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Aims The adsorption of lead ions from aqueous solution by macroporous Ca-alginate-lignin (MCAL) beads immobilized with Clostridium tyrobutyricum and free strains was evaluated. Methods and Results The effects of different factors including pH, adsorption time, adsorbent dosage and initial concentration of lead ions were explored. Different characterization methods were used to evaluate the adsorption process of lead ions. Meanwhile, the adsorption kinetics models and adsorption isotherm models were applied. The fitting results showed that the adsorption behaviour of C. tyrobutyricum immobilized in MCAL beads and free strains was better described by the pseudo-second-order kinetic model and the adsorption process followed the Langmuir isotherm model. The maximum biosorption of lead ions by C. tyrobutyricum immobilized in MCAL beads and free strains was 144.9 and 106.4 mg/g respectively. Conclusions The C. tyrobutyricum immobilized in MCAL beads proved to be practicable and had better adsorption effects on lead ions compared with the free strains. Significance and Impact of the Study The paper demonstrated a new insight and strategy for the effective treatment of lead ions from aqueous solutions by the novel function of C. tyrobutyricum.

The flexible ReS2/P(VDF-TrFE) hybrid photodetector could be enhanced by a ferroelectric field and strain field.

With the growing number of facilities applying nuclear technology in China, a high-performance portable gamma-ray camera that uses well-developed gamma-ray imaging techniques is increasingly required. To fulfill this requirement, we have designed a camera using a self-supported mask, a CsI(Na) array coupled to a silicon photomultiplier (SiPM) rather than the traditional position-sensitive photomultiplier tube (PSPMT) and a highly integrated readout circuit. In addition, with the elimination of multi-Compton events in the crystal array based on a row/column readout circuit incorporated into the data processing method, the peak-to-valley ratio of the flood source map and the image quality quantified by the contrast-to-noise ratio index of 137Cs were improved significantly by 25.8% from 9.8 to 12.3 and 14.8% from 38.7 to 45.0, respectively.

Microbes have proven to be robust workhorses for the large-scale production of many chemicals. Especially, high-value biochemicals (e.g., natural pigments, unsaturated fatty acids) that cannot be derived from fossil fuels, can be produced by engineered microbes. There is a growing interest in both academia and industry to find new technologies that can enhance the efficiencies of microbial cell factories and boost the circular bioeconomy. Rapid technological innovations, such as microbial genome editing and synthetic biology, have greatly advanced the production of chemicals in engineered microbes. Nanomaterial-based technologies that exploit the unique physiochemical properties of nano-scale materials (e.g., large surface area, excellent catalytic activity, tunable optical and electrical performance) have demonstrated great potential and attracted increasing attention. There are many studies showing that nanomaterials can assist microbes in the synthesis of chemicals by providing micronutrients, inducing anti-ROS responses, promoting gas-liquid mass transfer, immobilizing microbial cells and promoting electron transfer in electrosynthesis. Furthermore, the latest studies demonstrate that nanomaterials can be used to construct photocatalyst-microbe hybrids and achieve solar driven chemical production. In this review, we comprehensively summarize these advances and discuss the current gaps as well as future perspectives. With the rapid development of synthetic biology and nanotechnology, we believe more nanomaterial-based technologies will be developed and used to improve the productivity of microbial cell factories.

Purpose Non-small cell lung cancer (NSCLC) is the first leading cause of cancer-related death globally. Long noncoding RNA KCNQ1 overlapping transcript 1 (KCNQ1OT1) was involved in the progression of multiple cancers by sponging target miRNA. We aimed to explore the pathological mechanism of KCNQ1OT1 in NSCLC progression. Methods The expression of KCNQ1OT1, miR-204-5p and autophagy-related gene 3 (ATG3) was measured by quantitative real-time polymerase chain reaction (qRT-PCR). 3-(4, 5-Dimethyl-2-thiazolyl)-2, 5-diphenyl-2-H-tetrazolium bromide (MTT) assay and flow cytometry assay were conducted for the detection of cell proliferation and apoptosis, respectively. Western blot assay was performed to examine the protein levels of B-cell lymphoma-2 (BCL-2), BCL2-Associated X (Bax), cleaved caspase-3, cleaved caspase-9 and LC3Ⅱ/LC3Ⅰ and P62. The interaction between miR-204-5p and KCNQ1OT1 or ATG3 was validated by dual-luciferase reporter system and RNA immunoprecipitation (RIP) assay. Murine xenograft assay was conducted to explore the function of KCNQ1OT1 in vivo. Immunohistochemistry (IHC) staining assay was used for the analysis of ki67-positive cell percentage. Results The expression of KCNQ1OT1 and ATG3 was up-regulated whereas miR-204-5p was down-regulated in NSCLC tumors and cells. MiR-204-5p was inversely correlated with KCNQ1OT1 or ATG3. In addition, KCNQ1OT1 knockdown facilitated apoptosis, inhibited autophagy and proliferation of NSCLC cells in vitro and blocked tumor growth in vivo. However, the miR-204-5p inhibitor reversed the effects. More importantly, ATG3 was a target gene of miR-204-5p and ATG3 overexpression restored the effect of miR-204-5p on NSCLC cell progression. Conclusion KCNQ1OT1 promotes cell proliferation and autophagy and inhibits cell apoptosis via regulating miR-204-5p/ATG3 axis, providing a promising target for NSCLC therapy.

A number of studies have shown that gastrointestinal manifestations co-exist with respiratory symptoms in coronavirus disease 2019 (COVID-19) patients. Xuanfei Baidu decoction (XFBD) was recommended by the National Health Commission to treat mild and moderate COVID-19 patients and proved to effectively alleviate intestinal symptoms. However, the exact mechanisms remain elusive.This study aimed at exploring potential mechanisms of XFBD by utilizing a mouse model of dextran sulfate sodium (DSS)-induced acute experimental colitis, mimicking the disease conditions of intestinal microecological disorders.The network pharmacology approach was employed to identify the potential targets and pathways of XFBD on the intestinal disorders. Mice with DSS-induced intestinal disorders were utilized to evaluate the protective effect of XFBD in vivo, including body weight, disease activity index (DAI) score, colon length, spleen weight, and serum tumor necrosis factor-α (TNF-α) level. Colon tissues were used to perform hematoxylin-eosin (HE) staining, western blot analysis, and transcriptome sequencing. Macrophages, neutrophils and the proportions of T helper cell (Th) 1 and Th2 cells were measured by flow cytometry. Intestinal contents were collected for 16S rRNA gene sequencing.Network pharmacology analysis indicated that XFBD inhibited the progression of COVID-19-related intestinal diseases by repressing inflammation. In mice with DSS-induced intestinal inflammation, XFBD treatment significantly reduced weight loss, the spleen index, the disease activity index, TNF-α levels, and colonic tissue damage, and prevented colon shortening. Transcriptomics and flow cytometry results suggested that XFBD remodeled intestinal immunity by downregulating the Th1/Th2 ratio. Western blot analysis showed that XFBD exerted its anti-inflammatory effects by blocking the nuclear factor-κB (NF-κB) signaling pathway. Indicator analysis of microbiota showed that 75 operational taxonomic units (OTUs) were affected after XFBD administration. Among them, Akkermansia, Muribaculaceae, Lachnospiraceae, and Enterorhabdus were simultaneously negatively correlated with intestinal disorders' parameters, and Bacteroides, Escherichia-Shigella, Eubacterium nodatum,Turicibacter, and Clostridium sensu stricto 1, showed positive correlations with intestinal disorders' parameters.Our data indicate that XFBD treatment attenuated intestinal disorders associated with inhibiting inflammation, remodeling of intestinal immunity, and improving intestinal flora. These findings provide a scientific basis for the clinical use of XFBD and offer a potential therapeutic approach for the treatment of COVID-19 patients with intestinal symptoms.

Acetylation is one of the most important methods of modification that lead to a change in the function of proteins. In humans, metabolic enzymes commonly undergo acetylation, which regulates the activities of metabolic enzymes and metabolic pathways. Sirtuin 3 (SIRT3) is a prominent deacetylase that participates in mitochondrial metabolism, redox balance, and mitochondrial dynamics by regulating mitochondrial protein acetylation, thereby protecting mitochondria from damage. Normal mitochondrial function is essential for maintaining the metabolism and function of the heart. Therefore, mitochondrial dysfunction caused by SIRT3 consumption and defects leads to the development of a variety of cardiovascular diseases. A comprehensive understanding of the role of SIRT3 in cardiovascular disease is critical for developing new therapeutic strategies. Herein, we summarize the function of SIRT3 in mitochondria, the complex mechanisms mediating cardiovascular diseases, and the potential value of SIRT3 small-molecule agonists in future clinical treatments.

Background Facilitating the primary health care (PHC) system and maintaining people’s reasonable healthcare-seeking behavior are key to establishing a sustainable healthcare system. China has employed a multitiered copayment system/medical insurance differentiated payment policies to incentivize the public to utilize PHC services through its hierarchical medical care system; however, most people still prefer visiting tertiary care hospitals. We question whether the quality gap in healthcare services reduces the effect of the multitiered copayment system, which is considered an important factor in the lack of reform in the Chinese healthcare system. Thus, we explore the effect and influencing factors of the multitiered copayment system that drives primary healthcare-seeking behavior under the current situation with a large quality gap. We also consider the hypothetical situation of a reduced gap in the future. Methods This study used the hypothetical quality improvement scenario to elicit people’s hypothetical behaviors, and a multistage stratified cluster random sampling method. This preliminary study was conducted in 2016 using 1829 individuals from four regions of Wenzhou in Zhejiang Province: Ouhai, Ruian, Yongjia, and Taishun. A descriptive statistical analysis, chi-square analysis, Fisher’s exact test, and multinomial logistic regression model were performed to introduce the effect of the multitiered copayment system, and to explore the factors affecting the selection of PHC institutions at pre- and post-change phases. Result The results show that compared with the large quality gap phase, the number of respondents who believed the multitiered copayment system had an effect on their selection of PHC institutions after the equalization of healthcare services quality increased threefold (from 14.0% to 50.8%). Moreover, the main determinants in people’s selection of PHC institutions changed from age and needs variables (self-rated health status) to age, needs variables (self-rated health status) and enabling variables (distance to a medical care facility). Conclusion The results indicate limited initial effects of the multitiered copayment system. However, they become more pronounced after the equalization of healthcare services quality. This study confirms that changes in the quality gap in healthcare services influence the effect of the multitiered copayment system. Hence, reducing this gap can help achieve the intended outcome of the tiered healthcare insurance schedule.

Background. Facilitating the primary health care (PHC) system and maintaining people’s reasonable health-seeking behavior are key to establishing a sustainable healthcare system. China has employed a multitiered copayment system to incentivize the public to utilize PHC services through its hierarchical medical care system; however, most people still prefer visiting tertiary care hospitals. Methods. This preliminary study was conducted in 2016 on 1831 individuals from four regions of Wenzhou in Zhejiang Province to explore the effect and influencing factors of the multitiered copayment system that drives their primary healthcare-seeking behavior. We question whether a quality gap in healthcare services influences the minimal effect of the multitiered copayment system, which existing literature has considered as an important factor in the lack of reform in the Chinese healthcare system. We discuss the effect of the policy following the current situation in which there exists a large gap and further consider the hypothetical situation of a reduced gap in the future. Result. The results indicate that the initial effects of the multitiered copayment system was limited. However, they become more pronounced after the equalization of the quality of healthcare services. Moreover, the main determinants in people’s selection of PHC institutions changed from age and needs variables (self-rated health status) to age and enabling variables (distance to a medical care facility). Conclusion. This study confirms that changes in the quality gap in healthcare services influence the multitiered copayment system. Hence, reducing this gap can help to achieve the intended outcome of the tiered healthcare insurance schedule.

According to previous research studies, automated quayside cranes (AQCs) and automated guided vehicles (AGVs) in automated container terminals have a high potential synergy. In this paper, a collaborative scheduling model for AQCs and AGVs is established and the capacity limitation of the transfer platform on AQCs is considered in the model. The minimum total energy consumption of automated quayside cranes (AQCs) and Automatic Guided Vehicles (AGVs) is taken as the objective function. A two-stage taboo search algorithm is adopted to solve the problem of collaborative scheduling optimization. This algorithm integrates AQC scheduling and AGV scheduling. The optimal solution to the model is obtained by feedback from the two-stage taboo search process. Finally, the Qingdao Port is taken as an example of a data experiment. Ten small size test cases are solved to evaluate the performance of the proposed optimization methods. The results show the applicability of the two-stage taboo search algorithm since it can find near-optimal solutions, precisely and accurately.

The Gamma-Ray Integrated Detectors (GRID) is a space mission concept dedicated to monitoring the transient gamma-ray sky in the energy range from 10 keV to 2 MeV using scintillation detectors onboard CubeSats in low Earth orbits. The primary targets of GRID are the gamma-ray bursts (GRBs) in the local universe. The scientific goal of GRID is, in synergy with ground-based gravitational wave (GW) detectors such as LIGO and VIRGO, to accumulate a sample of GRBs associated with the merger of two compact stars and study jets and related physics of those objects. It also involves observing and studying other gamma-ray transients such as long GRBs, soft gamma-ray repeaters, terrestrial gamma-ray flashes, and solar flares. With multiple CubeSats in various orbits, GRID is unaffected by the Earth occultation and serves as a full-time and all-sky monitor. Assuming a horizon of 200 Mpc for ground-based GW detectors, we expect to see a few associated GW-GRB events per year. With about 10 CubeSats in operation, GRID is capable of localizing a faint GRB like 170817A with a 90% error radius of about 10 degrees, through triangulation and flux modulation. GRID is proposed and developed by students, with considerable contribution from undergraduate students, and will remain operated as a student project in the future. The current GRID collaboration involves more than 20 institutes and keeps growing. On August 29th, the first GRID detector onboard a CubeSat was launched into a Sun-synchronous orbit and is currently under test., accepted for publication in Experimental Astronomy

Deep probabilistic aspect models are widely utilized in document analysis to extract the semantic information and obtain descriptive topics. However, there are two problems that may affect their applications. One is that common words shared among all documents with low representational meaning may reduce the representation ability of learned topics. The other is introducing supervision information to hierarchical topic models to fully utilize the side information of documents that is difficult. To address these problems, in this article, we first propose deep diverse latent Dirichlet allocation (DDLDA), a deep hierarchical topic model that can yield more meaningful semantic topics with less common and meaningless words by introducing shared topics. Moreover, we develop a variational inference network for DDLDA, which helps us to further generalize DDLDA to a supervised deep topic model called max-margin DDLDA (mmDDLDA) by employing max-margin principle as the classification criterion. Compared to DDLDA, mmDDLDA can discover more discriminative topical representations. In addition, a continual hybrid method with stochastic-gradient MCMC and variational inference is put forward for deep latent Dirichlet allocation (DLDA)-based models to make them more practical in real-world applications. The experimental results demonstrate that DDLDA and mmDDLDA are more efficient than existing unsupervised and supervised topic models in discovering highly discriminative topic representations and achieving higher classification accuracy. Meanwhile, DLDA and our proposed models trained by the proposed continual learning approach cannot only show good performance on preventing catastrophic forgetting but also fit the evolving new tasks well.

The gamma-ray imaging technique was developed and is widely used in several nuclear engineering fields. Specifically, compared with the traditional point-by-point radiation detector, the coded-aperture gamma camera has advantages of a wide field of view, high angular resolution, and high efficiency. Several methods for characterizing image quality, including the figure of merit (FOM) method and the contrast-to-noise ratio (CNR) method, were assessed and developed. These methods have their respective drawbacks depending on the circumstances. The FOM lacks reliability in exhibiting the impact of background noise fluctuation on the purity of a real image. The CNR characterizes image quality with inconsistent sensitivity while the source moves along the X and Y directions. Therefore, a new CNR method was proposed to achieve better performance and greater consistency in real imaging. With our coded-aperture imaging system developed in the laboratory, we performed simulations within the MATLAB and Geant4 platforms and real imaging experiments to analyze and compare images and the results of these three characterization methods. The results show that the new CNR method is reliable and practical in regard to real imaging performance.

The coordination of different container-handling equipment is an important method for improving the overall efficiency of automated container terminals. In the real terminal, we should consider many real-life issues, such as the equipment capacity, the equipment collision, changing lanes in the multi-lane road, and choosing one of container-handling lanes for each container. This paper proposes the integrated scheduling problem of three container-handling equipment with the capacity constraint and the dual-cycle strategy, for simultaneously solving the equipment scheduling problem, the assignment problem of the container-handling lane and the conflict-free route planning problem of automated guided vehicles (AGVs). With the objective of minimizing the ship’s berth time, we propose a mixed-integer programming model based on the space-time network representation method and two bilevel optimization algorithms based on conflict resolution rules. Finally, numerical experiments are conducted to verify the effectiveness of the proposed model and two bilevel optimization algorithms.

We propose Switching Poisson gamma dynamical systems (SPGDS) to model sequentially observed multivariate count data. Different from previous models, SPGDS assigns its latent variables into mixture of gamma distributed parameters to model complex sequences and describe the nonlinear dynamics, meanwhile, capture various temporal dependencies. For efficient inference, we develop a scalable hybrid stochastic gradient-MCMC and switching recurrent autoencoding variational inference, which is scalable to large scale sequences and fast in out-of-sample prediction. Experiments on both unsupervised and supervised tasks demonstrate that the proposed model not only has excellent fitting and prediction performance on complex dynamic sequences, but also separates different dynamical patterns within them.

Janibacter, a member of the Intrasporangiaceae family of Actinobacteria, is a Janus-faced bacterium that has both antibiotic resistance/pathogenicity and the ability to degrade pollutants, with significant research value. Here, we isolated the novel strain Janibacter melonis M714 from an irradiated area in Xinjiang Uygur Autonomous Region, China. J. melonis M714 contains one circular chromosome of 3,426,637 bp with a GC content of 72.98% and one plasmid of 54,436 bp with a GC content of 67.80%. The genome of J. melonis M714 contains 2,859 CDSs, 47 tRNA genes, and 6 rRNA genes. Genome assembly and annotation indicated that strain M714 has a high GC content and contains multiple notable functional genes, including a beta-lactam resistance gene and dioxygenase gene, which may be the key determinants of the strain’s antibiotic resistance and xenobiotic degradation ability, respectively. The whole genome sequences of J. melonis M714 provide information that is useful for its potential applications in the degradation of pollutants and environmental remediation.

Due to the uncertainty and complexity of multilinks and multifactors in urban express logistics system, it is very difficult to analyze the risk factors and the correlation among them for urban public security. In this paper, a method combining domain knowledge and data learning is proposed to construct Bayesian network, which can effectively deal with this problem. Based on the literature review and the investigation of transportation companies, this paper summarizes the risk factors to public safety caused by pick up, warehouse storage, transport, and the end distribution in the process of urban express logistics, which are divided into 5 dimensions: management, weather, human, transportation tools and facilities, and goods, including 11 risk factors. In this paper, Interpretative Structural Model is used to construct the initial hierarchical model to describe the complex relationship between factors, and then causal mapping method is used to improve the initial model to transform the structure into the final Bayesian network model. Finally, the sensitivity of one node to other nodes is analyzed based on the incident data. The results show that Bayesian network is effective in improving urban express logistics operation ability and avoiding public safety risks and has a strong generalization ability, which is simple and easy in practical application.

Pathological cardiac hypertrophy is a complex process and eventually develops into heart failure, in which the heart responds to various intrinsic or external stress, involving increased interstitial fibrosis, cell death and cardiac dysfunction. Studies have shown that oxidative stress is an important mechanism for this maladaptation. Cyclophilin A (CyPA) is a member of the cyclophilin (CyPs) family. Many cells secrete CyPA to the outside of the cells in response to oxidative stress. CyPA from blood vessels and the heart itself participate in a variety of signaling pathways to regulate the production of reactive oxygen species (ROS) and mediate inflammation, promote cardiomyocyte hypertrophy and proliferation of cardiac fibroblasts, stimulate endothelial injury and vascular smooth muscle hyperplasia, and promote the dissolution of extracellular matrix (ECM) by activating matrix metalloproteinases (MMPs). The events triggered by CyPA cause a decline of diastolic and systolic function and finally lead to the occurrence of heart failure. This article aims to introduce the role and mechanism of CyPA in cardiac hypertrophy and remodeling, and highlights its potential role as a disease biomarker and therapeutic target.

Hydrophobic CuS nanodisk assemblies and the anticancer drug paclitaxel (PTX) have been co-encapsulated into hybrid silica nanocapsules using a triblock copolymer®F127 (PEO106PPO70PEO106) micelle based soft-template method under mild conditions. The as-prepared CuS-PTX/SiO2 composite nanocapsules have excellent biocompatibility, solubility and high colloidal stability in physiological environments and also exhibit an enhanced photothermal conversion efficiency (PCE) of up to 31.2% as a result of the localized surface plasmon resonance (LSPR) effects. Owing to the hydrophobic-hydrophobic interaction and the silica shell protection, the PTX encapsulation ratio could reach 41.25% and the loaded PTX can undergo sustained release and controlled by near infrared (NIR) laser irradiation. In addition, in vitro and in vivo studies demonstrated the remarkable antitumor effects of the CuS-PTX/SiO2 nanocapsules under NIR laser irradiation (980 nm, 1 W cm-2) for 5 minutes. Hence, the designed novel CuS nanodisk assembly based CuS-PTX/SiO2 nanoplatform shows great potential for synergetic chemo-photothermal cancer therapy.

Currently, position check-in on mobile devices has become a fashionable social activity. Meanwhile, criminals probably tamper the geographical position (geo-position) information to provide an alibi. Therefore, it is of importance to identify the authenticity of geo-position. To our knowledge, many current methods for geo-position spoofing detection mainly rely on geo-position information in the database. However, these methods possibly fail in the case of missing prior information or lacking rich training samples. To address that challenge, this paper proposes an alternative manner for detecting the geo-position spoofing via camera sensor fingerprint. In particular, the camera sensor fingerprint is first extracted through the images posted by an inquiry user based on the well-designed denoising filter. Second, the authenticity of the geo-position is verified by comparing the consistency of the residual noise from newly-posted images with position check-in and the unique camera sensor fingerprint from an inquiry user. Finally, the extensive experiments are conducted on the image database, that empirically indicates the relevance of our proposed simple but effective method.

Pomegranate peels are an abundant agricultural waste material with a high content of carbohydrates and bioactive compounds. The aim of this study was to efficiently convert waste pomegranate peels (WPP) into high-value-added products. First, high yields of phenolics (12.2%) and bioactive pectin (24.8%) were obtained via enzymatic pretreatment. The lignin was subsequently degraded using an integrated method combining heteropolyacids as catalyst and biomass-derived γ-valerolactone as sustainable solvent and cellulase-catalyzed hydrolysis. The optimal degradation conditions were found to encompass a temperature of 293 K, reaction time of 3 h and catalyst loading with 30 mM heteropolyacids. Under these conditions, the enzymatic hydrolysis efficiency was enhanced significantly, leading to a yield of 93.3% glucose from the obtained cellulosic feedstock. Finally, the fermentable sugars together with the previously recovered pectin from WPP were firstly used as carbon source to evaluate their suitability as feedstock for butyric acid production using Clostridium tyrobutyricum.