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Triclosan is a promising candidate of fatty acid synthase (FASN) inhibitor by blocking FASN activity, but its effect on FASN expression and the underling epigenetic mechanism remain elusive. In this study, the effect of triclosan on FASN mRNA and protein expressions in human HepG2 cells and the regulatory role of microRNAs (miRNAs) in the downregulation of FASN induced by triclosan were explored through experiments and bioinformatics analysis. The results showed that triclosan not only directly inhibited FASN activity, but also significantly decreased FASN mRNA and protein levels in human liver HepG2 cells. Nine miRNAs targeting FASN mRNA degradation were identified by miRNA prediction tools, and the expression levels of these nine miRNAs were then detected by real-time quantitative PCR. Triclosan significantly increased the expressions of the six miRNAs, namely miR-15a, miR-107, miR-195, miR-424, miR-497 and miR-503, leading to the downregulation of FASN. Further investigation revealed that the six triclosan-upregulated miRNAs played an important regulatory role in lipid metabolism and cell cycle by gene ontology annotations and pathway analysis. Consistent with the results of bioinformatics analyses, triclosan significantly reduced the intracellular lipid content by triglyceride assay, oil red O, BODIPY 493/503 and Nile Red staining, thereby inhibiting the growth of HepG2 cells through apoptosis. Taken together, our study reveals that triclosan downregulates FASN expression through a variety of miRNAs, providing new insight for triclosan as a FASN inhibitor candidate to regulate lipid metabolism in human hepatoma cells.

This study introduces a novel unified power flow algorithm for hybrid AC/DC power grids. For hybrid AC/DC power grids that incorporate voltage source converters (VSCs), the proposed algorit...

This paper proposes a systematic analysis and synthesis method for the optimal design of filters for L1 adaptive output feedback controllers. In the L1 adaptive feedback structure, the low-pass fil...

The continuous cropping of sugar beet can result in soil degradation and a decrease in the sugar beet yield and quality. However, the role of continuous sugar beet (Beta vulgaris L. var. saccharifera) cropping in shaping the structure and function of the rhizosphere microbial community remains poorly investigated. In this study, we comparatively investigated the impact of different numbers of years of continuous sugar beet cropping on structural and functional changes in the microbial community of the rhizosphere using high-throughput sequencing and bioinformatics analysis. We collected rhizosphere soils from fields continuously cropped for one-year (T1), five-year (T5), and thirty-year (T30) periods, as well as one bulk soil (T0), in the Xinjiang Uygur Autonomous Region. The results demonstrated that continuous sugar beet cropping resulted in a significant decline in the community diversity of soil bacterial and fungal populations from T1 to T5. With continuous change in the structure of the microbial community, the Shannon diversity and observed species were increased in T30. With an abundance of pathogenic microbes, including Acidobacteria, Alternaria, and Fusarium, that were highly enriched in T30, soil-borne diseases could be accelerated, deduced by functional predictions based on 16S rRNA genes. Continuous sugar beet cropping also led to significant declines in beneficial bacteria, including Actinobacteria, Pseudomonas spp., and Bacillus spp. In addition, we profiled and analyzed predictive metabolic characteristics (metabolism and detoxification). The abundance of phenolic acid decarboxylase involved in the phenolic acid degradation pathway was significantly lower in groups T5 and T30 than that in T0 and T1, which could result in the phenolic compounds becoming excessive in long-term continuous cropping soil. Our results provide a deeper understanding of the rhizosphere soil microbial community&rsquo, s response to continuous sugar beet cropping, which is important in evaluating the sustainability of this agricultural practice.

Although CRIg was originally identified as a macrophage receptor for binding complement C3b/iC3b in vitro, recent studies reveal that CRIg functions as a pattern recognition receptor in vivo for Kupffer cells (KCs) to directly bind bacterial pathogens in a complement-independent manner. This raises the critical question of whether CRIg captures circulating pathogens through interactions with complement in vivo under flow conditions. Furthermore, the role of CRIg during parasitic infection is unknown. Taking advantage of intravital microscopy and using African trypanosomes as a model, we studied the role of CRIg in intravascular clearance of bloodborne parasites. Complement C3 is required for intravascular clearance of African trypanosomes by KCs, preventing the early mortality of infected mice. Moreover, antibodies are essential for complement-mediated capture of circulating parasites by KCs. Interestingly, reduced antibody production was observed in the absence of complement C3 during infection. We further demonstrate that CRIg but not CR3 is critically involved in KC-mediated capture of circulating parasites, accounting for parasitemia control and host survival. Of note, CRIg cannot directly catch circulating parasites and antibody-induced complement activation is indispensable for CRIg-mediated parasite capture. Thus, we provide evidence that CRIg, by interacting with complement in vivo, plays an essential role in intravascular clearance of bloodborne parasites. Targeting CRIg may be considered as a therapeutic strategy.

N(6)-methyladenosine (m(6)A), the most abundant and reversible RNA modification, plays critical a role in tumorigenesis. However, whether m(6)A can regulate p53, a leading antitumor protein remains poorly understood. In this study, we explored the regulatory role of m(6)A on p53 activation using an arsenite-transformed keratinocyte model, the HaCaT-T cell line. We created the cell line by exposing human keratinocyte HaCaT cells to 1 μM arsenite for 5 months. We found that the cells exhibited an increased m(6)A level along with an aberrant expression of the methyltransferases, demethylase, and readers of m(6)A. Moreover, the cells exhibited decreased p53 activity and reduced p53 phosphorylation, acetylation, and transactivation with a high nucleus export rate of p53. Knockdown of the m(6)A methyltransferase, METTL3 significantly decreased m(6)A level, restoring p53 activation and inhibiting cellular transformation phenotypes in the arsenite-transformed cells. Further, using both a bioinformatics analysis and experimental approaches, we demonstrated that m(6)A downregulated the expression of the positive p53 regulator, PRDM2, through the YTHDF2-promoted decay of PRDM2 mRNAs. We showed that m(6)A upregulated the expression of the negative p53 regulator, YY1 and MDM2 through YTHDF1-stimulated translation of YY1 and MDM2 mRNA. Taken together, our study revealed the novel role of m(6)A in mediating arsenite-induced human keratinocyte transformation by suppressing p53 activation. This study further sheds light on the mechanisms of arsenic carcinogenesis via RNA epigenetics.

Bats (order Chiroptera) are one of the most diverse and widely distributed group of mammals with a close relationship to humans. Over the past few decades, a number of studies have been performed on bat viruses; in contrast, bacterial pathogens carried by bats were largely neglected. As more bacterial pathogens are being identified from bats, the need to study their natural microbiota is becoming urgent. In the current study, fecal samples of four bat species from different locations of China were analyzed for their microbiota composition. Together with the results of others, we concluded that bat microbiota is most commonly dominated by Firmicutes and Proteobacteria; the strict anaerobic phylum Bacteroidetes, which is dominant in other terrestrial mammals, especially humans and mice, is relatively rare in bats. This phenomenon was interpreted as a result of a highly specified gastrointestinal tract in adaptation to the flying lifestyle of bats. Further comparative study implied that bat microbiota resemble those of the order Carnivora. To discover potential bacterial pathogens, a database was generated containing the 16S rRNA gene sequences of known bacterial pathogens. Potential bacterial pathogens belonging to 12 genera were detected such as Salmonella, Shigella, and Yersinia, among which some have been previously reported in bats. This study demonstrated high resolution and repeatability in detecting organisms of rare existence, and the results could be used as guidance for future bacterial pathogen isolation.

Arsenic trioxide is an effective drug in the treatment of hematologic malignancies, but it has no obvious therapeutic effect on liver cancer. Long non-coding RNA ROR is a newly found long-noncoding RNA that has been reported to get involved in the regulation of chemo-resistance in multiple cancers. However, whether and how long non-coding RNA ROR gets involved in the resistance to arsenic trioxide in liver cancer has not been explored. In this study, We found that cellular apoptosis was increased by arsenic trioxide in liver cancer HepG2 cells; P53 expression was also increased by arsenic trioxide at both mRNA level and protein level, indicating that P53-dependent apoptosis is the main mechanism for arsenic trioxide to induce cytotoxicity in liver cancer HepG2 cells. Meanwhile, we found an obvious increase in the level of long non-coding RNA ROR in arsenic trioxide-treated HepG2 cells. By measuring the level of reactive oxygen species, glutathione, superoxide dismutase, and malondialdehyde, the product of lipid peroxidation, we further demonstrated that oxidative stress was a potential factor for both the activation of P53 expression and the increase in long non-coding RNA ROR expression. Through the knock-down of long non-coding RNA ROR by siRNA, we revealed that the activated long non-coding RNA ROR ameliorated arsenic trioxide-induced apoptosis by inhibiting P53 expression. Together, our study reported that long non-coding RNA ROR conferred arsenic trioxide resistance to liver cancer cells through inhibiting P53 expression, and long non-coding RNA ROR might be a novel sensitizing target for liver cancer treatment.

Multi-spectral sensors consisting of a standard (visible-light) camera and a long-wave infrared camera can simultaneously provide both visible and thermal images. Since thermal images are independent from environmental illumination, they can help to overcome certain limitations of standard cameras under complicated illumination conditions. However, due to the difference in the information source of the two types of cameras, their images usually share very low texture similarity. Hence, traditional texture-based feature matching methods cannot be directly applied to obtain stereo correspondences. To tackle this problem, a multi-spectral visual odometry method without explicit stereo matching is proposed in this paper. Bundle adjustment of multi-view stereo is performed on the visible and the thermal images using direct image alignment. Scale drift can be avoided by additional temporal observations of map points with the fixed-baseline stereo. Experimental results indicate that the proposed method can provide accurate visual odometry results with recovered metric scale. Moreover, the proposed method can also provide a metric 3D reconstruction in semi-dense density with multi-spectral information, which is not available from existing multi-spectral methods.

The interconnected power grid emerges because of the temporal and spatial difference of power generation and power utilization as well as the precondition of considering the complementary resources, safety and reliability. The economic dispatch of multi-area interconnected power grids can realize the effect in scale economies and mutual complementary cooperation in supporting capacities of frequency and voltage, to achieve a wider range of the optimal allocation of resources. Considering the increasing power grid interconnection in the new situation and the trend of resource allocation in the wide range, this paper proposes the economic dispatch method for interconnected power grid considering transmission flexibility. The bus tearing method is applied to split the interconnected power grid, and the decomposition-coordination model is built based on the alternating direction multiplier method. In addition, the alternating direction multiplier idea is introduced to realize the parallel computation of the economic dispatch of each regional power grid. The calculation results of each area are coordinated by the central coordination unit, and the iterative calculation is carried out alternately until the convergence solution is obtained. Numerical example analysis illustrates the effectiveness and economic benefits of the proposed dispatch method.

The widespread usage and ubiquitous distribution of triclocarban (3,4,4′-trichlorocarbanilide, TCC) have raised public concerns about its health effects. At present, there is little information about the genotoxicity of TCC. In this study, we used a battery of genotoxicity testing methods including salmonella reverse mutation test (Ames test), comet assay and micronucleus assay to detect the effects of TCC on gene mutation, DNA breakage, and chromosome damage. The results of Ames test showed that TCC at 0.1–1000 μg/plate did not significantly increase the number of revertant colonies in the four standard Salmonella typhimurium strains, i.e., TA97, TA98, TA100, and TA102, when compared to the vehicle control. The results from comet assay demonstrated that exposure to 5, 10, or 15 μM TCC for 24 h did not significantly increase the percentage of comet cells, tail length (TL), DNA in tail (T DNA%), or olive tail moment (OTM) in keratinocyte HaCaT and hepatic L02 cells. Moreover, TCC did not markedly enhance the frequency of micronucleated cells or micronuclei in HaCaT and L02 cells in the micronucleus assay. Taken together, the results indicated that TCC did not exhibit any genotoxic effects. Our study provides additional information for the safety profile of TCC.

As for the complex integration of power grid planning data and difficulty in meeting the power grid development needs by the current power grid planning simulation and calculation capability, this paper conducted the study on power grid planning data structure system, power grid consistency planning decision-making system by using big data and cloud computing technology. The key technologies, functional architecture and network architecture for the implementation of the power grid consistency planning decision-making system are proposed. The decision-making system for power grid consistency planning is developed to realize the distributed maintenance, structured consistency management and intelligent cloud storage of power grid planning data resources, and realize the dynamic allocation and overall coordination of calculation and verification, which can meet the needs of power grid consistency planning simulation calculations at different management levels and voltage levels, and provide technical support for large-scale power grid planning decision-making. The field application in more than 120 power grid companies illustrates the economic benefits of the developed decision-making system for power grid consistency planning.

Application of exogenous Abs targeting cell surface Ags has been widely used as an experimental approach to induce cell depletion or to inhibit receptor functionality. Moreover, Ab therapy is emerging as one of the mainstream strategies for cancer treatment. Previous studies on the mechanisms of Ab-mediated cell depletion mainly employed Abs from the same species as the research subject. However, there has been a recent trend toward using xenogeneic (cross-species) Abs to achieve cell depletion or block receptor-ligand interactions; with rat Abs used in mice being the most common approach. Considering the molecular differences in Abs from different species, the mechanism(s) of xenogeneic Ab-mediated cell depletion is likely to be different than species-matched Ab supplementation. The current work describes our efforts to identify the mechanism of rat anti-mouse Ly6G (clone: 1A8) mAb mediated depletion of mouse neutrophils. The results showed that neutrophils circulating in the blood but not those in the bone marrow are depleted, and depletion depends on mononuclear phagocyte system, especially liver Kupffer cells that efficiently capture and phagocytize targeted cells. Interestingly, whereas species-matched Ab depletion does not require complement functionality, we found that complement activation significantly facilitates cross-species neutrophil depletion. Finally, we found that some rat mAbs (anti-C5aR, anti-CD11a, anti-CD11b, and anti-VLA4) used to block cell surface receptors also induce cell depletion. Thus, our work strongly recommends controlling for cell depletion effect when using these Abs for receptor blockade purposes.

In this paper, a scalable distributed online algorithm is proposed for solving optimal power flow (OPF) in real time. The operation of distribution systems can be continuously driven towards given OPF targets only depending on local and some aggregated information of each distribution area. Particularly, the proposed algorithm is applicable to the distribution system where each area operates in arbitrary topologies. The algorithm uses the primal-dual gradient method to update DER set-points recurrently based on the sensitivities of the OPF targets; moreover, we decompose the sensitivities into several separate items and give the method to calculate these separate items in a distributed way. The decomposition and distributed calculation methods are all deduced under the general power flow model that completely specifies the physics of electrical networks with arbitrary topologies. The effectiveness of the algorithm is verified using a modified 502-node distribution system. Compared with the online algorithms requiring to process some operation details in a centralized way, the proposed algorithm can achieve almost the same convergence properties with reducing the calculation time sharply.

Swarming behavior of neutrophils has been noticed in both sterile injury and infection models and the mechanisms are being unveiled. So far, no in vitro model has been established to study neutrophil swarming to microbes. In the current study, using live-cell imaging, we observed in vitro neutrophil swarming toward Cryptococcus neoformans, a fungal pathogen causing human meningoencephalitis. Complement C3 and CD11b expression are essential for neutrophils to form cell swarms surrounding C. neoformans. Leukotriene B4 (LTB4) was quickly released by neutrophils during their interactions with C. neoformans. Blockade of LTB4 synthesis inhibited the swarming response to C. neoformans. Importantly, blockade of LTB4 synthesis also significantly reduced neutrophil recruitment in the lung vasculature of mice infected intravenously with C. neoformans, demonstrating a critical role of LTB4 in intravascular neutrophil swarming during infection. Together, this is the first report of neutrophil dynamics of swarming toward a microorganism in vitro, mediated by complement and LTB4.

Extrapulmonary dissemination of Cryptococcus neoformans (C. neoformans) is one of the most critical steps in the development of meningoencephalitis. Here, we report that clearance of the disseminating C. neoformans occurs within the brain microvasculature. Interestingly, the efficiency of the intravascular clearance in the brain is reduced compared to that in the lung. Intravascular clearance is mainly mediated by neutrophils, and complement C5a receptor signaling is crucial for mediating neutrophil recruitment in the vasculature. C. neoformans stimulated actin polymerization of neutrophils is critically involved in their recruitment to the lung, which is associated with the unique vascular structure detected in the lung. The relatively lower efficiency of fungal clearance in the brain vasculature correlates with less efficient recruitment of neutrophils. Accordingly, intravascular clearance of C. neoformans in the brain could be remarkably improved by increasing the recruitment of neutrophils. We conclude that neutrophils have the ability to eliminate C. neoformans arrested in the vasculature. However, insufficient recruitment of neutrophils limited the optimal clearance of this microorganism in the brain. These results imply that a therapeutic strategy aimed at enhancing the accumulation of neutrophils could help prevent cryptococcal meningoencephalitis.

Regular monitoring of drinking water in China is carried out by the Centers for Disease Control and Prevention at all levels and some articles were published for the public to understand the status of drinking water. However, these published articles were limited to small areas and reported almost exclusively in Chinese. In order to give the public a comprehensive understanding of the situation of drinking water sanitation in China and provide specific directions for ensuring drinking water safety in the future, we review the sanitation status of drinking water in different regions of China from 2007 to 2018, the changes over time and the factors affecting drinking water quality by means of systematic review for the first time. Our results show that the quality of drinking water in China has shown an upward trend from 2007 to 2018. The qualification rate of urban drinking water (85.51%) was much higher than that of rural drinking water (51.12%), and the dry season (56.93%) was higher than the wet season (50.54%), and the terminal tap water (59.88%) was higher than the outlet water of waterworks (55.87%). In addition, the regions with low qualification rate of water quality in China were mainly distributed in several southern provinces, such as Yunnan, Guizhou, Hainan, etc. What's more, the qualified rate of the three microbiological indicators was the lowest, all below 85%. All the results indicate that the sanitation status of drinking water in China is unsatisfactory, and the biggest risk affecting water safety is microbial pollution. The central and local governments should work hard to improve people's drinking water quality and continue to strengthen the treatment and supervision of drinking water, especially in rural areas and undeveloped southern areas.

Demand response(DR) has become an effective means to deal with renewable energy integration and load fluctuations in the power system. This article first analyzes the classification and characteristics of controllable resources used in DR. Secondly, taking into consideration the transferable load, interruptible load and the energy storage system in DR, an intra-day scheduling model is then established based on safety constraints. Finally, a case is studied to analyze the role of DR in improving system safety and reducing operating costs. Results show the effectiveness of this model.

The intelligent terminal is a key device in the Power Internet of Things (PIOT), which plays a core role in the process of accurately sensing the state of power equipment and adjusting the user’s electricity behaviour in real time. As a decentralized computing architecture, edge computing plays an important role in improving the data processing capacity and operation reliability of PIOT. This paper describes the operation process of PIOT based on edge computing, by studying the form of intelligent terminals in the field of power transmission, distribution and consumption, putting forward the basic configuration, specific function and principles of intelligent terminal. Combined with the operation characteristics and actual demand of power system, the application analysis of information perception ability and online control ability of intelligent terminal is carried out.

In this paper, a probabilistic load flow computation method based on the cumulants and Edgeworth expansion theory is put forward, and is used in the analysis of system containing wind farms composed of doubly-fed induction generator. Firstly a 2-parameter Weibull function is adopted to fit the random distribution of wind speed, and then the probabilistic model for wind power generator can be established based on active power output characteristic of wind power generator. Based on the linearized AC load flow model, analysis for IEEE 30-node system with wind farm is carried out. Finally the method is compared with Monte-Carlo simulation method, and the effects of wind farms integrated to the operation of power system is analysed in detail.

The rapid development of integrated wind power bring serious challenges to power system operation. In order to address the increasing wind power curtailment problem, the frequency-voltage characteristics concerned optimal dispatch for power system with large-scale wind power integration is proposed in this paper. Through integration of the optimization of frequency characteristics and voltage characteristics into the traditional power system economic dispatch model, the flexibility resources of generation side and load sides in power systems are mobilized to promote large-scale wind power accommodation. The formulated frequency-voltage characteristics concerned optimal dispatch mathematical model is a nonlinear programming model, which is solved by the GAMS platform. The numerical analysis for an actual provincial power grid indicates that the proposed frequency-voltage characteristics concerned optimal dispatch method can promote wind power utilization efficiency and improve the economy of power system operation.

Based on the surface meteorological data of 11 national meteorological stations in the main walnut producing areas of central and southern Hebei province from 1960 to 2017, three distribution functions, including normal distribution, Gumbel distribution and Weibull distribution functions are used to fit the minimum temperature of walnut flowering period, and a probability model of low temperature freezing damage is proposed. The results show that the commonly used probability model is not generally applicable to the freezing damage of walnut’s florescence; different sites of freezing damage of walnut blossom obeyed different probabilistic distribution, Weibull distribution model is more fitting to Gaocheng and Shexian than that of normal distribution fitting model, and the normal distribution model is much suitable for 9 sites such as Lianyuan than Weibull distribution model; comparing the stations in mountainous and plain areas, the mean value varies with the latitudes. The mean value of stations in the eastern foot of Taihang Mountains decreases with the increase of latitude. However, the mean value of stations in the Inner Hill is lower than that of other stations at the same altitude and latitude due to the influence of geographical topography and microclimate. Therefore, the probability of freezing damage is affected by both mean and standard deviation. The extreme weather is more likely to occur in Laiyuan, Inner Hill, Shexian and Gaocheng. The probability of low temperature occurrence is generally consistent with the altitude and latitude and it is also greatly affected by the geographical topography and microclimate.

This paper presents a control architecture for an aerial manipulator operating in indoor environments. The objective is to provide a viable solution to the growing need for indoor assistive technology. The study tries to address the problem of payload pick-and-place with unknown mass. The control structure consists of i) a baseline pitch angle tracking controller that provides satisfactory performance for the quadrotor without a payload; ii) an adaptive augmentation that compensates for the disturbance in the rotational dynamics due to the unknown payload; iii) a horizontal position tracking controller that generates the pitch angle command; iv) a baseline vertical position tracking controller; and v) another adaptive augmentation controller that compensates for the disturbance in the vertical motion from the pick-and-place of the unknown payload. Since the robotic manipulator operates in the vertical plane of symmetry of the quadrotor, the control design is considered for the motion only in this plane. The controller is verified in a simulation environment.

N6-methyladenosine (m6A), the most abundant and reversible RNA modification, plays critical a role in tumorigenesis. However, whether m6A can regulate p53, a leading antitumor protein remains poorly understood. In this study, we explored the regulatory role of m6A on p53 activation using an arsenite-transformed keratinocyte model, the HaCaT-T cell line. We created the cell line by exposing human keratinocyte HaCaT cells to 1 μM arsenite for 5 months. We found that the cells exhibited an increased m6A level along with an aberrant expression of the methyltransferases, demethylase, and readers of m6A. Moreover, the cells exhibited decreased p53 activity and reduced p53 phosphorylation, acetylation, and transactivation with a high nucleus export rate of p53. Knockdown of the m6A methyltransferase, METTL3 significantly decreased m6A level, restoring p53 activation and inhibiting cellular transformation phenotypes in the arsenite-transformed cells. Further, using both a bioinformatics analysis and experimental approaches, we demonstrated that m6A downregulated the expression of the positive p53 regulator, PRDM2, through the YTHDF2-promoted decay of PRDM2 mRNAs. We showed that m6A upregulated the expression of the negative p53 regulator, YY1 and MDM2 through YTHDF1-stimulated translation of YY1 and MDM2 mRNA. Taken together, our study revealed the novel role of m6A in mediating arsenite-induced human keratinocyte transformation by suppressing p53 activation. This study further sheds light on the mechanisms of arsenic carcinogenesis via RNA epigenetics.

In this paper, a stochastic optimization model of transmission network planning considering annual planned maintenance of lines under new energy integration is proposed. This model combines the planning model and maintenance model together, and can determine the optimal transmission capacity of lines and the annual maintenance plan simultaneously. In addition, in order to take into account the uncertainty of wind power output, the multi-scenario probabilistic method is used, and the nonlinear constraints in the model is equivalently linearized, therefore the model can be converted into a mixed integer linear model and can be directly solved by the commercial solver. To validate its effectiveness and superiority, the proposed stochastic optimization model is tested on the IEEE RTS-24 system.

Ostertagia ostertagi (OO) is a widespread parasite that causes chronic infection in cattle and leads to annual losses of billions of dollars in the cattle industry. It remains unclear why cattle are unable to mount an effective immune response despite a large influx of immune cells to the infected abomasal mucosa and draining lymph nodes. Neutrophils, the immune system’s first responders, have the capacity to release neutrophil extracellular traps (NETs) to contain various pathogens, including some parasites. In the present study, the mechanisms by which O. ostertagi influences bovine NET formation were investigated. O. ostertagi larval soluble extract (OO extract) was able to induce typical NETs by purified neutrophils in vitro, confirmed by co-localization of extracellular DNA with typical NET-associated proteins histone and neutrophil elastase (NE). Consistent with existing literature, inhibition assays demonstrated that these OO extract-induced NETs were dependent upon the enzymes NADPH oxidase and myeloperoxidase (MPO). Live OO stage 4 larvae (L4) stimulated neutrophils to form NETs similar to those induced by OO extract. Bovine neutrophils also released NETs in response to Caenorhabditis elegans, a free-living soil nematode, suggesting that bovine NET production may be a conserved mechanism against a broad range of nematodes. This is the first report demonstrating O. ostertagi-induced NET formation by bovine neutrophils, a potentially underappreciated mechanism in the early immune response against nematode infections.

This paper does an extensive analysis of high-speed bipolar junction transistor which includes the structure of the transistor and doping concentration of each region. The main limitations of the desired characteristic are parasitic capacitance and carrier recombination regions. The gain of the amplifier will decrease as the operation frequency increase because of the parasitic capacitance. The bipolar junction transistor design is mainly aiming to reduce the parasitic capacitance and ensure that the recombination occurs at collector region. Furthermore, a photonic circuit is introduced in the project. The photonic circuit is unstable because of a susceptible cavity. The circuit can be enhanced by introducing a feedback control circuit. This work will also use the designed BJT to construct a feedback control circuit which includes a differential amplifier and a reference current generator. The feedback control circuit will not only make the photonic circuit stable but also be efficient and low noise. The layout of the full feedback control circuit and the structure of the BJT are presented to illustrate the effectiveness of the designed strategy for controlling on-chip photonic circuits.

With the increasing penetration of distribution generations, distribution system is characterized by complex injection uncertainties, which brings formidable challenges for distribution network operation. As distributed renewable energy penetrating into power network, the operation mechanism and control strategy of distribution network become more complex, which makes it necessary to adjust the control measures to improve the operation quality and efficiency. In order to deal with the increasing uncertainties caused by renewable generations, a voltage aware synergetic dispatch method of active distribution network is proposed. By accounting for the voltage regulation characteristics of all kinds of generators and loads, flexible network topology and participation mechanism of regulation reserves of synchronous generators and connected transmission network in response to uncertainties, an optimization model of voltage aware synergetic dispatch of active distribution network is constructed. The proposed model is formulated as a mixed-integer nonlinear optimization problem and is resolved by the combination of firefly algorithm and nonlinear primal-dual interior-point method. Finally, case studies on the modified IEEE 33-bus distribution system are conducted to illustrate the effectiveness of the proposed method.

Arsenite exposure can induce a biphasic response called "hormesis", and oxidative stress has been proposed to play critical roles in the hormesis effect. However, the precise mechanisms underlying the hormesis effect induced by arsenite is largely unknown. Recently, N

This paper proposes a novel frequency aware robust economic dispatch (FARED) approach to exploit the synergistic capability of accommodating uncertain loads and renewable generation by accounting for both the frequency regulation effect and optimal participation mechanism of secondary regulation reserves for conventional units in response to uncertainties in the robust optimization counterpart of security constrained economic dispatch. The FARED is formulated as a robust optimization problem. In this formulation the allowable frequency deviation and the possible load or renewable generation curtailments are expressed in terms of variable uncertainty sets. The variables in the formulation are described as interval variables and treated in affine form. In order to improve the computational tractability, the dominant constraints which can be the candidates of tight transmission constraints are determined by complementarity constraints. Then the robust optimization problem is simplified to a bilinear programming problem based on duality theory. Finally, the effectiveness and efficiency of the proposed method are illustrated based on several study cases.

Neutrophils have been shown to efficiently kill Cryptococcus neoformans , a causative agent of meningoencephalitis. Here, using live-cell imaging, we characterize the dynamic interactions of neutrophils with C. neoformans and the underlying mechanisms in real time. Neutrophils were directly seen to chase C. neoformans cells and then rapidly internalize them. Complement C5a-C5aR signaling guided neutrophils to migrate to the yeast cells, resulting in optimal phagocytosis and subsequent killing of the organisms. The addition of recombinant complement C5a enhanced neutrophil movement but did not induce chemotaxis, suggesting that the C5a gradient is crucial. Incubation with C. neoformans resulted in enhanced activation of Erk and p38 mitogen-activated protein (MAP) kinases (MAPKs) in neutrophils. Inhibition of the p38 MAPK pathway, but not the Erk pathway, significantly impaired neutrophil migration and its subsequent killing of C. neoformans . Deficiency of CD11b or blocking of CD11b did not affect the migration of neutrophils toward C. neoformans but almost completely abolished phagocytosis and killing of the organisms by neutrophils. C5a-C5aR signaling induced enhanced surface expression of CD11b. Interestingly, the original surface expression of CD11b was essential and sufficient for neutrophils to attach to C. neoformans but was unable to mediate phagocytosis. In contrast, the enhanced surface expression of CD11b induced by C5a-C5aR signaling was essential for neutrophil phagocytosis and subsequent killing of yeast cells. Collectively, this is the first report of the dynamic interactions of neutrophils with C. neoformans , demonstrating a crucial role of C5a-C5aR signaling in neutrophil killing of C. neoformans in real time.

Although neutrophils are typically the first immune cells attracted to an infection site, little is known about how neutrophils dynamically interact with invading pathogens in vivo. Here, with the use of intravital microscopy, we demonstrate that neutrophils migrate to the arrested Cryptococcus neoformans, a leading agent to cause meningoencephalitis, in the brain microvasculature. Following interactions with C. neoformans, neutrophils were seen to internalize the organism and then circulate back into the bloodstream, resulting in a direct removal of the organism from the endothelial surface before its transmigration into the brain parenchyma. C. neoformans infection led to enhanced expression of adhesion molecules macrophage 1 antigen on neutrophils and ICAM-1 on brain endothelial cells. Depletion of neutrophils enhanced the brain fungal burden. Complement C3 was critically involved in the recognition of C. neoformans by neutrophils and subsequent clearance of the organism from the brain. Together, our finding of the direct removal of C. neoformans by neutrophils from its arrested site may represent a novel mechanism of host defense in the brain, in addition to the known, direct killing of microorganisms at the infection sites. These data are the first to characterize directly the dynamic interactions of leukocytes with a microbe in the brain of a living animal.

Although gamma interferon (IFN-γ) and interleukin-10 (IL-10) have been shown to be critically involved in the pathogenesis of African trypanosomiasis, the contributions to this disease of CD4 + and CD8 + T cells, the major potential producers of the two cytokines, are incompletely understood. Here we show that, in contrast to previous findings, IFN-γ was produced by CD4 + , but not CD8 + , T cells in mice infected with Trypanosoma brucei . Without any impairment in the secretion of IFN-γ, infected CD8 −/− mice survived significantly longer than infected wild-type mice, suggesting that CD8 + T cells mediated mortality in an IFN-γ-independent manner. The increased survival of infected CD8 −/− mice was significantly reduced in the absence of IL-10 signaling. Interestingly, IL-10 was also secreted mainly by CD4 + T cells. Strikingly, depletion of CD4 + T cells abrogated the prolonged survival of infected CD8 −/− mice, demonstrating that CD4 + T cells mediated protection. Infected wild-type mice and CD8 −/− mice depleted of CD4 + T cells had equal survival times, suggesting that the protection mediated by CD4 + T cells was counteracted by the detrimental effects of CD8 + T cells in infected wild-type mice. Interestingly, CD4 + T cells also mediated the mortality of infected mice in the absence of IL-10 signaling, probably via excessive secretion of IFN-γ. Finally, CD4 + , but not CD8 + , T cells were critically involved in the synthesis of IgG antibodies during T. brucei infections. Collectively, these results highlight distinct roles of CD4 + and CD8 + T cells in the context of IFN-γ and IL-10 during T. brucei infections.

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The stalk sugar content in silage maize plays an important role in improving its forage quality and palatability. In this study, we reported a dynamic quantitative trait loci (QTL) analysis of stalk sugar content at different growth stages in maize. A recombinant inbred line (RIL) population with 202 lines derived from a cross of YXD053 × Y6-1 was used to identify the dynamic QTL for stalk sugar content (Brix) in maize. The Brix of RILs were measured at four stages in two environments. Twenty-two QTLs affecting maize stalk sugar content (Brix) were detected by unconditional mapping method. Fifteen QTLs were identified using conditional mapping approach. No QTL was detected at all sampling stages. Six QTL, qSSC-2.1, qSSC-2.2, qSSC-2.3, qSSC-5.1, qSSC-9.1 and qSSC-9.4, were detected by both unconditional and conditional mapping. One major QTL qSSC-2.1 flanked by markers bnlg1909 and umc1635 on chromosome 2 had a relatively high net effects of gene expression from anthesis stage to 20 days after anthesis. A total of six pairs of QTL with significant epistatic effects were identified at different developmental stages. No significant QTL × environment interactions were observed. Stalk sugar content is controlled by a complex genetic mechanism, and the QTL detected at different development stages might be important contributors to stalk sugar content in maize.

With the large-scale integration of volatile wind power generations, power system operation and planning face the problem of increasing injection fluctuations and uncertainties. In this paper, chance constraint expressions are used to characterize the wind power uncertainty, and then a new chance-constrained programming model for reference network with wind power integration is proposed to ensure the expected wind power utilization. In the proposed model, the objective function is minimizing total power generation cost and transmission investment cost, and the constraints are the safety operation technical requirements under intact operation state and the preconceived contingency operation state. The sample average approximation (SAA) method is used to develop a deterministic approach for the proposed model. Numerical analysis shows the potential benefit of the proposed model.

The active participation of demand side resources in power grid operation not only benefits the individual participant but also benefits the whole system. The optimal goal can promote by excavating the active behaviors of demand side. The welfare maximization of market participant is the driving force of such active behaviors. Considering the independence of each user's behavior, the consumer's utility function is selected to depict consumer's preference and demand response behavior. In order to coordinate the consumers' maximum welfare with social welfare maximization, consumers' utility function and units' operation cost are integrated into Unit Commitment (UC) model. The objective function is to maximize social welfare, by subtracting units' operation cost from consumers' total utility, and this objective can be acquired. Considering the proposed model should be solved in a distributed manner, the idea of the centralized coordination and the decentralized decision-making is proposed. Based on the Lagrangian relaxation (LR) principle and distributed real-time pricing scheme, a closed-loop feedback mechanism is constructed to reflect the relationship among generator output, price level, and load demand. The ten generating units example can illustrate the effectiveness of the proposed method.

To deal with the increasing penetration of uncertainties caused by renewable generations and uncertain loads, this paper proposes a novel robust optimization model for the optimal power flow (OPF) problem of power systems. In the model proposed, the generation and the network topology are co-optimized, and then the proposed robust optimal power flow with transmission switching (ROPF_TS) model is converted to be a two-stage mixed-integer optimization model based on the duality theory. Based on Benders decomposition, the model is decomposed into a master problem and a slave problem, the master problem corresponds to the resolution of the deterministic optimal power flow with transmission switching problem under base-point mode, the slave problem corresponds to the robust optimal power flow with the given network topology, and then the feasible domain of the master problem is restrained by the Benders cuts developed by the slave problem. Finally, Example analyses are conducted to verify the validity of the proposed model and its solution methodology.

The alterations of micro RNAs (miRNAs) and their potential roles in arsenite-induced tumorigenesis are still poorly understood. In this study, miRNA Array was used to detect the expression level of miRNAs in human bronchial epithelial (HBE) cells that were transformed by 2.5 μM arsenite for 13 weeks. These cells exhibited a neoplastic phenotype manifested by increased levels of cellular proliferation and migration and clone formation. Subsequently, 191 dysregulated miRNAs were identified to be associated with arsenite-induced transformation by miRNA Array. Among them, six miRNAs were validated by their expression levels with quantitative real-time polymerase chain reaction (qPCR), and 17 miRNAs were further explored via their target genes as well as regulatory network. Three databases, TargetMiner, miRDB, and TarBase, were used to predict the target genes of the 17 miRNAs, and a total of 954 common genes were sorted. Results of Gene Ontology (GO) analyses showed that the 954 genes were involved in diverse terms of GO categories, such as positive regulation of macroautophagy, epithelial cell maturation, and synaptic vesicle clustering. Moreover, results of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses demonstrated that most of these target genes were enriched in various cancer-related pathways, including non-small cell lung cancer, Wnt signaling pathway, cell cycle, and p53 signaling pathway. The miRNA-gene regulatory network, which was constructed by cytoscape software with miRNAs and their target genes, showed that miR-15b-5p, miR-106b-5p, and miR-320d were the core hubs. Collectively, our results provide new insights into miRNA-mediated mechanisms underlying arsenite-induced transformation, although more experimental verification is still needed to prove these predictions.

This paper proposes a novel optimization model for optimal reactive power flow concerning wind power generation, which considers generator voltage regulation characteristics. Synchronous generators (SGs) static excitation error control characteristics and doubly fed induction generator(DFIG) wind farm reactive power (var)-voltage control characteristics are considered. An extra inner potential node is introduced to reflect the excitation limits. Complementarity constraints are applied to represent the wind farm var-voltage control. Power fluctuation caused by the variability and uncertainty of wind generation are considered based on scenario analysis. Nonlinear primal-dual interior point algorithm is used to get the optimal strategies. Case study demonstrates effectiveness of the proposed approach.

In this paper, a new method for reference network considering network topology optimization is proposed. The actual operation mode optimization and the correction control with transmission switching under the contingency situation are taken into account in the proposed method. Based on the forecasted load values of each period in predictive multi-time scale and candidate transmission line schemes of future planning time horizon, a new optimal model for reference network is built. In the proposed model, the objective function is minimizing annual power generation cost and transmission cost, and the constraints are the safety operation technical requirements under normal operation state and N-1 accident operation state. The proposed model is a complex mixed-integer nonlinear problem mathematically, and can be converted to a mixed-integer linear programming problem. Finally, case studies are conducted to illustrate the effectiveness of the proposed method.

For the randomness and asynchronous characteristics of wind power and photovoltaic (PV) generation, large-scale integration of renewable generations into power grid, especially when the electric network topology is fixed, has brought the problems of transmission congestion and voltage security in power system operation. In order to make better use of existing network to promote security and economy of power system, this paper proposes an optimal power flow with transmission switching for power system with wind and PV generation integration. By making full use of the time-domain complementarity characteristics of wind/PV generation, the mathematical model of optimal power flow (OPF) with transmission switching is constructed based on alternating current (AC) power flow to ensure voltage security and improve flexibility of power system operation. Then a combination of genetic algorithm (GA) and the nonlinear primal-dual interior point method is proposed to solve the proposed model. Finally, case studies on a realistic system demonstrate the feasibility and effectiveness of the proposed method.

With the diversified development of electrical loads, and the large-scale integration of volatile renewable generations, power system operation, control and planning face the challenge of increasing injection uncertainties. In this paper, a new method for reference network considering nodal injection uncertainties is proposed. The actual operation mode optimization and reserve configuration of power grid as well as the correction control under the contingency situation are taken into account in the proposed method. Based on the forecasted interval values of nodal injection power of each period in predictive multi-time scale and candidate transmission line schemes of future planning time horizon, a new optimal model for reference network is built. In the proposed model, the objective function is minimizing annual power generation cost, reserve cost and transmission cost, and the constraints are the safety operation technical requirements under normal operation state and N-1 accident operation state. The proposed model is an interval optimization problem mathematically, and can be converted to a linear programming problem. Finally, case studies are conducted to illustrate the effectiveness of the proposed method.

With the increase of wind power penetration rate, the effect of large-scale wind power influence on static voltage security of power grid is gradually significant. The fluctuation of wind power output will lead to the possibility of voltage instability. To deal with static voltage security risk caused by wind power, this paper proposes an online assessment method. Firstly, the relationship between security limitation and power flow status is trained offline through GA-SVM from continuation power flow (CPF) sample. Secondly, wind power probabilistic forecasting carry out online through fluctuation variation Markov Chain model. Finally, static voltage security risk is assessed online by calculating operation status probability and distance to security limitation. The validity of proposed method is proved by IEEE 9 bus system.

Artemisinin-based drugs are documented to possess anticancer potential that is selectively effective to cancer cells. However, this selectivity is disputable in different studies and the mechanism is still unclear. To clarify this discrepancy, this study employed five assays to evaluate the cytotoxic effects of artemisinin and artesunate on normal human bronchial epithelial (HBE) cells and lung adenocarcinoma A549 cells. The results of five cytotoxic assays coherently showed that artemisinin and artesunate caused dose-dependent cytotoxicity in both HBE and A549 cells with a slight selectivity to A549 cells. Further, both HBE cells and A549 cells demonstrated elevated levels of intracellular reactive oxygen species (ROS) and increased DNA damage. Since artemisinin and artesunate exerted significant cytotoxic effect on both normal cells and cancer cells via the same pathway of ROS-mediated DNA damage, the side effects of artemisinin and artesunate on normal cell cannot be ignored when developing their antitumor effects.