Broadband photoelectric fusion transceiver-multiplexed conversion system with high spurious rejection.

In this paper, a broadband photoelectric fusion transceiver-multiplexed system is proposed to realize a frequency converter. The system achieves a high spurious suppression ratio through two frequency conversions that utilize the advantages of microwave and photonics technology simultaneously to reduce the complexity of the system and improve the effective spectrum utilization. In addition, the core components, such as the Mach-Zehnder modulator (MZM), are multiplexed in the up and down frequency conversion link. High-frequency local oscillator (LO) signals are used to keep image frequency signals and various kinds of spurious signals obtained by beating frequency outside the system bandwidth. Experimental results demonstrate that the operating frequency ranges from 2 to 18 GHz with high performance for both transmitter and receiver. The image rejection is 57.35 dB for up-conversion and 46.56 dB for down-conversion, and the in-band spurious suppression achieves at least 55.02 dB. At the same time, the spurious-free dynamic range (SFDR) can reach at least 89.11d B⋅H z 2/3.

Variation pattern in the macromolecular (cellulose, hemicelluloses, lignin) composition of cell walls in Pinus tabulaeformis tree trunks at different ages as revealed using multiple techniques.

The plant cell wall is a complex, heterogeneous structure primarily composed of cellulose, hemicelluloses, and lignin. Exploring the variations in these three macromolecules over time is crucial for understanding wood formation to enhance chemical processing and utilization. Here, we comprehensively analyzed the chemical composition of cell walls in the trunks of Pinus tabulaeformis using multiple techniques. In situ analysis showed that macromolecules accumulated gradually in the cell wall as the plant aged, and the distribution pattern of lignin was opposite that of polysaccharides, and both showed heterogenous distribution patterns. In addition, gel permeation chromatography (GPC) results revealed that the molecular weights of hemicelluloses decreased while that of lignin increased with age. Two-dimensional heteronuclear single quantum coherence nuclear magnetic resonance (2D-HSQC NMR) analysis indicated that hemicelluloses mainly comprised galactoglucomannan and arabinoglucuronoxylan, and the lignin types were mainly comprised guaiacyl (G) and p-hydroxyphenyl (H) units with three main linkage types: ß-O-4, ß-ß, and ß-5. Furthermore, the C-O bond (ß-O-4) signals of lignin decreased while the C-C bonds (ß-ß and ß-5) signals increased over time. Taken together, these findings shed light on wood formation in P. tabulaeformis and lay the foundation for enhancing the processing and use of wood and timber products.

Research on ultrawideband photodetector module based on parasitic parameter regulation.

A four-channel ultrawideband photodetector (PD) module with a size of 26.1 mm ×33.2 mm × 8.5 mm has been demonstrated in our laboratory. We propose a method to improve the bandwidth of the PD module based on compensating parasitic parameters by dual resistance regulation on the P and N terminals of the PD chip. A small signal equivalent circuit model with package matching network is established for the PD module, and the effectiveness of the proposed method and the accuracy of the model are verified by experiments. A four-channel photodetector module with a -3 dB bandwidth of up to 67 GHz is fabricated by using photodetector chips with -3 dB bandwidths of 46 GHz, and the responsivity is up to 0.50A/W.

3D reconstruction and multi-omics analysis reveal a unique pattern of embryogenesis in Ginkgo biloba.

Ginkgo (Ginkgo biloba L.) is one of the earliest extant species in seed plant phylogeny. Embryo development patterns can provide fundamental evidence for the origin, evolution, and adaptation of seeds. However, the architectural and morphological dynamics during embryogenesis in Ginkgo biloba (G. biloba) remain elusive. Herein, we obtained over 2200 visual slices from three stages of embryo development using micro-computed tomography imaging with improved staining methods. Based on 3D spatio-temporal pattern analysis, we found that a shoot apical meristem with seven highly differentiated leaf primordia, including apical and axillary leaf buds, is present in mature Ginkgo embryos. 3D rendering from the front, top, and side views showed two separate transport systems of tracheids located in the hypocotyl and cotyledon, representing a unique pattern of embryogenesis. Furthermore, the morphological dynamic analysis of secretory cavities indicated their strong association with cotyledons during development. In addition, we identified genes GbLBD25a (lateral organ boundaries domain 25a), GbCESA2a (cellulose synthase 2a), GbMYB74c (myeloblastosis 74c), GbPIN2 (PIN-FORMED 2) associated with vascular development regulation, and GbWRKY1 (WRKYGOK 1), GbbHLH12a (basic helix-loop-helix 12a), GbJAZ4 (jasmonate zim-domain 4) potentially involved in the formation of secretory cavities. Moreover, we found that flavonoid accumulation in mature embryos could enhance post-germinative growth and seedling establishment in harsh environments. Our 3D spatial reconstruction technique combined with multi-omics analysis opens avenues for investigating developmental architecture and molecular mechanisms during embryogenesis and lays the foundation for evolutionary studies of embryo development and maturation.

A unified dataset for the city-scale traffic assignment model in 20 U.S. cities.

City-scale traffic data, such as traffic flow, speed, and density on every road segment, are the foundation of modern urban research. However, accessing such data on a city scale is challenging due to the limited number of sensors and privacy concerns. Consequently, most of the existing traffic datasets are typically limited to small, specific urban areas with incomplete data types, hindering the research in urban studies, such as transportation, environment, and energy fields. It still lacks a city-scale traffic dataset with comprehensive data types and satisfactory quality that can be publicly available across cities. To address this issue, we propose a unified approach for producing city-scale traffic data using the classic traffic assignment model in transportation studies. Specifically, the inputs of our approach are sourced from open public databases, including road networks, traffic demand, and travel time. Then the approach outputs comprehensive and validated citywide traffic data on the entire road network. In this study, we apply the proposed approach to 20 cities in the United States, achieving an average correlation coefficient of 0.79 in average travel time and an average relative error of 5.16% and 10.47% in average travel speed when compared with the real-world data.

Highly sensitive and specific graphene oxide-based FRET aptasensor for quantitative detection of human soluble growth stimulating gene protein 2.

Soluble growth stimulation expressed gene 2 (sST2) is a new generation biomarker in the diagnosis and prognosis of heart failure (HF). Here, the sST2-specific aptamers were selected from a random ssDNA library with the full length of 88 nucleotides (nt) via target-immobilized magnetic beads (MB)-based systematic evolution of ligands by exponential enrichment (SELEX) technology. After eight rounds of selection, six aptamers with the most enrichment were selected. Among, the aptamer L1 showed the high-affinity binding to sST2 with the lowest Kd value (77.3 ± 0.05 nM), which was chosen as the optimal aptamer for further molecular docking. Then, the aptamer L1 was used to construct a graphene oxide (GO) - based fluorescence resonance energy transfer (FRET) biosensor for sST2, which exhibits a linear detection range of 0.1-100 µg/ml and a detection limit of 3.7 ng/ml. The aptasensor was applied to detect sST2 in real samples, with a good correlation and agreement with the traditional enzyme-linked immunosorbent assay (ELISA) when quantitative analyzing the sST2 concentration in serum samples from HF patients. The results show that not only an efficient strategy for screening the practicable aptamer, but also a rapid and sensitive detection platform for sST2 were established.

Bacillus sp. as a microbial cell factory: Advancements and future prospects.

Bacillus sp. is one of the most distinctive gram-positive bacteria, able to grow efficiently using cheap carbon sources and secrete a variety of useful substances, which are widely used in food, pharmaceutical, agricultural and environmental industries. At the same time, Bacillus sp. is also recognized as a safe genus with a relatively clear genetic background, which is conducive to the industrial production of target metabolites. In this review, we discuss the reasons why Bacillus sp. has been so extensively studied and summarize its advances in systems and synthetic biology, engineering strategies to improve microbial cell properties, and industrial applications in several metabolic engineering applications. Finally, we present the current challenges and possible solutions to provide a reliable basis for Bacillus sp. as a microbial cell factory.

Improving acetoin production through construction of a genome-scale metabolic model.

Acetoin was widely used in food, medicine, and other industries, because of its unique fragrance. Bacillus amyloliquefaciens was recognized as a safe strain and a promising acetoin producer in fermentation. However, due to the complexity of its metabolic network, it had not been fully utilized. Therefore, a genome-scale metabolic network model (iJYQ746) of B. amyloliquefaciens was constructed in this study, containing 746 genes, 1736 reactions, and 1611 metabolites. The results showed that Mg2+, Mn2+, and Fe2+ have inhibitory effects on acetoin. When the stirring speed was 400 rpm, the maximum titer was 49.8 g L-1. Minimization of metabolic adjustments (MOMA) was used to identify potential metabolic modification targets 2-oxoglutarate aminotransferase (serC, EC 2.6.1.52) and glucose-6-phosphate isomerase (pgi, EC 5.3.1.9). These targets could effectively accumulate acetoin by increasing pyruvate content, and the acetoin synthesis rate was increased by 610% and 10%, respectively. This provides a theoretical basis for metabolic engineering to reasonably transform B. amyloliquefaciens and produce acetoin.

Metabolic analysis of Schizochytrium sp. mutants with high EPA content achieved with ARTP mutagenesis screening.

Eicosapentaenoic acid (EPA) belonged to the ω-3 series of polyunsaturated fatty acids and had physiological functions lipid as regulating blood lipid and preventing cardiovascular diseases. Schizochytrium sp. was considered to be a potential industrial fermentation strain of EPA because of its fast growth, high oil content, and simple fatty acid composition. However, Schizochytrium sp. produced EPA with low production efficiency and a long synthesis path. This research aims to improve the yield of EPA in Schizochytrium sp. by ARTP mutagenesis and to reveal the mechanism of high-yield EPA through transcriptome analysis. ARTP mutagenesis screening yielded the mutant M12 that whereas the productivity of EPA increased 108% reaching 0.48 g/L, the total fatty acid concentration was 13.82 g/L with an increase of 13.7%. The transcriptomics revealed 2995 differentially expressed genes were identified between M12 and the wild-type strain and transcripts involved in carbohydrate, amino acid, energy, and lipid metabolism were up-regulated. Among them, the hexokinase (HK) and the phosphofructokinase genes (PFK), which can catalyze pyruvate to acetyl-CoA, were increased 2.23-fold and 1.78-fold. Glucose-6-phosphate dehydrogenase (G6PD) and glutamate dehydrogenase (GLDH), which can both generate NADPH, were increased by 1.67-fold and 3.11-fold. Furthermore, in the EPA synthesis module, the expression of 3-oxoacyl-[acyl-carrier protein] reductase(fabG) and carbonyl reductase 4 / 3-oxoacyl-[acyl-carrier protein] reductase beta subunit(CBR4), also up-regulated 1.11-fold and 2.67-fold. These may lead to increases in cell growth. The results provide an important reference for further research on promoting fatty acid and EPA accumulation in Schizochytrium sp.

Bone age recognition based on mask R-CNN using xception regression model.

Background and Objective: Bone age detection plays an important role in medical care, sports, judicial expertise and other fields. Traditional bone age identification and detection is according to manual interpretation of X-ray images of hand bone by doctors. This method is subjective and requires experience, and has certain errors. Computer-aided detection can effectually enhance the validity of medical diagnosis, especially with the fast development of machine learning and neural network, the method of bone age recognition using machine learning has gradually become the focus of research, which has the advantages of simple data pretreatment, good robustness and high recognition accuracy. Methods: In this paper, the hand bone segmentation network based on Mask R-CNN was proposed to segment the hand bone area, and the segmented hand bone region was directly input into the regression network for bone age evaluation. The regression network is using an enhancd network Xception of InceptionV3. After the output of Xception, the convolutional block attention module is connected to refine the feature mapping from channel and space to obtain more effective features. Results: According to the experimental results, the hand bone segmentation network model based on Mask R-CNN can segment the hand bone region and eliminate the interference of redundant background information. The average Dice coefficient on the verification set is 0.976. The mean absolute error of predicting bone age on our data set was only 4.97 months, which exceeded the accuracy of most other bone age assessment methods. Conclusion: Experiments show that the accuracy of bone age assessment can be enhancd by using the Mask R-CNN-based hand bone segmentation network and the Xception bone age regression network to form a model, which can be well applied to actual clinical bone age assessment.

Fast testing of partial camera lenses based on a liquid crystal spatial light modulator.

Today, there are strict requirements for the quality inspection of mobile phone cameras, as the design tolerance is getting critically tighter. In order to avoid unnecessary disposal of lens components when testing and assembling the complete cameras, testing the quality of each single lens group in advance before the final assembly is effective. However, as part of a whole camera, a single lens group cannot generate a sharp image independently; it needs to be combined with other elements in the testing system and assembled precisely. In order to address this challenge, we propose a fast testing method based on spatial light modulators (SLMs). By taking advantage of the programmable feature of the SLM, the assembly misalignments caused by fixing the lens group to be tested into the testing system are dynamically scanned and compensated at a fast speed. A design criterion of the phase map pattern to be loaded on the SLM is also verified by simulation and is applied on the testing system. In this way, the proposed method significantly reduces the positioning requirement of the lens under test, and thus improves efficiency. The passed yield of tested lens groups reaches 92.6%.

Cytology, transcriptomics, and mass spectrometry imaging reveal changes in late-maturation elm (Ulmus pumila) seeds.

During seed maturation, the seed deposits storage compounds (starches, oils, and proteins), synthesizes defense compounds, produces a seed coat, initiates embryo dormancy, and becomes desiccated. During the late-maturation stage, seed storage compound contents and compositions change dramatically. Although maturation has been extensively studied in model species and crops, it remains less well characterized in woody perennial plants. In this study, we conducted morphological and cytological observations, transcriptome profiling, and chemical constituent analysis of elm (Ulmus pumila L.) seeds during the late-maturation stage. Light and electron microscopy revealed that closely packed yet discrete lipid bodies frequently surrounded the densely stained protein bodies, and the protein bodies became irregular or even partially disintegrated at the end of seed development. RNA-seq detected substantial transcriptome changes during the late-maturation stage, and pathway enrichment analysis showed that the differentially expressed genes were associated with phenylpropanoid biosynthesis, starch and sucrose metabolism, plant-pathogen interactions, and hormone signal transduction. Furthermore, we used mass spectrometry imaging to detect the relative intensity and spatial distribution of fatty acids, phospholipids, and waxes in elm seeds. Our findings provide a framework for understanding the changes in cytological features and chemical composition during the final stage of elm seed development, and a detailed reference for seed development in woody plants.

An Improved Approach towards Multi-Agent Pursuit-Evasion Game Decision-Making Using Deep Reinforcement Learning.

A pursuit-evasion game is a classical maneuver confrontation problem in the multi-agent systems (MASs) domain. An online decision technique based on deep reinforcement learning (DRL) was developed in this paper to address the problem of environment sensing and decision-making in pursuit-evasion games. A control-oriented framework developed from the DRL-based multi-agent deep deterministic policy gradient (MADDPG) algorithm was built to implement multi-agent cooperative decision-making to overcome the limitation of the tedious state variables required for the traditionally complicated modeling process. To address the effects of errors between a model and a real scenario, this paper introduces adversarial disturbances. It also proposes a novel adversarial attack trick and adversarial learning MADDPG (A2-MADDPG) algorithm. By introducing an adversarial attack trick for the agents themselves, uncertainties of the real world are modeled, thereby optimizing robust training. During the training process, adversarial learning was incorporated into our algorithm to preprocess the actions of multiple agents, which enabled them to properly respond to uncertain dynamic changes in MASs. Experimental results verified that the proposed approach provides superior performance and effectiveness for pursuers and evaders, and both can learn the corresponding confrontational strategy during training.

Regulatory utility of pharmacometrics in the development and evaluation of antimicrobial agents and its recent progress in China.

Pharmacometrics is an emerging science that interprets drug, disease, and trial information in a mathematical fashion to inform and facilitate efficient drug development and/or regulatory decisions. Pharmacometrics study is increasingly adopted in the regulatory review of new antimicrobial agents. We summarized the 31 antimicrobial agents approved by the US Food and Drug Administration (FDA) and the 26 antimicrobial agents approved by European Medicines Agency (EMA) from January 2001 to May 2019. We also reviewed recent examples of utilizing pharmacometrics to support antimicrobial agent's registration in China, including modeling and simulation methods, effects of internal/external factors on pharmacokinetic (PK) parameters, safety and efficacy evaluation in terms of exposure-response analysis, refinement of the wording of product labeling and package leaflet, and possible postmarketing clinical trial. Ongoing communication among regulator, academia, and industry regarding pharmacometrics is encouraged to streamline and facilitate the development of new antimicrobial agents. The industry can maximize its benefit in drug development through continued pharmacometrics education/training.

Plant multiscale networks: charting plant connectivity by multi-level analysis and imaging techniques.

In multicellular and even single-celled organisms, individual components are interconnected at multiscale levels to produce enormously complex biological networks that help these systems maintain homeostasis for development and environmental adaptation. Systems biology studies initially adopted network analysis to explore how relationships between individual components give rise to complex biological processes. Network analysis has been applied to dissect the complex connectivity of mammalian brains across different scales in time and space in The Human Brain Project. In plant science, network analysis has similarly been applied to study the connectivity of plant components at the molecular, subcellular, cellular, organic, and organism levels. Analysis of these multiscale networks contributes to our understanding of how genotype determines phenotype. In this review, we summarized the theoretical framework of plant multiscale networks and introduced studies investigating plant networks by various experimental and computational modalities. We next discussed the currently available analytic methodologies and multi-level imaging techniques used to map multiscale networks in plants. Finally, we highlighted some of the technical challenges and key questions remaining to be addressed in this emerging field.

HIF-1α Enhances Vascular Endothelial Cell Permeability Through Degradation and Translocation of Vascular Endothelial Cadherin and Claudin-5 in Rats With Burn Injury.

The mechanism underlying burn injury-induced enhanced vascular endothelial permeability and consequent body fluid extravasation is unclear. Here, the rat aortic endothelial cells (RAECs) were treated with the serum derived from rats with burn injury to elucidate the mechanism. Sprague-Dawley (SD) rats were grouped as follows (10 rats/group): control, 2, 4, 8, 12, and 24 hours postburn groups. The heart, liver, kidney, lung, jejunum, and ileum of rats injected with 2% Evans blue (EB) through the tail vein were excised to detect the EB level in each organ. The serum levels of hypoxia-inducible factor-1α (HIF-1α) and endothelin-1 (ET-1) were examined using enzyme-linked immunosorbent assay (ELISA). The effect of serum from 12-hour postburn group on the membrane permeability of RAEC monolayer, as well as on the mRNA and protein levels of ET-1, endothelin receptor A (ETA), ETB, and zonula occludens (ZO-1), was analyzed using quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting. The membrane permeability of GV230/HIF-1α-transfected or shRNA-HIF-1α-transfected RAECs, as well as the expression levels of HIF-1α, ET-1, ETA, ETB, vascular endothelial (VE)-cadherin, and claudin-5, was analyzed using qRT-PCR and western blotting, whereas the localization of VE-cadherin and claudin-5 was examined using immunofluorescence. The serum HIF-1α and ET-1 levels in the burn groups, which peaked at 12 hours postburn, were significantly upregulated (P < .01) when compared with those in the control group. Additionally, the serum HIF-1α levels were positively correlated with vascular permeability. Compared with the shRNA-negative control-transfected RAECs, the shRNA-II/HIF-1α-transfected RAECs exhibited downregulated expression of HIF-1α, ET-1, ETA, and ETB (P < .01), and upregulated expression of ZO-1, claudin-5, and VE-cadherin (P < .05). Compared with the GV230-transfected RAECs, the GV230/HIF-1α-transfected RAECs exhibited upregulated expression of HIF-1α, ET-1, ETA, and ETB (P < .01), and downregulated expression of ZO-1, claudin-5, and VE-cadherin (P < .05). The GV230/HIF-1α-transfected RAECs exhibited degradation and translocation of VE-cadherin and claudin-5. In addition to degradation of VE-cadherin and claudin-5, HIF-1α mediated enhanced endothelial cell permeability through upregulation of ET-1, ETA, and ETB, and downregulation of ZO-1 and VE-cadherin in rats with burn injury.

The main sources of circulating cell-free DNA: Apoptosis, necrosis and active secretion.

Cell-free DNA (cfDNA) as an emerging biomarker with huge potential for clinical application, especially in the field of liquid biopsy. The field is now in a critical transitional period in which cfDNA-based analysis is developing rapidly. No doubt learning more about the biological knowledge of cfDNA is beneficial to catalyze this transformation process. Therefore, in this review we have summarized the characteristics of cfDNA, including its structure and origin of tissues, in order to provide researchers with a more holistic insight of cfDNA. Subsequently, we focused on the pathways that cfDNA releases from cells, such as apoptosis, necrosis, and active secretion. Additionally, the clearance of cfDNA derived from both cellular death and active secretion in the physiological environment is also discussed. Finally, we have mentioned the link between cfDNA active secretion and tumor microenvironment.

High-efficiency procedure to characterize, segment, and quantify complex multicellularity in raw micrographs in plants.

BACKGROUND: The increasing number of novel approaches for large-scale, multi-dimensional imaging of cells has created an unprecedented opportunity to analyze plant morphogenesis. However, complex image processing, including identifying specific cells and quantitating parameters, and high running cost of some image analysis softwares remains challenging. Therefore, it is essential to develop an efficient method for identifying plant complex multicellularity in raw micrographs in plants. RESULTS: Here, we developed a high-efficiency procedure to characterize, segment, and quantify plant multicellularity in various raw images using the open-source software packages ImageJ and SR-Tesseler. This procedure allows for the rapid, accurate, automatic quantification of cell patterns and organization at different scales, from large tissues down to the cellular level. We validated our method using different images captured from Arabidopsis thaliana roots and seeds and Populus tremula stems, including fluorescently labeled images, Micro-CT scans, and dyed sections. Finally, we determined the area, centroid coordinate, perimeter, and Feret's diameter of the cells and harvested the cell distribution patterns from Voronoï diagrams by setting the threshold at localization density, mean distance, or area. CONCLUSIONS: This procedure can be used to determine the character and organization of multicellular plant tissues at high efficiency, including precise parameter identification and polygon-based segmentation of plant cells.

Deep Reinforcement Learning Approach with Multiple Experience Pools for UAV's Autonomous Motion Planning in Complex Unknown Environments.

Autonomous motion planning (AMP) of unmanned aerial vehicles (UAVs) is aimed at enabling a UAV to safely fly to the target without human intervention. Recently, several emerging deep reinforcement learning (DRL) methods have been employed to address the AMP problem in some simplified environments, and these methods have yielded good results. This paper proposes a multiple experience pools (MEPs) framework leveraging human expert experiences for DRL to speed up the learning process. Based on the deep deterministic policy gradient (DDPG) algorithm, a MEP-DDPG algorithm was designed using model predictive control and simulated annealing to generate expert experiences. On applying this algorithm to a complex unknown simulation environment constructed based on the parameters of the real UAV, the training experiment results showed that the novel DRL algorithm resulted in a performance improvement exceeding 20% as compared with the state-of-the-art DDPG. The results of the experimental testing indicate that UAVs trained using MEP-DDPG can stably complete a variety of tasks in complex, unknown environments.

Effects of hypoxia inducible factor-1α on expression levels of MLCK, p-MLC and ZO-1 of rat endothelial cells.

OBJECTIVE: To examine the aberrant expression of endothelial permeability associated proteins including MLCK, p-MLC and ZO-1 in presence of different levels of hypoxia-inducible factor 1 alpha (HIF-1α). METHODS: We established monolayer vascular endothelial cell model with the primary rat endothelial cells. Over-expressed or under-expressed HIF-1α cell lines were made by endothelial cells transfected with plasmid vector constructed with HIF-1α gene or HIF-1α-specific short hairpin RNA (shRNA). Levels of mRNA and protein of MLCK, p-MLC and ZO-1 were determined using Real-Time PCR and Western blot. All data were analyzed using by One-Way ANOVA method and LSD. RESULTS: We successfully cultured the rat endothelial primary cells for four days. The mRNA and protein levels of MLCK and p-MLC were significantly increased in the HIF-1α over-expression group than that in the blank control group and the empty plasmid GV230 group (P＜0.05). ZO-1 was significantly lower in the HIF-1α over-expression group than that in the blank control group and the GV230 group. On the contrary, the mRNA and protein levels of MLCK and p-MLC were significantly lower in the HIF-1α under-expression group than that in the blank control group and the shRNA-NC group (P＜0.05). ZO-1 was significantly higher in the HIF-1α low-expression group than that in the blank control group and the shRNA-NC group. CONCLUSION: HIF-1α positively regulates the expression of MLCK and p-MLC and negatively regulates the expression of ZO-1 in rat monolayer endothelial cells.