Csmith, respectively. In addition, 30.43% bugs detected by DeepGen are not detected by other approaches. Furthermore, DeepGen has successfully detected 38 bugs in the latest development versions of GCC and LLVM; 21 of them have been confirmed/fixed by the developers.

With the plain text descriptions of design patterns, developers could better learn and understand the definitions and usage scenarios of design patterns. To facilitate the automatic usage of these descriptions, e.g., recommending design patterns by free-text queries, design patterns and natural languages should be adequately associated. Existing studies usually use texts in design pattern books as the representations of design patterns to calculate similarities with the queries. However, this way is problematic. Lots of information of design patterns may be absent from design pattern books and many words would be out of vocabulary due to the content limitation of these books. To overcome these issues, a more comprehensive method should be constructed to estimate the relatedness between design patterns and natural language words. Motivated by Word2Vec, in this study, we propose DPWord2Vec that embeds design patterns and natural language words into vectors simultaneously. We first build a corpus containing more than 400 thousand documents extracted from design pattern books, Wikipedia, and Stack Overflow. Next, we redefine the concept of context window to associate design patterns with words. Then, the design pattern and word vector representations are learnt by leveraging an advanced word embedding method. The learnt design pattern and word vectors can be universally used in textual description based design pattern tasks. An evaluation shows that DPWord2Vec outperforms the baseline algorithms by 17.1%-96.5% in measuring the similarities between design patterns and words in terms of Spearman's rank correlation coefficient. Moreover, we adopt DPWord2Vec on two typical design pattern tasks. In the design pattern tag recommendation task, the DPWord2Vec based method outperforms two state-of-the-art algorithms by 6.6% and 32.7% respectively when considering Recall@10. In the design pattern selection task, DPWord2Vec improves the existing methods by 6.5%-70.7% in terms of MRR.

In this study, a novel adsorbent (SRM-ZnO) was prepared using zinc oxide supported on red mud in a seawater medium and was used for the adsorption of methyl orange (MO). It is expected to solve the recycling of red mud and prepare an economical adsorbent with high efficiency to adsorb dye wastewater. Material composition and morphology analyses showed that hydrotalcite compounds were attached on the surface of SRM-ZnO. The hydrotalcite compounds can increase the surface area of the modified red mud and thus increase the adsorption capacity of MO. The adsorption of MO dye on modified red mud conforms to the Temkin isotherm model and pseudo-second-order kinetic model. The adsorption behavior mainly includes physical interaction, supplemented with chemical interactions. Result also found that the adsorption of MO on SRM-ZnO is a spontaneous exothermic process.

The ternary Ge cluster [Co2@(Ge17Ni)]4− was synthesized, which not only exhibits a unique double-cage form in the family of 18-vertex Zintl clusters, but also makes up the missing link of edge fusion in the construction of double-cage systems.

Papillary thyroid cancer (PTC) is an endocrine malignancy whose incidence has increased rapidly worldwide. Exosome-miR-655-3p was down-regulated in patients with PTC. However, the effect and molecular mechanism of exosome-miR-655-3p in PTC was indistinct until now. Our study found that exosome-miR-655-3p was decreased in serum of PTC patients. Overexpression of miR-655-3p with mimics significantly shrunk the cell viability, reduced the number of chemotactic and invasive PTC cells. Besides, the proportion of CD163 positive cells and the expression of markers of M2 subtype macrophages was markedly decreased when mononuclear macrophage THP-1 was cultured with exosomes of miR-655-3p mimics. Oppositely, the inhibitor of miR-655-3p exacerbated growth, chemotaxis and invasion of PTC cells, and enhanced the M2 subtype macrophages. Structurally, miR-655-3p could target the 3’ untranslated region (3’UTR) of CXCR4 and restrict the expression of CXCR4. In Xenograft tumor experiment, upregulated exosome-miR-655-3p effectively inhibited the growth of tumor and reduced the expression of CXCR4, Ki67 and CD163 in vivo. In summary, exosomal miR-655-3p inhibited growth, invasion and macrophage M2 polarization through targeting CXCR4 in papillary thyroid carcinoma. Regulating exosome-miR-655-3p/CXCR4 may be a potential treatment strategy for PTC.

The pathological proliferation of cells in vascular smooth muscle underlies neointimal hyperplasia (NIH) development during atherosclerosis. Circular RNAs (circRNAs), which represent novel functional biomarkers and RNA-binding proteins, contribute to multiple cardiovascular diseases; however, their roles in regulating the vascular smooth muscle cell cycle remain unknown. Thus, we aimed to identify the roles of circRNAs in vascular smooth muscle during coronary heart disease (CHD). Through circRNA sequencing of CHD samples and human antigen R (ELAVL1) immunoprecipitation, we identified circRNAs that are associated with CHD and interact with ELAVL1. Our results suggested that the hsa_circ_0000280 associated with CHD inhibits cell proliferation and induces ELAVL1-dependent cell cycle arrest. Gain/loss-of-function experiments and assays in vivo indicated that hsa_circ_0000280 facilitates interactions between ELAVL1 and cyclin-dependent kinase suppressor 1 (CDKN1A) mRNA and stabilization of this complex and leads to cell cycle arrest at the G1/S checkpoint, inhibiting cell proliferation of vascular smooth muscle cells in vitro and NIH in vivo. Importantly, hsa_circ_0000280 reduced neointimal thickness and smooth muscle cell proliferation in vivo. Taken together, these findings reveal a novel pathway in which hsa_circ_0000280 facilitates the regulation of ELAVL1 on CDKN1A mRNA to inhibit NIH. Therefore, measuring and modulating their expression might represent a potential diagnostic or therapeutic strategy for CHD.

The degree of network attack methods is limitless, and the conventional defence and detection mode cannot satisfy the needs of network security monitoring, thanks to the fast growth of network technology and the large-scale expansion of networks. Widely distributed network system, the network system structure becomes increasingly complex, the network is facing increasingly attacks and threats, network security problems are increasingly serious, a variety of security incidents and vulnerabilities are increasingly frequent, including hacker attacks, and network security vulnerability is gradually exposed. Traditional ways of dealing with the problem may be insufficient, resulting in harm to persons and businesses, as well as the loss of property and a reduction in people's faith in the Internet. An IOT (Internet of Things) based orientated model is suggested to increase the accuracy in predicting network security condition for schools. The data is first rebuilt into a multidimensional time series, then fed into the support vector machine for training, and then nonlinear method is utilised to handle the problem of parameter optimization of the training mode to create the network security scenario prediction model. Finally, utilising IOT, the network security scenario prediction model is utilised to forecast network security in the future. The simulation results show that the optimal parameters of the support vector machine (SVM) are C = 10, σ = 0.625, and e = 0.001. C = 10, σ = 0.625, e = 0.001 were used to relearn the training set, the optimal network security situation prediction model was established, and the test set was predicted. The projected values were close to the actual values, and the accuracy of the forecast was high. The model, when paired with the nonlinear algorithm and SVM, can accurately reflect the network's overall security operation, enhance network security scenario forecast accuracy, and help the administrator in network security control.

The (AlCoCrFeNi)1-X (WC-10Co)X composite coatings were fabricated on 06Cr13Ni5Mo steel by high-velocity oxygen-fuel (HVOF) spraying. The coatings' microstructure, mechanical properties, and corrosion performance were characterized, and the cavitation erosion resistance of the coatings was tested in 3.5 wt% NaCl medium. The influence of the microstructure, mechanical properties, and corrosion resistance on cavitation erosion resistance were discussed. The microhardness and local plastic deformation resistance of the coatings were increased by WC-10Co, while the corrosion resistance of the composite coatings was decreased by severe galvanic corrosion. The cavitation erosion mechanism of the coatings was lamellar spalling. In NaCl medium, the (AlCoCrFeNi)75(WC–10Co)25 (HEA75/WC25) coating showed lower cavitation erosion resistance than the AlCoCrFeNi (HEA) coating, which was caused by the galvanic corrosion, uncoordinated deformation and the low bonding strength of the HEA/WC-10Co interface. For the HEA75/WC25 coating and (AlCoCrFeNi)50(WC–10Co)50 (HEA50/WC50) coating, the cavitation erosion damage of the HEA75/WC25 coating was higher than that of the HEA50/WC50 coating. When the microstructure and corrosion resistance of the coatings were similar, the cavitation erosion resistance was mainly affected by the mechanical property.

Parallel tasks have been paid growing attention in recent years, and the scheduling with shared resources is of significant importance to real-time systems. As an efficient mechanism to provide mutual exclusion for parallel processing, spin-locks are ubiquitous in multi-processor real-time systems. However, the spin-locks suffer the scalability problem, and the intra-task parallelism further exacerbates the analytical pessimism. To overcome such deficiencies, we propose a Hierarchical Hybrid Locking Protocol (H2LP) under federated scheduling. The proposed H2LP integrates the classical Multiprocessor Stack Resource Policy (MSRP) and uses a token mechanism to reduce global contentions. We provide a complete analysis framework supporting both heavy and light tasks under federated scheduling and develop a blocking analysis with the state-of-the-art linear optimization technique. Empirical evaluations showed that the H2LP outperformed the other state-of-the-art locking protocols in at least configurations when considering exclusive clustering. Furthermore, our partitioned approach for light tasks can substantially improve schedulability by mitigating the over-provisioning problem.

Memory allocation and deallocation are the fundamental operations of embedded operating systems, which have been extensively used in many safety critical systems. The correctness of the operations is of paramount importance because their failure could incur severe consequences. While the system is running, the memory state can easily grow to a gigantic amount, which means that it is impossible to verify the huge memory states one by one. Therefore, it is a challenge how to verify the correctness of running memory state of the system. In this article, we propose a novel memory state verification method based on inductive and deductive reasoning. First, we abstract the memory state as a list of memory blocks, which will transform in memory operations. Second, we construct the generic model based on the transition function of the memory management and summarize the invariant properties of the memory state. Third, we use the inductive method to calculate the changes between the memory states, and verify that the memory state of the system always satisfy the global properties. All the proofs are implemented in the interactive theorem prover Coq. On the basis of our proposed model, we verify the correctness of a two-level segregated fit (TLSF) algorithm through some extensions, and we also apply this method to verify the correctness of the memory state of the embedded system at runtime.

Chemodynamic therapy (CDT) utilizes Fenton or Fenton-like reactions to convert hydrogen peroxide (H

A unidirectional cable pendulum damper is proposed to mitigate vibration responses of large-scale wind turbine blades in the edgewise direction, and the effectiveness of the proposed device for vibration response control is investigated. First, the configuration and working principles of the vibration damper are introduced. Second, the Euler–Lagrange equation of the single blade vibration damping system with the vibration damper is derived based on the Hamilton’s principle. At last, considering the effect of blade rotation, the wind load that applied on the blade was calculated using the rotating sample spectrum. The dynamic responses of blades are also calculated using the MATLAB/Simulink platform. The peak value and standard deviation of blade responses were taken as evaluation indexes to evaluate the vibration control efficiency of the device with varying the parameters such as the mass ball pendulum length, the fixed pulley block installation position, the stiffness and the pre-stress of the flexible cable. The optimal parameters of the vibration damper are investigated and obtained based on the assumption that no pounding happens between the mass ball of the vibration damper and the inner wall of the blade. Results show that the length of the mass ball pendulum and the installation position of the fixed pulley block, the values of which are within a reasonable range, can ensure the optimal performance of the vibration damper. The displacement of the mass sphere can be effectively reduced by increasing the stiffness of the flexible cable, and the pre-stress shows marginal beneficial effect on the damping performance and the displacement control of the mass sphere. Using the optimum parameters, the vibration damper can keep the mass ball within a safe running distance. The reduction of the peak value and the standard deviation of the blade displacement can reach 89.36% and 89.83%, respectively. The proposed device space can effectively reduce the blade tip response of the wind turbine by occupying less space. Moreover, the size of the device installation space can be changed by adjusting the weight ball swing length, which is suitable for the vibration control of the wind turbine blade edgewise direction.

Patients with gastric cancer (GC) are prone to lymph node metastasis (LNM), which is an important factor for recurrence and poor prognosis of GC. Nowadays, more and more studies have confirmed that exosomes can participate in tumor lymphangiogenesis. In-depth exploration of the pathological mechanism in the process of LNM in GC may provide effective targets and improve the diagnosis and treatment effect. We used sequencing analysis of collected serum to screen out exo-miRNA related to LNM in GC. In this study, we screened out miR-224-3p related to GC progression and LNM in a vascular endothelial growth factor C (VEGFC)-independent manner. We found that exo-miR-224-3p derived from GC cells could enter human lymphatic endothelial cells (HLECs) and promote the tube formation and migration of HLECs. In addition, it was revealed that miR-224-3p could bind to the 3'UTR region of GSK3B mRNA. Then, we proved that inhibiting the expression of GSK3B could suppress the phosphorylation of β-catenin and promote the transcription of PROX1, thus leading to tumor lymphangiogenesis. Furthermore, it was also found that hnRNPA1 mediated the sorting of miR-224-3p into exosomes, and the high expression of PKM2 promoted the secretion of exo-miR-224-3p. Our discovery of the exo-miR-224-3p/GSK3B/β-catenin/PROX1 axis may provide a new direction for the clinical treatment of GC.

Lei Qiao, Yue Chen, Xiaofan Song, Xina Dou, Chunlan Xu The Key Laboratory for Space Bioscience and Biotechnology, School of Life Sciences, Northwestern Polytechnical University, Xi’an, People’s Republic of ChinaCorrespondence: Chunlan Xu, The Key Laboratory for Space Bioscience and Biotechnology, School of Life Sciences, Northwestern Polytechnical University, Xi’an, People’s Republic of China, Tel +86 29-88460543, Fax +86 29-88460332, Email clxu@nwpu.edu.cnPurpose: The bidirectional communication between the gut and the central nervous system mediated by gut microbiota is closely related to the occurrence and development of neurodegenerative diseases, including Alzheimer’s disease (AD). Selenium (Se) has been identified as playing a role against AD. Probiotics have beneficial effects on host brain function and behavior by modulating the microbiota-gut-brain axis. Herein, we evaluated the protective effects of Lactobacillus casei ATCC 393 (L. casei ATCC 393) and selenium nanoparticles-enriched L. casei ATCC 393 (L. casei ATCC 393-SeNPs) against D-galactose/aluminum chloride-induced AD model mice.Methods: The Morris Water Maze (MWM) test was used to assess cognitive function of mice. The morphology and histopathological changes, antioxidant capacity and immune responses in the brain and ileum were evaluated. The alterations in intestinal permeability of the mice were determined using FITC-dextran. Gut microbiota composition was assessed using 16s rRNA sequencing.Results: Thirteen weeks intervention with L. casei ATCC 393 or L. casei ATCC 393-SeNPs significantly improved cognitive dysfunction, and minimized amyloid beta (Aβ) aggregation, hyperphosphorylation of TAU protein, and prevented neuronal death by modulating Akt/cAMP-response element binding protein (CREB)/brain-derived neurotrophic factor (BDNF) signaling pathway. Moreover, compared with L. casei ATCC 393, L. casei ATCC 393-SeNPs further effectively mitigated intestinal barrier dysfunction by improving antioxidant capacity, regulating immune response, restoring gut microbiota balance, and increasing the level of short-chain fatty acids and neurotransmitters, thereby inhibiting the activation of microglia and protecting brain neurons from neurotoxicity such as oxidative stress and neuroinflammation.Conclusion: These findings indicated that targeting the microbiota-gut-brain axis with L. casei ATCC 393-SeNPs may have therapeutic potential for the deficits of cognitive function in the AD model mice. Thus, we anticipate that L. casei ATCC 393-SeNPs may be a promising and safe Se nutritional supplement for use as a food additive to prevent the neurodegenerative disease.Graphical Abstract: Keywords: neurodegenerative disease, gut microbiota, oxidative stress, neuroinflammation

LINC00461 represents a new long noncoding RNA. However, it is unclear whether LINC00461 is associated with glucose metabolism and proliferation in triple-negative breast cancer. Here, we show that LINC00461 overexpression induces glucose metabolism and proliferation in TNBC, whereas its downregulation markedly reduces glucose metabolism and proliferation. Mechanistically, LINC00461 might function in TNBC by binding with HSP90. Then, it enhances the interaction between HSP90 and c-Myc and inhibits ubiquitination and degradation of c-Myc to regulate c-Myc target genes-LDHA. Clinically, LINC00461 has tight associations with tumor grade and TNM in cancer patients. There is compelling evidence LINC00461 may be exploited as a possible novel molecular marker and therapeutic target in TNBC.

It is highly desirable to develop high-performance ratiometric fluorescent probes for SO

Selenium nanoparticles (SeNPs) with unique biological properties have been suggested as a safer and more effective platform for delivering of Selenium for biological needs. In this study, we investigated the association between gut microbiota altered by SeNPs supplementation and its metabolites under oxidative stress conditions through 16S rDNA gene sequencing analysis and untargeted metabolomics. The results showed that dietary supplementation with SeNPs attenuated diquat-induced acute toxicity in mice, as demonstrated by lower levels of inflammatory effector cells, and biochemical markers in serum such as aspartate aminotransferase (AST), alanine aminotransferase (ALT), blood urea nitrogen (BUN) and lactate dehydrogenase (LDH). SeNPs also reversed the perturbed gut microbiota composition induced by diquat, decreased the Firmicutes/Bacteroidetes ratio, and increased the abundance of beneficial bacteria such as Akkermansia, Muribaculaceae, Bacteroides and Parabacteroides. Untargeted fecal metabolomics showed that SeNPs can regulate the production of steroids and steroid derivatives, organonitrogen compounds, pyridines and derivatives and other metabolites. Microbiome-metabolome correlation analysis suggested that Parabacteroides was the key bacteria for the SeNPs intervention, which might upregulate the levels of metabolites such as trimethaphan, emedastine, berberine, desoxycortone, tetrahydrocortisone. This study demonstrated that dietary SeNPs supplementation can extensively modulate the gut microbiota and its metabolism, thereby alleviating diquat-induced acute toxicity.

The (AlCoCrFeNi)1-X(WC-10Co)X composite coatings were fabricated by HVOF spraying and their microstructures, mechanical properties and cavitation erosion behaviors were tested. The effects of WC-10Co on the cavitation erosion mechanisms were discussed by compared the differences of volume losses and eroded surface morphologies between the coatings. The cavitation erosion resistance of the coatings was about 3 times as that of the 06Cr13Ni5Mo steel. With the addition of WC-10Co, the cavitation erosion resistance of the coating was slightly increased. In the initial stage of cavitation erosion test, the cavitation erosion damage was concentrated on the interface, which was caused by the uncoordinated deformation and poor mechanical properties of the interface between HEA and WC-10Co. When the WC-10Co distributed below the HEA region, the WC-10Co played a strong supporting role and improved the impact resistance of the HEA region. The cavitation erosion mechanism of the HEA1 coating was lamellar spalling. The cavitation erosion mechanisms of the HEA2 and HEA3 coatings were particles spalling and lamellar spalling.