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Background Heterosis has been widely used for breeding high-yield crops, changes crop breeding and agricultural production by increasing yield. Transcriptome profiles of sorghum spikes in hybrid Jinnuo 3 and its parents 10480A and L17R were performed by RNA sequencing technology at secondary branch and spikelet differentiation period. Results During above two differentiation period, there were 2,641 and 2,175 differentially expressed genes (DEGs) between Jinnuo 3 and 10480A, respectively. Meanwhile, there were 1,387 and 1,094 DEGs between Jinnuo 3 and L17R, respectively. These indicated that massive DEGs were existed between hybird and its parents, and a more similar expression pattern was presented between hybrid and male parent. Gene expression inheritance analysis showed that most of genes were expressed additively, suggesting that the complementary effect may play a foundation role in sorghum spike heterosis. Among non-additive expression genes, L17R-dominant genes were predominant, indicating that male parent may provide beneficial alleles with great contribution to heterosis. GO and KEGG analysis suggested that metabolic pathways, such as photosynthetic antenna protein, photosynthesis, carbon fixation in photosynthetic organisms, amino acid metabolism, glycolysis, and endoplasmic reticulum protein processing, would participate in yield heterosis formation in hybrid Jinnuo 3. Further analysis showed that photosynthesis-related genes PsbW, PsbR, Lhca2, Lhcb1 and LAX3, spike structure development-related genes MADS1, MADS7, MADS16 and MADS55, as well as stress resistance-related genes WRKY14, WRKY35, HSFB2C and HSP70, might play an important role in yield heterosis formation in hybrid Jinnuo 3. Conclusion Hybrids Jinnuo 3 increased yield by simultaneously increasing source (photosynthetic efficiency-related genes), library (spike development-related genes), and resistance (inresistance-related genes). This molecular mechanism could provide new clues for sorghum heterosis utilization and high-yield breeding.

The internal states of generators obtained by dynamic states estimation (DSE) may provide additional information for the control performances. However, conventional sigma-point Kalman filter (SPKF)-based DSE may experience the loss of positive definiteness and symmetricalness of state noise covariances. This article proposes three numerically stable square-root SPKF (SR-SPKF) algorithms and proposes a novel derivative-free SR-SPKF-based DSE framework to estimate the dynamic states for doubly fed induction generator (DFIG) wind turbines in an interconnected power network. While this article investigates the dynamic behavior of the power grid at a system-level, the DSE of DFIG is achieved in a decentralized manner, which is made possible by the use of phasor measurement units (PMUs) to acquire and transmit voltage and current phasors at DFIG terminal. By utilizing the SR-SPKF-based DSE framework and PMUs data, a comparison study is conducted for square-root unscented Kalman filter, square-root Cubature Kalman filter, square-root central difference Kalman filter, and their conventional versions. The computational burden, estimation accuracy, and mathematical capability of each filtering algorithm are compared and analyzed through simulation studies.

Coronary artery disease (CAD) is regarded as the principal cause of cardiovascular diseases and one of the leading causes of mortality. In order to alleviate the risk of CAD, percutaneous coronary intervention (PCI) and stent implantation have recently been applied. In particular, Mg alloy (Mg-alloy) stents (MAS) have been used as clinical routine for the treatment of CAD. However, emerging evidence suggests that this treatment strategy is substantially associated with coronary in-stent restenosis (ISR), which remains the main cause of unintentional and repeat drug-eluting stent (DES) interventions in the United States. In this regard, understanding of MAS as friend or foe of ISR treatment is needed to establish the exact mechanism underlying this condition. This mini review therefore aimed to provide an integrated view on the existing findings of the relationship between MAS and ISR. The understanding of MAS as either a friend or foe is crucial for the management of ISR, which is reported to be very challenging amidst lack of effective therapeutic options.

This study aims to investigate the effect of adding different types of mature compost amendments and sulfur powder on nitrogen loss and compost maturity of food waste. High-throughput sequencing was used to analyze the bacterial community during composting. Results showed that the secondary fermentation mature compost mixed with sulfur powder group had the most reduction of ammonia emission (56.3%) and the primary fermentation mature compost amendments were the most effective for nitrous oxide emission reduction (36.9%). The temperature, pH well as the nitrogen forms transformation of the pile significantly affect the nitrogen loss during composting. Firmicutes helped to promote the rapid warming of the pile and Actinobacteria and Proteobacteria played an important role in decomposition of organic matter. Thermobifida and Ureibacillus had main contribution to the rapid degradation of organic matter in the process of composting. The relative abundance of nitrogen-fixing bacteria were higher and the relative abundance of predominantly ammonifying and denitrifying bacteria were lower than control group, with different additives addition.

Coronavirus disease 2019 has seriously affected the world. One major protective measure for individuals is to wear masks in public areas. Several regions applied a compulsory mask-wearing rule in public areas to prevent transmission of the virus. Few research studies have examined automatic face mask detection based on image analysis. In this paper, we propose a deep learning based single-shot light-weight face mask detector to meet the low computational requirements for embedded systems, as well as achieve high performance. To cope with the low feature extraction capability caused by the light-weight model, we propose two novel methods to enhance the model’s feature extraction process. First, to extract rich context information and focus on crucial face mask related regions, we propose a novel residual context attention module. Second, to learn more discriminating features for faces with and without masks, we introduce a novel auxiliary task using synthesized Gaussian heat map regression. Ablation studies show that these methods can considerably boost the feature extraction ability and thus increase the final detection performance. Comparison with other models shows that the proposed model achieves state-of-the-art results on two public datasets, the AIZOO and Moxa3K face mask datasets. In particular, compared with another light-weight you only look once version 3 tiny model, the mean average precision of our model is 1.7% higher on the AIZOO dataset, and 10.47% higher on the Moxa3K dataset. Therefore, the proposed model has a high potential to contribute to public health care and fight against the coronavirus disease 2019 pandemic.

Expansion microscopy (ExM) allows super-resolution imaging on conventional fluorescence microscopes, but has been limited to proteins and nucleic acids. Here we develop click-ExM, which integrates click labeling into ExM to enable a 'one-stop-shop' method for nanoscale imaging of various types of biomolecule. By click labeling with biotin and staining with fluorescently labeled streptavidin, a large range of biomolecules can be imaged by the standard ExM procedure normally used for proteins. Using 18 clickable labels, we demonstrate click-ExM on lipids, glycans, proteins, DNA, RNA and small molecules. We demonstrate that click-ExM is applicable in cell culture systems and for tissue imaging. We further show that click-ExM is compatible with signal-amplification techniques and two-color imaging. Click-ExM thus provides a convenient and versatile method for super-resolution imaging, which may be routinely used for cell and tissue samples.

Metabolic labeling of glycans with clickable unnatural sugars has enabled glycan analysis in multicellular systems. However, cell-type-specific labeling of glycans in vivo remains challenging. Here we develop genetically encoded metabolic glycan labeling (GeMGL), a cell-type-specific strategy based on a bump-and-hole pair of an unnatural sugar and its matching engineered enzyme. N-pentynylacetylglucosamine (GlcNAl) serves as a bumped analog of N-acetylglucosamine (GlcNAc) that is specifically incorporated into glycans of cells expressing a UDP-GlcNAc pyrophosphorylase mutant, AGX2

Recognition of facial expressions plays an important role in understanding human behavior, classroom assessment, customer feedback, education, business, and many other human-machine interaction applications. Some researchers have realized that using features corresponding to different scales can improve the recognition accuracy, but there is a lack of a systematic study to utilize the scale information. In this work, we proposed a hierarchical scale convolutional neural network (HSNet) for facial expression recognition, which can systematically enhance the information extracted from the kernel, network, and knowledge scale. First, inspired by that the facial expression can be defined by different size facial action units and the power of sparsity, we proposed dilation Inception blocks to enhance kernel scale information extraction. Second, to supervise relatively shallow layers for learning more discriminated features from different size feature maps, we proposed a feature guided auxiliary learning approach to utilize high-level semantic features to guide the shallow layers learning. Last, since human cognitive ability can progressively be improved by learned knowledge, we mimicked such ability by knowledge transfer learning from related tasks. Extensive experiments on lab-controlled, synthesized, and in-the-wild databases showed that the proposed method substantially boosts performance, and achieved state-of-the-art accuracy on most databases. Ablation studies proved the effectiveness of modules in the proposed method.

The anatomy of the superior mesenteric vessels is complex, yet important, for right-sided colorectal surgery. The usefulness of three-dimensional (3D) printing of these vessels in right hemicolon cancer surgery has rarely been reported. In this prospective clinical study, 61 patients who received laparoscopic surgery for right hemicolon cancer were preoperatively randomized into 3 groups: 3D-printing (20 patients), 3D-image (19 patients), and control (22 patients) groups. Surgery duration, bleeding volume, and number of lymph node dissections were designed to be the primary end points, whereas postoperative complications, post-operative flatus recovery time, duration of hospitalization, patient satisfaction, and medical expenses were designed to be secondary end points. To reduce the influence of including different surgeons in the study, the surgical team was divided into 2 groups based on surgical experience. The duration of surgery for the 3D-printing and 3D-image groups was significantly reduced (138.4 ± 19.5 and 154.7 ± 25.9 min vs. 177.6 ± 24.4 min, P = 0.000 and P = 0.006), while the number of lymph node dissections for the these 2 groups was significantly increased (19.1 ± 3.8 and 17.6 ± 3.9 vs. 15.8 ± 3.0, P = 0.001 and P = 0.024) compared to the control group. Meanwhile, the bleeding volume for the 3D-printing group was significantly reduced compared to the control group (75.8 ± 30.4 mL vs. 120.9 ± 39.1 mL, P = 0.000). Moreover, patients in the 3D-printing group reported increased satisfaction in terms of effective communication compared to those in the 3D-image and control groups. Medical expenses decreased by 6.74% after the use of 3D-printing technology. Our results show that 3D-printing technology could reduce the duration of surgery and total bleeding volume and increase the number of lymph node dissections. 3D-printing technology may be more helpful for novice surgeons.Trial registration: Chinese Clinical Trial Registry, ChiCTR1800017161. Registered on 15 July 2018.

Expansion microscopy (ExM) allows super-resolution imaging on conventional fluorescence microscopes, but has been limited to proteins and nucleic acids. Here we develop click-ExM, which integrates click-labeling into ExM to enable a “one-stop-shop” method for nanoscale imaging of various types of biomolecules. Using 18 clickable labels for click-ExM imaging of DNA, RNA, proteins, lipids, glycans and small molecules, we demonstrate its universality, compatibility with signal-amplification techniques, and broad applications in cellular imaging.

The unexpected, non-enzymatic S-glycosylation of cysteine residues in various proteins by per-O-acetylated monosaccharides is described. This artificial S-glycosylation greatly compromises the specificity and validity of metabolic glycan labeling in living cells by per-O-acetylated azido and alkynyl sugars, which has been overlooked in the field for decades. It is demonstrated that the use of unacetylated unnatural sugars can avoid the artifact formation and a corrected list of O-GlcNAcylated proteins and O-GlcNAc sites in HeLa cells has been assembled by using N-azidoacetylgalactosamine (GalNAz).

Expansion microscopy (ExM) allows super-resolution imaging on conventional fluorescence microscopes, but has been limited to proteins and nucleic acids. Here we develop click-ExM, which integrates click labeling into ExM to enable a 'one-stop-shop' method for nanoscale imaging of various types of biomolecule. By click labeling with biotin and staining with fluorescently labeled streptavidin, a large range of biomolecules can be imaged by the standard ExM procedure normally used for proteins. Using 18 clickable labels, we demonstrate click-ExM on lipids, glycans, proteins, DNA, RNA and small molecules. We demonstrate that click-ExM is applicable in cell culture systems and for tissue imaging. We further show that click-ExM is compatible with signal-amplification techniques and two-color imaging. Click-ExM thus provides a convenient and versatile method for super-resolution imaging, which may be routinely used for cell and tissue samples.

OBJECTIVE Complex vascular anatomy has always been a difficult point for medical students. Gastrocolic trunk (Henle trunk) has many branches and variations, involving the venous reflux of the stomach, right colon, and pancreas. This study investigated the effects of 3 dimensional (3D) printing technology on medical interns’ understanding of Henle trunk's variation, by comparing 2 dimensional (2D) images. SETTING Henle trunk modes were manufactured using 3D-CT angiography and 3D-printing technology. PARTICIPANTS Forty-seven interns from 2 medical schools (Nanjing Medical University and Medical College of Nantong University) participated in the study. DESIGN The interns were divided randomly allocated into 2 groups, where group 1 was the control group with a 2D image of Henle trunk plus surgical video (named 2D image group), and group 2 was the study group with a 3D printed model of Henle trunk plus surgical video (named 3D-printing group). Knowledge of interns on the Henle trunk was compared between 2 groups using a question test before and after the teaching intervention. RESULTS All interns had an improved overall assessment score as a result of attending the seminar, whether in the 2D image group or the 3D-printing group. The score of the 2D image group increased 32.57 ± 13.86, and the 3D-printing group increased 47.04 ± 12.99, showing significant difference (p = 0.001). There was no significant difference observed between postseminar scores between 2 medical schools (p = 0.975). There was a significant improvement in satisfaction among the 3D-printing group for education depth, novel and inspiring of teaching method, except for the interaction between teacher and interns (p = 0.215). Interns hope to have more teaching time for 3D printing, and not satisfied with the time of 3D printing teaching compared with those in the 2D image group (p = 0.021). CONCLUSIONS The 3-D printed Henle trunk model is a very effective teaching tool, which can help interns understand the anatomy of Henle trunk. The application of 3D printing technology in the teaching of interns of complex vascular anatomy is worth popularizing in teaching hospitals.

Background Cotton is one of the most economically important crops in the world, and it is exposed to various abiotic stresses during its lifecycle, especially salt stress. However, the molecular mechanisms underlying cotton tolerance to salt stress are still not fully understood due to the complex nature of salt response. Therefore, identification of salt stress-tolerance-related functional genes will help us to understand key components involved in stress response and to provide valuable genes for salt stress tolerance improvement via genetic engineering in cotton. In a previous study, expression of a Group III WRKY gene family member from the diploid cotton species Gossypium aridum, GarWRKY5, was significantly induced in response to salt stress. Results In this present study, virus-induced gene silencing of GarWRKY5 in cotton showed enhanced salt sensitivity compared to wild-type plants under salt stress. Overexpression of GarWRKY5 in Arabidopsis positively regulated salt tolerance at the stages of seed germination and vegetative growth. Additionally, GarWRKY5-overexpressing plants exhibited higher activities of superoxide dismutase (SOD) and peroxidase (POD) under salt stress. The transcriptome sequencing analysis of transgenic Arabidopsis plants and wild-type plants revealed that there was enriched co-expression of genes involved in reactive oxygen species (ROS) scavenging (including glutamine S-transferases (GSTs) and SODs) and altered response to jasmonic acid and salicylic acid in the GarWRKY5-OE lines. Conclusion GarWRKY5 is involved in salt stress response by the jasmonic acid- or salicylic acid-mediated signaling pathway based on overexpression of GarWRKY5 in Arabidopsis and virus-induced gene silencing of GarWRKY5 in cotton.

Intercellular communication via gap junctions is crucial for orchestrating behaviors of multicellular systems. Imaging methods and electrophysiological techniques have been widely used to identify gap junctions and map the gap-junction-connected cell networks. However, analyzing gene expression within a gap-junction network remains challenging. Herein, we report the development of bio-orthogonal recording of translation in adjacent cells connected by gap junctions (BORTAC-GJ), a gap-junction-dependent protein tagging method based on local activation of clickable amino acid analogues that pass through gap junctions and are metabolically incorporated into nascent proteins. We demonstrated that BORTAC-GJ enabled selective labeling of nascent proteomes, thus recording translation, in cell networks connected by gap junctions, leaving unconnected cells not labeled. We further applied BORTAC-GJ to probe bystander STING activation triggered by gap-junction-mediated cGAMP transfer, an important process in innate immune response. BORTAC-GJ provides a means to investigate the gap-junction network at the proteome level and is broadly applicable for various cell types connected by gap junctions.

Travel time estimation plays a core role in intelligent traffic systems, as people or smart vehicles can choose a better travel route in advance, while local authorities can make urban traffic planning based on it. The paper proposes a dual traffic network topology coupled with improved delay models to estimate travel time in urban traffic system. The structure of the system is demonstrated by the dual traffic network (DTN) topology. It hires nodes to representjoint points of links and intersections; it also has two kinds of edges-links and turning cases of intersections. The BPR model is improved by concerning the influence of pedestrians and the lane width, and the HCM model is improved by adding travel time at intersections and considering three different turning cases to match with the DTN topology. The proposed methodology is evaluated by a comparison and an experiment in Changzhou, China. The error is greatly reduced, even though the degree of saturation exceeds 0.72. This proposed estimation methodology can improve the estimation accuracy significantly, especially in high degree of saturation cases.

Light-responsive proteins have been delivered into the cells for controlling intracellular events with high spatial and temporal resolution. However, the choice of wavelength is limited to the UV and visible range; activation of proteins inside the cells using near-infrared (NIR) light, which has better tissue penetration and biocompatibility, remains elusive. Here, we report the development of a single-walled carbon nanotube (SWCNT)-based bifunctional system that enables protein intracellular delivery, followed by NIR activation of the delivered proteins inside the cells. Proteins of interest are conjugated onto SWCNTs via a streptavidin-desthiobiotin (SA-DTB) linkage, where the protein activity is blocked. SWCNTs serve as both a nanocarrier for carrying proteins into the cells and subsequently a NIR sensitizer to photothermally cleave the linkage and release the proteins. The released proteins become active and exert their functions inside the cells. We demonstrated this strategy by intracellular delivery and NIR-triggered nuclear translocation of enhanced green fluorescent protein, and by intracellular delivery and NIR-activation of a therapeutic protein, saporin, in living cells. Furthermore, we showed that proteins conjugated onto SWCNTs via the SA-DTB linkage could be delivered to the tumors, and optically released and activated by using NIR light in living mice.

Metabolic labeling of glycans with sugar chemical reporters (i.e., unnatural sugars bearing a bioorthogonal group), followed by bioorthogonal reaction with imaging probes or affinity tags, has enabled visualization and proteomic analysis of glycosylation in live cells and in living animals. This two-step metabolic glycan labeling strategy has emerged as a powerful tool for probing glycosylation, but suffers from a lack of cell-type selectivity. Here we describe liposome-assisted bioorthogonal reporter (LABOR), a liposome-assisted format of metabolic glycan labeling that allows for cell-selective and tissue-specific glycan imaging and glycoproteomic profiling. After a brief introduction of the principles and applications of LABOR, we provide detailed protocols for performing LABOR in cell culture and in living mice.

Metabolic labeling of glycans with sugar chemical reporters (i.e., unnatural sugars bearing a bioorthogonal group), followed by bioorthogonal reaction with imaging probes or affinity tags, has enabled visualization and proteomic analysis of glycosylation in live cells and in living animals. This two-step metabolic glycan labeling strategy has emerged as a powerful tool for probing glycosylation, but suffers from a lack of cell-type selectivity. Here we describe liposome-assisted bioorthogonal reporter (LABOR), a liposome-assisted format of metabolic glycan labeling that allows for cell-selective and tissue-specific glycan imaging and glycoproteomic profiling. After a brief introduction of the principles and applications of LABOR, we provide detailed protocols for performing LABOR in cell culture and in living mice.

In mammalian cells, more than 1,000 intracellular proteins are posttranslationally modified with O-linked GlcNAc (O-GlcNAc), which regulates many important biological processes. The O-GlcNAc modification has been found to dynamically cycle on and off the modified proteins. How O-GlcNAc affects protein stability remains to be investigated at the proteome level. In this work, we developed a quantitative time-resolved proteomic strategy to analyze the turnover dynamics of O-GlcNAcylated proteins. We discovered that not all protein O-GlcNAcylation events were reversible and that a subset of O-GlcNAcylated proteins exhibited minimal removal of O-GlcNAc or degradation of protein backbones. Our work reveals stable O-GlcNAc as an important regulatory mechanism for stabilizing proteins, such as core proteins of box C/D small nucleolar ribonucleoprotein complexes.