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The fluorescent probe SiR-FH realized real-time monitoring of HClO in the brains of mice with LPS-induced neuroinflammation.

Oxidative stress is closely related to the physiopathology of numerous diseases. Reactive oxygen species (ROS), reactive nitrogen species (RNS), and reactive sulfur species (RSS) are direct participants and important biomarkers of oxidative stress.

Oxetanocin A and albucidin are two oxetane natural products. While the biosynthesis of oxetanocin A has been described, less is known about albucidin. In this work, the albucidin biosynthetic gene cluster is identified in Streptomyces. Heterologous expression in a nonproducing strain demonstrates that the genes alsA and alsB are necessary and sufficient for albucidin biosynthesis confirming a previous study (Myronovskyi et al. Microorganisms 2020, 8, 237). A two-step construction of albucidin 4'-phosphate from 2'-deoxyadenosine monophosphate (2'-dAMP) is shown to be catalyzed in vitro by the cobalamin dependent radical S-adenosyl-l-methionine (SAM) enzyme AlsB, which catalyzes a ring contraction, and the radical SAM enzyme AlsA, which catalyzes elimination of a one-carbon fragment. Isotope labelling studies show that AlsB catalysis begins with stereospecific H-atom transfer of the C2'-pro-R hydrogen from 2'-dAMP to 5'-deoxyadenosine, and that the eliminated one-carbon fragment originates from C3' of 2'-dAMP.

Schizophrenia is a common type of serious mental illness with an unclear etiology. Recently, the excessive production of hydrogen sulfide in the brain has been considered to be one of the pathophysiological bases of schizophrenia. However, due to the existence of the blood-brain barrier (BBB), almost no fluorescent probe has been successfully used for the sensing and detection of H

Two-dimensional transition metal dichalcogenides with outstanding properties open up a new way to develop optoelectronic devices such as phototransistors and light-emitting diodes. Heterostructure with light-harvesting materials can produce many photogenerated carriers via charge and/or energy transfer. In this paper, the ultrafast dynamics of charge transfer in zero-dimensional CsPbBr3 quantum dot/two-dimensional MoS2 van der Waals heterostructures are investigated through femtosecond time-resolved transient absorption spectroscopy. Hole and electron transfers in the ps and fs magnitude at the interfaces between MoS2 and CsPbBr3 are observed by modulating pump wavelengths of the pump-probe configurations. Our study highlights the opportunities for realizing the exciton devices based on quantum dot/two-dimensional semiconductor heterostructures.

C-Nucleosides are characterized by a C-C rather than a C-N linkage between the heterocyclic base and the ribofuranose ring. While the biosynthesis of pseudouridine-C-nucleosides has been studied, less is known about the pyrazole-C-nucleosides such as the formycins and pyrazofurin. Herein, genome screening of Streptomyces candidus NRRL 3601 led to the discovery of the pyrazofurin biosynthetic gene cluster pyf. In vitro characterization of gene product PyfQ demonstrated that it is able to catalyze formation of the C-glycoside carboxyhydroxypyrazole ribonucleotide (CHPR) from 4-hydroxy-1H-pyrazole-3,5-dicarboxylic acid and phosphoribosyl pyrophosphate (PRPP). Similarly, ForT, the PyfQ homologue in the formycin pathway, can catalyze the coupling of 4-amino-1H-pyrazole-3,5-dicarboxylic acid and PRPP to form carboxyaminopyrazole ribonucleotide. Finally, PyfP and PyfT are shown to catalyze amidation of CHPR to pyrazofurin 5'-phosphate thereby establishing the latter stages of both pyrazofurin and formycin biosynthesis.

Peptidyl nucleoside antibiotics (PNAs) are a diverse class of natural products with promising biomedical activities. These compounds have tripartite structures composed of a core saccharide, a nucleobase, and one or more amino acids. In particular, amipurimycin and the miharamycins are novel 2-aminopurinyl PNAs with complex nine-carbon core saccharides and include the unusual amino acids (–)-cispentacin and N(5)-hydroxyarginine, respectively. Despite their interesting structures and properties, these PNAs have heretofore eluded biochemical scrutiny. Herein is reported the discovery and initial characterization of the miharamycin gene cluster in Streptomyces miharaensis (mhr) and the amipurimycin gene cluster (amc) in Streptomyces novoguineensis and Streptomyces sp. SN-C1. The gene clusters were identified using a comparative genomics approach, and heterologous expression of the amc cluster as well as gene interruption experiments in the mhr cluster support their role in the biosynthesis of amipurimycin and the miharamycins, respectively. The mhr and amc biosynthetic gene clusters characterized encode enzymes typical of polyketide biosynthesis instead of enzymes commonly associated with PNA biosynthesis, which along with labeled precursor feeding studies, implies that the core saccharides found in the miharamycins and amipurimycin are partially assembled as polyketides rather than derived solely from carbohydrates. Furthermore, in vitro analysis of Mhr20 and Amc18 established their roles as ATP-grasp ligases involved in the attachment of the pendant amino acids found in these PNAs, and Mhr24 was found to be an unusual hydroxylase involved in the biosynthesis of N(5)-hydroxyarginine. Finally, analysis of the amc cluster and feeding studies also led to the proposal of a biosynthetic pathway for (–)-cispentacin.

Image outpainting receives less attention due to the challenges of predicting the spatial content consistency and maintaining the high quality in generated images. All-sides image prediction is a generalized task in outpainting, aiming to extrapolate the outside content for all sides of an image. It is a challenging task to maintain spatial and semantic consistency between the original input and the generated multi-step regions. In this paper, we embed a novel Multi-view Recurrent Content Transfer module into an Encoder-Decoder architecture for long-range all-side image outpainting. A multi-head attention mechanism is leveraged to fuse information from different representation sub-spaces at different positions to enhance the consistency of generated images and the original input. Our model could obtain sufficient temporal information in predicting the extended feature maps, which improves the quality of long-range images extrapolation. We experimentally demonstrate that our proposed method could produce visually appealing results for outside image outpainting against the state-of-the-art image inpainting and outpainting approaches. Modelling the temporal relationship could help generate the outside regions and reconstruct the input regions smoothly and realistically. In addition, an attempt to possibly allow for arbitrary output resolutions is supported as well.

Cloud storage has emerged as a promising solution to the scalability problem of massive data management for both individuals and organizations, but it still faces some serious limitations in reliability and security. Recently, Tian et al. proposed a novel public auditing scheme for cloud storage (DHT-PA) based on dynamic hash table (DHT), with which their scheme achieves higher efficiency in dynamic auditing than the state-of-the-art schemes. They claimed that their scheme is provably secure against forging data signatures under the CDH assumption. Unfortunately, by presenting a concrete attack, we demonstrate that their scheme is vulnerable to the signature forgery attack, i.e., the cloud service provider (CSP) can forge a valid signature of an arbitrary data block. Thus, a malicious cloud service provider can pass the audit without correct data storage. The cryptanalysis shows that DHT-PA is not secure for public data verification. The purposed of our work is to help cryptographers and engineers design/implement more secure and efficient identity-based public auditing schemes for cloud storage by avoiding such kind of attacks.

Accurate discrimination of cancerous cells is a good solution for early diagnosis of tumors. The mitochondrion plays an important role in cells. Herein, the five aggregation-induced emission luminogens (AIEgens) with various double positive charges are synthesized to image mitochondria. Tetraphenylethylene (TPE) molecules are modified by methoxy groups, conjugated donor-acceptor, and different positive charges to achieve multicolor emission. The five AIEgens form the PTx-Sa (positive mitochondria-target molecular sensor array) to perform cross-fluorescence response based on the mitochondria-targeted imaging to achieve the discrimination of various cells. Principal component analysis of the cross-response fluorescence data of PTx-Sa shows that 100% accurate identification of various cells, including cancer cells and normal cells, digestive tract cancer cells, gastric cancer cells, and mixed gastric cancer cells. By support vector machine to show the predictive ability of PTx-Sa to unknown cells by using blind samples. This is the first time to apply mitochondria-targeted sensor array to identification of various cells.

In the current multi-energy complementary integrated energy system, there are many problems, such as complex equipment operation, incomplete operation data monitoring, multi-time scale characteristics of the monitoring data and so on. In order to solve these problems, the research on distributed intelligent sensing technology is carried out in this paper. First of all, the multi-time scale data model and ultra-lightweight stream encryption scheme are used to optimize the existing measurement and control methods, and from three aspects of economy, technology, and environmental protection, a multi-index comprehensive evaluation system for system operation is constructed; secondly, using distributed intelligent sensing technology to collect and monitor the operation data of load sides and all kinds of energy systems including pOwer, gas, cold and heat, and has designed and constructed a multi-energy complementary integrated energy distributed measurement and control system; finally, the rationality and reliability of the stream encryption scheme and the multi index comprehensive evaluation method are verified through the application example analysis. This system have optimized data collection and transmission mode, realized multi-energy flow high reliability data collection and real-time communication, and imprOved the performance of the energy system.

With the development of the power grid, the adjustment of national policies, and the increasingly stringent management requirements of the dispatch center, the original support platform has gradually exposed the lack of multi-level open capabilities, the lack of unified management and utilization of basic equipment and facility resources, insufficient support for regional III applications, supporting various applications to improve processing capabilities, service capabilities, scalability and lack of reliability and other shortcomings. Aiming at the defects of the original support platform, it is urgent to combine advanced cloud computing and big data and other advanced applicable technologies to carry out regulatory cloud research and design work to improve the technical support capability of the large grid’s regulatory operation. With the continuous expansion of the scale of the power grid, the measurement and acquisition of primary and secondary equipment has increased in a blowout manner. The processing of these data has far exceeded the processing capacity of a single computer. The research and application of advanced data storage technology in the dispatching and control cloud played a vital role. This data storage technology serves the Dameng database, and research shows that database operation and other corresponding performances can meet the application requirements of Shandong regulatory cloud.

The large-scale development of wind energy leads to the integration of multiple wind farms into a power system in a region. Due to the geographic locations of wind farms, wind speeds at different sites show certain dependence between each other, which has a considerable impact on the wind energy potential. An essential step in studying the impaction is the construction of relatively accurate wind speed models incorporating the dependence. In this paper, four probabilistic models of multiple wind speeds are introduced, including conditional distribution model, correlation matrix transformation model, normal transformation model and copula function model. The modeling procedure and simulation methodology are illustrated. The model accuracy is analyzed and compared using two actual wind speed data. Useful conclusions are obtained for further study and application.

The multi-nodes supply chain network composed of suppliers, logistics centres, transfer stations, retailers and other different types of enterprise nodes was taken as the research object in this pa...

The CRISPR (clustered regularly interspaced short palindromic repeats)-associated (Cas) protein, Cas9, is a RNA-guided endonuclease that uses RNA–DNA base pairing to recognize and cleave double-stranded DNA (dsDNA) with a protospacer adjacent motif (PAM). It is widely accepted that the most commonly used Streptococcus pyogenes Cas9 (SpyCas9) protein recognizes a canonical 5′-NGG-3′ sequence in the PAM. In this study, we discovered another critical characteristic required for SpyCas9 cleavage i.e. the interspace between the protospacer and NGG. The results generated from DNA cleavage assays showed that both interspace length and the presence of a GG dinucleotide (particularly the upstream guanosine) are critical components in permitting SpyCas9-mediated cleavage. Interestingly, the interspace length significantly affects the selection of SpyCas9 cleavage sites on the non-complementary strand. Additionally, the complementary strand cleavage site is determined by the location of the single-molecular guide RNA (sgRNA). This indicates that PAM and sgRNA play different roles in determining the SpyCas9 specific cleavage site. Importantly, we also revealed for the first time that in vitro annealing of dsDNA with exogenous PAM-presenting oligonucleotides (PAMmers) stimulated SpyCas9 cleavage of target dsDNA without PAM. This study pertaining to PAM and SpyCas9 is expected to improve our understanding of SpyCas9 with an associated impact on related bioengineering capabilities.

Multi-energy complementary integrated energy system has the problems of complex equipment operation, incomplete operation data monitoring and multi-time scale characteristics. In order to solve these problems, the operation state data of power, gas, cooling, heating network and distributed power supply as well as the operation state parameters of various networking energy consumption equipment at the load side were collected and monitored. This paper was optimized the system data collection and transmission method through multi-time scale data modeling and ultra-lightweight stream encryption algorithm, and the system operation multi-index evaluation system was constructed from three aspects of economy, technology and environmental protection. In this paper, the rationality and reliability of the scheme of stream encryption and the method of multi-index comprehensive evaluation were verified through the analysis of application examples. From multiple time scales, the system can monitor and control the change of heterogeneous energy stream, such as cooling, heating and electricity, and also can realize the high reliability data acquisition and real-time communication of multi-energy stream. It provided a data source for the real-time scheduling and control decision-making of the follow-up integrated energy system.

There are various types of transformer device defects and the formation reasons are complex. Exploring the influencing factors and occurrence of transformer devices defects is a focus in the field of power transmission and transformation devices state inspection and evaluation. This paper proposes an analysis method, multidimensional FP-Growth algorithm (MDFPG) to mine association rules from multidimensional transformer defect records. The method combines records from different system of power grid to construct multidimensional records first. Then, the records are preprocessed and encoded into single dimension form. The MDFPG method speeds up the mining process by adding a pruning step. Experiments show that MDFPG method has a better performance than FP-Growth algorithm on large data sets. Some conclusions can be learned from the experiment result, which has a certain value for making equipment maintenance plans and exploring defect occurrence regularity.

Although traditional fault diagnosis methods can qualitatively identify the failure modes for power equipment, it is difficult to evaluate the failure probability quantitatively. In this paper, a failure probability calculation method for power equipment based on multi-characteristic parameters is proposed. After collecting the historical data of different fault characteristic parameters, the distribution functions and the cumulative distribution functions of each parameter, which are applied to dispersing the parameters and calculating the differential warning values, are calculated by using the two-parameter Weibull model. To calculate the membership functions of parameters for each failure mode, the Apriori algorithm is chosen to mine the association rules between parameters and failure modes. After that, the failure probability of each failure mode is obtained by integrating the membership functions of different parameters by a weighted method, and the important weight of each parameter is calculated by the differential warning values. According to the failure probability calculation result, the series model is established to estimate the failure probability of the equipment. Finally, an application example for two 220 kV transformers is presented to show the detailed process of the method. Compared with traditional fault diagnosis methods, the calculation results not only identify the failure modes correctly, but also reflect the failure probability changing trend of the equipment accurately.

Anaglyph stereo provides a portable and inexpensive way to view stereoscopic images. Rendering anaglyph, however, often suffers from ghosting which results from the viewer’s one eye receiving a weaker version of the image aimed for the other eye. In this paper, we present a novel approach to reduce ghosting in anaglyph that does not rely on power spectra of a monitor or on transmission spectra of anaglyph glasses. First, we measure the ghosting effect by the red lightness difference between a stereo pair and visual saliency estimate. Then, we formulate ghosting reduction as an energy minimization problem, which can be efficiently solved using a standard linear solver. Experimental results show that our method not only successfully reduces ghosting in anaglyph but also produces images that appear almost ordinary to the naked eye which improves the backward-compatibility of anaglyph.

Stereopsis provides an additional depth cue and plays an important role in the human vision system. This paper explores stereopsis for saliency analysis and presents two approaches to stereo saliency detection from stereoscopic images. The first approach computes stereo saliency based on the global disparity contrast in the input image. The second approach leverages domain knowledge in stereoscopic photography. A good stereoscopic image takes care of its disparity distribution to avoid 3D fatigue. Particularly, salient content tends to be positioned in the stereoscopic comfort zone to alleviate the vergence-accommodation conflict. Accordingly, our method computes stereo saliency of an image region based on the distance between its perceived location and the comfort zone. Moreover, we consider objects popping out from the screen salient as these objects tend to catch a viewer's attention. We build a stereo saliency analysis benchmark dataset that contains 1000 stereoscopic images with salient object masks. Our experiments on this dataset show that stereo saliency provides a useful complement to existing visual saliency analysis and our method can successfully detect salient content from images that are difficult for monocular saliency analysis methods.