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With the rapid development of industry, agriculture, and urbanization, various organic pollutants have accumulated in natural water, posing a potential threat to both the ecological environment and human beings, and removing organic pollutants from water is an urgent priority. Piezocatalytic techniques, with the advantages of green, simple operation, and high efficiency, are highly sought after in the degradation of environmental organic pollutants. Moreover, combining piezocatalytic techniques with advanced oxidation processes (AOPs), photocatalysis, or electrocatalysis can further effectively promote the efficient degradation of target pollutants. Therefore, a perspective is presented on the recent progress of piezocatalytic techniques for the degradation of various organic pollutants from aqueous solutions. The classification of various piezoelectric materials, as well as modification strategies for improving piezocatalysis, are first systematically summarized. Furthermore, the latest research on piezocatalysis and its combination with other technologies, such as AOPs, photocatalysis, and electrocatalysis, in the degradation of environmental pollutants is discussed. The potential mechanisms of piezocatalysis are also analyzed in depth. Finally, the urgent challenges and future opportunities for piezocatalytic techniques in the degradation of organic pollutants are provided.

Hepatocellular carcinoma (HCC) is one of the primary forms of liver cancer and is currently the sixth most prevalent malignancy worldwide. In addition to surgical interventions, effective drug treatment is essential for treating HCC. With an increasing number of therapeutic drugs for liver cancer undergoing clinical studies, the therapeutic strategies for advanced HCC are more diverse than ever, leading to improved prospects for HCC patients. Molecular targeted drugs and immunotherapies have become crucial treatment options for HCC. Treatment programs include single-agent molecular-targeted drugs, immunotherapies, combinations of immunotherapies with molecular-targeted drugs, and dual immune checkpoint inhibitors. However, further exploration is necessary to determine the optimal pharmacological treatment regimens, and the development of new effective drugs is urgently needed. This review provides an overview of the current globally approved drugs for liver cancer, as well as the latest advances in ongoing clinical research and drug therapies. Additionally, the review offers an outlook and discussion on the prospects for the development of drug therapy approaches for HCC.

With the intensification of global population aging, attention to the emotional health of the elderly continues to grow. Traditional interior architectural design primarily focuses on optimizing physical functionality; however, this approach is no longer sufficient to meet the increasingly complex emotional needs of the elderly. Integrating the Three-Level Theory of Emotional Design (TTED) into interior design provides a significant opportunity to systematically address the multidimensional needs of the elderly. However, existing research is often fragmented and lacks thematic literature reviews to summarize the key factors, characteristics, and design strategy frameworks of interior design. This study aims to evaluate the impact of interior design on the emotional experiences of the elderly and to construct a conceptual framework to address current research gaps. By establishing rigorous selection criteria, 39 high-quality studies were identified from the Scopus, Web of Science, and Mendeley databases. Using ATLAS.ti 9 for thematic analysis, five core themes were distilled: aesthetics, use and function, emotional reflection, design strategies, and emotional experience. The findings revealed that architectural interior design practices often paid limited attention to the emotional needs of older adults. Through a comprehensive literature review, 10 key design features were identified, including multi-sensory attributes, morphological characteristics, cultural elements, and natural components, alongside 17 related research directions. The study introduces a dynamic feedback mechanism within the framework of the proposed architectural interior design strategy, highlighting the importance of employing multiple strategies that balance and complement each other in practical applications. Additionally, the study clarifies future research directions, offering theoretical support and practical guidance for designers to address the complex needs of the elderly. This achievement provides a systematic reference for the future development of interior architectural design and has significant implications for improving the emotional experience of the elderly.

Arsenic exposure can induce liver insulin resistance (IR) and diabetes (DM), but the underlying mechanisms are not yet clear. Circular RNAs (circRNAs) are involved in the regulation of the onset of diabetes, especially in the progression of IR. This study aimed to investigate the role of circRNAs in arsenic-induced hepatic IR and its underlying mechanism. Male C57BL/6J mice were given drinking water containing sodium arsenite (0, 0.5, 5, or 50 ppm) for 12 months. The results show that sodium arsenite increased circ_0000284 expression, decreased insulin-like growth factor 2 mRNA binding protein 2 (IGF2BP2) and peroxisome proliferator-activated receptor-γ (PPAR-γ), and inhibited cell membrane protein levels of insulin-responsive glucose transporter protein 4 (GLUT4) in the mouse livers, indicating that arsenic exposure causes liver damage and disruptions to glucose metabolism. Furthermore, sodium arsenite reduced glucose consumption and glycogen levels, increased the expression of circ_0000284, reduced the protein levels of IGF2BP2 and PPAR-γ, and inhibited GLUT4 protein levels in the cell membranes of insulin-treated HepG2 cells. However, a circ_0000284 inhibitor reversed arsenic exposure-induced reductions in IGF2BP2, PPAR-γ, and GLUT4 levels in the plasma membrane. These results indicate that circ_0000284 is involved in arsenite-induced hepatic insulin resistance through blocking the plasma membrane translocation of GLUT4 in hepatocytes via IGF2BP2/PPAR-γ. This study provides a scientific basis for finding early biomarkers for the control of arsenic exposure and type 2 diabetes mellitus (T2DM), and discovering new prevention and control measures.

Manganese (Mn) overexposure has been associated with the development of neurological damage reminiscent of Parkinson's disease, while the underlying mechanisms have yet to be fully characterized. This study aimed to investigate the mechanisms leading to injury in dopaminergic neurons induced by Mn and identify novel treatment approaches. In the in vivo and in vitro models, ICR mice and dopaminergic neuron-like PC12 cells were exposed to Mn, respectively. We treated them with anti-ferroptotic agents ferrostatin-1 (Fer-1), deferoxamine (DFO), HIF-1α activator dimethyloxalylglycine (DMOG) and inhibitor LW6. We also used p53-siRNA to verify the mechanism underlying Mn-induced neurotoxicity. Fe and Mn concentrations increased in ICR mice brains overexposed to Mn. Additionally, Mn-exposed mice exhibited movement impairment and encephalic pathological changes, with decreased HIF-1α, SLC7A11, and GPX4 proteins and increased p53 protein levels. Fer-1 exhibited protective effects against Mn-induced both behavioral and biochemical changes. Consistently, in vitro, Mn exposure caused ferroptosis-related changes and decreased HIF-1α levels, all ameliorated by Fer-1. Upregulation of HIF-1α by DMOG alleviated the Mn-associated ferroptosis, while LW6 exacerbated Mn-induced neurotoxicity through downregulating HIF-1α. p53 knock-down also rescued Mn-induced ferroptosis without altering HIF-1α protein expression. Mn overexposure resulted in ferroptosis in dopaminergic neurons, mediated through the HIF-1α/p53/SLC7A11 pathway.

Abstract Papillary thyroid carcinoma (PTC) is the most common endocrine malignancy with a rapidly increasing incidence. The pathogenesis of PTC is unclear, but metabolic and lipidomic reprogramming may play a role in tumor growth. We applied ultra-performance liquid chromatography-tandem mass spectrometry to perform widely targeted metabolomics and lipidomics on plasma samples from 94 patients with PTC and 100 healthy controls. We identified 113 differential metabolites and 236 differential lipids, mainly involved in branched-chain amino acid metabolism, glutamate and glutamine metabolism, tricarboxylic acid cycle, and lipid metabolism. We also screened three potential metabolite biomarkers: sebacic acid, L-glutamine, and indole-3-carboxaldehyde. These biomarkers showed excellent diagnostic performance for PTC in both discovery and validation cohorts, with areas under the receiver operating characteristic curves of 0.994 and 0.925, respectively. Our findings reveal distinct metabolic and lipidomic features of PTC and provide novel targets for diagnosis and treatment.

BackgroundOccupational and environmental particulate matter may cause fibrosis, accompanied by RNA m6A modification changes. Neodymium oxide (Nd2O3) can cause mouse lung fibrosis, which contains a large number of fibroblasts. ObjectiveTo investigate m6A modification of tumor necrosis factor receptor-associated protein 6/nuclear factor-κB (TRAF6/NF-κB) signaling pathway in fibrosis of human embryonic lung fibroblasts induced by Nd2O3, and identify the key m6A modification sites of TRAF6. MethodsDesigned concentrations of Nd2O3 (0, 1.563, 3.125, 6.25, 12.5, 25, 50, 100, and 200 mg∙L−1) were infected with HELF cells for 24 and 48 h, and cell viability was detected to determine exposure time and dose. Measurements included indicators of fibrosis [hydroxyproline (HYP) and transforming growth factor-β1 (TGF-β1)], m6A methylation level, methyltransferases (METTL3 and METTL14), demethylases (FTO and ALKBH5), reading proteins (YTHDC2 and YTHDF2), fibrosis-associated genes (collagen-І, vimentin, and α-SMA), and proteins related to signaling pathway (TRAF6, NFKB1, P65, and P-P65). The enrichment of m6A in TRAF6 mRNA was measured by methylated RNA immunoprecipitation-quantitative real-time PCR (MeRIP-qPCR). ResultsThe results of cell viability indicated that 6.25, 12.5, 25 mg∙L−1 Nd2O3 and 48 h exposure time were used for subsequent experiments. After 48 h exposure, compared with the control group, the HYP level in the 25 mg∙L−1 Nd2O3 group was increased, and the levels of TGF-β1 in the 6.25, 12.5, and 25 mg∙L−1 Nd2O3 groups were increased (P

To date, significant efforts have been devoted to eliminating hazardous components to purify wastewater through the development of various nanomaterials. Covalent organic frameworks (COFs), an important branch of the porous crystalline family, possess the peculiarity of ultrahigh surface area, adjustable pore size, and facile functionality. Exciting studies from design fabrication to potential applications in water treatment by COF-based membranes (COMs) have emerged. This review summarizes various preparation strategies and synthesis mechanisms for COMs, including layer-by-layer stacking, in situ growth, interfacial polymerization, and electrochemical synthesis, and briefly describes the advanced characterization techniques for COMs. Moreover, the application of COMs in heavy metal removal, dye separation, purification of radionuclides, pollutant detection, sea water desalination, and so on, is described and discussed. Finally, the perspectives on future opportunities for designing COMs in water purification have been proposed.

Abstract Biochar and biochar-based materials have been studied extensively in multidisciplinary areas because of their outstanding physicochemical properties. In this review article, biochar and biochar-based materials in the removal of environmental pollutants, hydrogen generation and carbon dioxide capture were summarized and compared. The interaction mechanisms were discussed from the experimental results and characterization analysis. The high porous structures, active surface sites, (co)doping of single metals/nonmetals, and incorporation of metal oxides or other materials improved the high activity of biochar-based materials in their applications. However, there are still some challenges such as: (1) the fact that H2 generation with high selectivity or the produced syngas to meet the real application requirement in industrial is the main challenge in H2 production; (2) the fact that the selective capture of CO2 with high stability, high adsorption capacity and recyclability at low-cost should be considered and focused on; (3) the sorption-(photo)degradation of the organic chemicals; and (4) the fact that the sorption-reduction-extraction/solidification of metals/radionuclides are efficient methods for the elimination of environmental pollutants. In the end, the perspectives, challenges and possible techniques for biochar-based materials’ real application in future were described. Graphical Abstract

As a reversible and dynamic epigenetic marker, N6-adenylate methylation (m6A) modification is the most common mRNA modification in eukaryotes. This paper briefly described how m6A can influence RNA splicing, stability, and translation after transcription, and then participate in a variety of signaling pathways and biological and pathological processes, regulating cell proliferation, apoptosis, epithelial mesenchymal transformation (EMT) processes, and tumor invasion and metastasis. In addition, according to current studies, m6A methyltransferases (writers) are believed to promote EMT and tumor development, and readers and erasers both promote and inhibit EMT in different research objects. In this review, we summarized the mechanism of m6A modification and its role in cell transformation, and pointed out the direction of disease treatment.

Plot text is very valuable supporting information in movie recommendations. It has several characteristics: 1) It is rich in content. Each movie often has a document of more than 200 words to describe it, which can give the movie a rich semantic meaning. 2) Objectivity. Plot texts are different from review information. A movie may have thousands of reviews with mixed and conflicting opinions. However, a film has only one plot text, which is fair in tone and does not take a position. Despite its appealing properties and potential for accurate movie portrayal, the lack of a building block for effectively mining plot semantics has led to the marginalization of plot text in the design of movie recommendation algorithms. Therefore, in this paper, we explore the application of the Transformer, currently the best natural language processing module, to learning movie plot texts to help achieve more accurate rating prediction. We propose the "Plot-Aware Transformer" model (PAT) to model the process of "user-movie" rating interaction. We test the PAT model on several movie datasets and demonstrated that the model is competitive. In all tasks, PAT achieves state-of-the-art performance compared to baseline experiments.

In this paper, we use a graph capsule network to capture the spatial dependence of air quality data and meteorological data among cities, then use an LSTM network to model the temporal dependence of air pollution levels in specific cities and finally implement PM2.5 concentration prediction. We propose a graph-capsule-LSTM model based on a graph-capsule network and an LSTM network. The model uses a graph capsule network to model the neighboring feature information of the target city and then combines the local data of the target city to form the final feature vector. The feature mapping on the time axis is then used to obtain the temporal feature sequences of the target nodes, which are fed into the LSTM network for learning and prediction. Experiments show that the method achieves better results than the latest baseline model in the PM2.5 prediction task. While demonstrating that the capsule network outperforms the convolutional network, it also shows that this capsule network is very competent for the task of PM2.5 prediction.

Collaborative filtering is one of the most widely used methods in recommender systems. In recent years, Graph Neural Networks (GNN) were naturally applied to collaborative filtering methods to model users' preference representation. However, empirical research has ignored the effects of different items on user representation, which prevented them from capturing fine-grained users' preferences. Besides, due to the problem of data sparsity in collaborative filtering, most GNN-based models conduct a large number of graph convolution operations in the user-item graph, resulting in an over-smoothing effect. To tackle these problems, Adaptive Preference Retention Graph Convolutional Collaborative Filtering Method (APR-GCCF) was proposed to distinguish the difference among the items and capture the fine-grained users' preferences. Specifically, the graph convolutional method was applied to model the high-order relationship on the user-item graph and an adaptive preference retention mechanism was used to capture the difference between items adaptively. To obtain a unified users' preferences representation and alleviate the over-smoothing effect, we employed a residual preference prediction mechanism to concatenate the representation of users' preferences generated by each layer of the graph neural network. Extensive experiments were conducted based on three real datasets and the experimental results demonstrate the effectiveness of the model.

Three-phase single-switch power factor correction (PFC) circuit has the advantages of simple structure and convenient control, and its current source characteristics is conducive to achieve higher power by parallel interleaving. But theoretical analysis of the circuit was complex and the design theory was not established yet. To solve these problems, a parameters design method based on volt-second balance of the input inductance is proposed. By this method, the key component parameters of a 7.6 kW experimental prototype are designed. At the same time, A constant on-time control method of this circuit based on MATLAB simulation is designed, which can be applied to various converters with constant on-time control. The parameters and control design method of the single-switch PFC circuit are simulated based on the MATLAB. A prototype is built and tested also, the test results verify the correctness of the parameter design theory and constant on-time control simulation method.

Rice bean is an underexploited legume crop that has many desirable properties against bio and abiotic stresses. Here, the authors report the genome assembly of this species, conduct population genetics studies and reveal the genetic variations associated with adaptation and yield traits.

Background Coronavirus disease 2019 (COVID-19) vaccination is expected to end the pandemic; a high coverage rate is required to meet this end. This study aimed to investigate the prevalence of behavioral intention of free/self-paid COVID-19 vaccination and its associations with prosociality and social responsibility among university students in China. Methods An anonymous online cross-sectional survey was conducted among 6922 university students in five provinces in China during November 1-28, 2020. With informed consent, participants filled out an online survey link distributed to them via WeChat study groups. The response rate was 72.3%.Results The prevalence of behavioral intentions of free COVID-19 vaccination was 78.1%, but it dropped to 57.7% if the COVID-19 vaccination involved self-payment (400 RMB; around 42 USD). After adjusting for background factors, prosociality (free vaccination: adjusted odds ratio [ORa] = 1.10, 95% CI: 1.09-1.12; self-paid vaccination: ORa = 1.08, 95% CI: 1.07-1.09) and social responsibility (free vaccination: ORa = 1.17, 95% CI: 1.14-1.19; self-paid vaccination: ORa = 1.13, 95% CI: 1.11-1.14) were positively associated with the two variables of COVID-19 vaccination intention.Conclusion The present study demonstrated the positive effects of prosociality and social responsibility on the intention of COVID-19 vaccination. Accordingly, modification of prosociality and social responsibility can potentially improve COVID-19 vaccination. Future longitudinal and intervention studies are warranted to confirm such associations across populations and countries.

Highlights 1. Adsorption-photocatalytic degradation of organic pollutants by biochar-based catalysts is summarized. 2. Adsorption-(photo)catalytic reduction-solidification of heavy metal ions is discussed. 3. Mechanism and active free radicals on the degradation/reduction of contaminants are compared and described. 4. The methods to improve the photocatalysis performance of biochar-based catalysts are introduced. 5. The challenges for the real application of biochar-based materials are provided.

The COVID-19 pandemic has accelerated innovations for supporting learning and teaching online. However, online learning also means a reduction of opportunities in direct communication between teachers and students. Given the inevitable diversity in learning progress and achievements for individual online learners, it is difficult for teachers to give personalized guidance to a large number of students. The personalized guidance may cover many aspects, including recommending tailored exercises to a specific student according to the student′s knowledge gaps on a subject. In this paper, we propose a personalized exercise recommendation method named causal deep learning (CDL) based on the combination of causal inference and deep learning. Deep learning is used to train and generate initial feature representations for the students and the exercises, and intervention algorithms based on causal inference are then applied to further tune these feature representations. Afterwards, deep learning is again used to predict individual students′ score ratings on exercises, from which the Top-N ranked exercises are recommended to similar students who likely need enhancing of skills and understanding of the subject areas indicated by the chosen exercises. Experiments of CDL and four baseline methods on two real-world datasets demonstrate that CDL is superior to the existing methods in terms of capturing students′ knowledge gaps in learning and more accurately recommending appropriate exercises to individual students to help bridge their knowledge gaps.

BackgroundArsenic can be toxic to human by triggering oxidative stress, which is companied by epigenetic modifications.ObjectiveTo investigate the modification of N6-methyladenosine (m6A) in human embryonic lung fibroblasts (HELF) during oxidative stress induced by sodium arsenite (NaAsO2).MethodsHELF cells were treated by designed concentrations of NaAsO2 (0, 2.5, 5, 10, and 20 μmol·L−1) for 48 h. Cell viability was detected by 3-(4,5-dimethylthia zol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfopheny)-2H-tetrazolium (MTS) method; the activities of total superoxide dismutase (T-SOD) and glutathione peroxidase (GSH-Px) as well as the content of malondialdehyde (MDA) were detected with corresponding kits; the level of m6A methylation in total RNA was detected by enzyme-linked immunosorbent assay; the mRNA expressions of m6A modified enzymes were detected by real-time fluorescence quantitative PCR, including methyltransferase-like 3 (METTL3), methyltransferase-like 14 (METTL14), Wilms' tumor 1-associated protein (WTAP), fat mass and obesity-associated protein (FTO), alkB family of Fe(II)/α-ketoglutarate-dependent dioxygenases 5 (ALKBH5), YTH domain containing protein 2 (YTHDC2), YTH domain family protein 2 (YTHDF2), and YTH domain family protein 3 (YTHDF3); the protein expressions of METTL3, FTO, YTHDC2, YTHDF3, and nuclear factor erythroid 2-related factor 2 (NRF2) were detected by Western blotting. The enrichment of m6A in NRF2 mRNA was detected by RNA methylated immunoprecipitation combined with real-time fluorescence quantitative PCR (MeRIP-qPCR).ResultsAfter the 0, 2.5, 5, 10, and 20 μmol·L−1 NaAsO2 treatment, the MTS results showed that compared with the control group, the cell viability of the 20 μmol·L−1 group decreased to 84% (P

Elevated levels of arsenic may be present in groundwater, and long-term exposure to arsenic increases hepatic fibrosis. T helper 2 (Th2) cells are involved in the fibrotic cascade, and cell metabolism is a regulatory factor participating in CD4+ T cell differentiation and function. However, the mechanism for Th2 cell regulation of arsenite-induced hepatic fibrosis is not fully understood. In present study, for arsenite-fed mice, activated hepatic stellate cells may be involved in the infiltration of CD4+ T cells, accompanied by up-regulation of GATA3, a transcription factor, and IL-13, the major Th2 cytokine. Exposed to arsenite, Jurkat cells had increased aerobic glycolysis to promote the cell cycle and cell proliferation. Further, this process elevated levels of marker molecules, including those of the Th2 paradigm characterized by GATA3, IL-4, and IL-13. LX-2 cells were activated when treated with culture medium from Jurkat cells exposed to arsenite. miR-21 may be a therapeutic target for arsenite-induced hepatic fibrosis. In vitro, miR-21 knock-down caused inhibition of the PTEN/PI3K/AKT pathway induced by arsenite. It also reversed the elevated glycolysis and the accelerated cell cycle and cell proliferation. Indeed, this alteration led to diminished expression of GATA3, IL-4, and IL-13 in T cells differentiated under Th2 conditions, which inhibits activation of LX-2 cells. Consistent with the results in vitro, miR-21 knock-out in mice reversed hepatic fibrosis and attenuated the levels of GATA3 and IL-13 induced by arsenite. These findings indicate that miR-21 regulates the glycolysis of CD4+ T cells through the PTEN/PI3K/AKT pathway to accelerate the cell cycle, thereby facilitating CD4+ T cell polarization toward Th2 and releasing the fibrogenic factor IL-13, which participates in arsenite-associated hepatic fibrosis. Inhibition of Th2 polarization of CD4+T cells or miR-21 could be a therapeutic strategy to combat hepatic fibrosis caused by exposure to arsenic.

The occupational and environmental health safety of rare earths has attracted considerable attention. In China, the rare earth neodymium oxide (Nd2O3) is extensively refined and utilized. However, the mechanisms of Nd2O3-induced lung injury are elusive. In the present study, we found that exposure of mice to Nd2O3 caused an inflammatory reaction and fibrosis in lung tissues, which was in relation to the Nd2O3-induced higher levels of the lncRNA H19 (H19), tumor necrosis factor receptor 1 (TNFRSF1A), p-p65, and p-IKKβ and lower levels of miR-29a-3p. Further, in mouse monocyte macrophage leukemia cells (RAW264.7), Nd2O3 induced an inflammatory reaction, increases of H19 and TNFRSF1A levels, decreases of miR-29a-3p levels, and activation of the nuclear factor (NF)-κB signaling pathway. Further, we established that miR-29a-3p regulates TNFRSF1A expression. Up-regulation of miR-29a-3p and down-regulation of H19 blocked the Nd2O3-induced secretion of TNF-α, MIP-1α, and IL-6; the increases of TNFRSF1A levels; and activation of the NF-κB signaling pathway in RAW264.7 cells. Further, in Nd2O3-treated RAW26.4 cells, H19 inhibited the expression of miR-29a-3p, which targets TNFRSF1A, and activated the NF-κB signaling pathway to enhance the expression of TNF-α, MIP-1α, and IL-6. Moreover, for mice, up-regulation of miR-29a-3p reversed lung tissue inflammation, pulmonary fibrosis, and activation of the NF-κB signaling pathway induced by Nd2O3. In sum, the present investigation shows that H19 via miR-29a-3p is involved in lung inflammation and pulmonary fibrosis induced by Nd2O3, which is a mechanism for the Nd2O3-induced lung inflammatory response and pulmonary fibrosis. This information is useful for development of a biomarker of Nd2O3-induced lung injury.

(1) Objective: Rare earth neodymium oxide (Nd2O3) is refined and used extensively around the world, and the occupational and environmental safety of rare piles of the earth has attracted considerable attention. Nd2O3 enters the human body through the respiratory system, reaches various organs through blood circulation, and accumulates to produce toxic effects. At present, little is known about the reproductive toxicity of Nd2O3. Non-coding RNAs participate in a variety of physiological activities and are very important for spermatogenesis. However, it is unknown whether they are involved in Nd2O3-induced reproductive toxicity. Therefore, we conducted a pathological analysis, sperm quality testing, and RNA-seq on the testicular tissue of mice exposed to Nd2O3 to find the key genes and regulatory pathways of male reproductive damage and explore the early biomarkers and mechanisms of reproductive damage caused by Nd2O3. (2) Methods: After exposure of mice to Nd2O3, we carried out a pathological analysis and RNA-seq analysis for miRNAs/lncRNAs/circRNAs/mRNAs on the testicular tissue of mice, and the total RNAs were used to investigate miRNA/lncRNA/circRNA/mRNA expression profiles by strand-specific RNA sequencing at the transcriptome level to help uncover RNA-related mechanisms in Nd2O3-induced toxicity. (3) Results: Nd2O3 damaged testis and sperm morphology, significantly decreased the number of sperm, and deformed the sperm head and tail. RNA-seq analysis showed that the expression level of mRNA/miRNA/circRNA/lncRNA in the testicular tissue of mice exposed to Nd2O3 is abnormal. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis demonstrated that the functional enrichment of differentially expressed genes (DEGs) and their target genes was closely related to the related pathway of spermatogenesis. Furthermore, some miRNAs/lncRNAs/circRNAs that were greatly upregulated or inducibly expressed, implying their potential value as candidate markers for Nd2O3-induced reproductive toxicity, help us to further investigate the mechanisms of key genes, key signaling pathways, and inter-gene regulation for Nd2O3-induced reproductive toxicity. (4) Conclusions: This study provides the first database of a Nd2O3-induced transcriptome. This information is useful for the development of biomarkers of Nd2O3-induced reproductive injury and promotes understanding of the reproductive toxicity mechanism of Nd2O3.

This paper investigates the routing, modulation, and spectrum assignment (RMSA) problem for advance reservation (AR) requests in semi-filterless optical networks (semi-FONs). A link resource-aware (LRA) algorithm consisting of three parts is proposed. First, in the request scheduling phase, a request sorting strategy based on the flexible window size of the starting time is proposed. This strategy schedules AR requests based on the size of a flexible window with respect to the starting time. Next, in the routing phase, a link resource-aware strategy is proposed. This strategy evenly distributes the requests across the network resources, thereby avoiding request blocking due to excessive resource occupation on a single or few links. In the spectrum assignment phase, a frequency–time block-based metric is employed to measure the availability of each frequency–time block for AR requests. This metric is a sum of two factors: the distance to the block and spectrum boundaries, and the time interval between the request start time and the earliest start time. Our simulation results demonstrate that the proposed LRA algorithm has a lower blocking probability compared to the benchmark algorithms.

Filterless optical networks (FONs) have become a cost-effective solution for optical network deployment due to their low-cost characteristics. However, eliminating active switching elements causes signals to propagate over unintended links, wasting spectral resources. Therefore, semi-filterless optical networks (Semi-FONs) have become a more cost-effective solution. This paper mainly studies the routing, modulation, and spectrum assignment (RMSA) problem in semi-filterless optical networks. It proposes a single–multi-path combination (LR-SMPC) RMSA algorithm with the least resource consumption. The algorithm first obtains the K shortest paths that satisfy the conditions according to the K short path (KSP) algorithm and re-orders the paths according to the resource consumption path re-ordering strategy, selecting the three paths that consume the least resources as the set of candidate paths. Then, based on the single–multi-path combination scheme of the set of candidate paths, the resource consumption of each scheme and the maximum number of available spectrum blocks for each path is calculated, from which the single path or multi-path with the least resource consumption is selected to serve the request. We perform simulation experiments on two network topologies using Poisson traffic models and compare them with existing single-path algorithms (S-P), fixed spectrum assignment granularity algorithms (g = 1), and adaptation spectrum assignment algorithms (g adaptation) to evaluate the performance of the proposed algorithm. The simulation results show that the proposed algorithm exhibits better performance in terms of both blocking rate and spectrum utilization.

Adzuki bean (Vigna angularis (Willd.) Ohwi & Ohashi) is an annual cultivated leguminous crop commonly grown in Asia and consumed worldwide. However, there has been limited research regarding adzuki bean genetics, which has prevented the efficient application of genes during breeding. In the present study, we constructed a high-density genetic map based on whole genome re-sequencing technology and validated its utility by mining QTLs related to seed size. Moreover, we analyzed the sequences flanking insertions/deletions (InDels) to develop a set of PCR-based markers useful for characterizing adzuki bean genetics. A total of 2904 markers were mapped to 11 linkage groups (LGs). The total length of the map was 1365.0 cM, with an average distance between markers of 0.47 cM. Among the LGs, the number of markers ranged from 208 (LG7) to 397 (LG1) and the total distance ranged from 97.4 cM (LG9) to 155.6 cM (LG1). Twelve QTLs related to seed size were identified using the constructed map. The two major QTLs in LG2 and LG9 explained 22.1 and 18.8% of the total phenotypic variation, respectively. Ten minor QTLs in LG4, LG5 and LG6 explained 3.0–10.4% of the total phenotypic variation. A total of 9718 primer pairs were designed based on the sequences flanking InDels. Among the 200 selected primer pairs, 75 revealed polymorphisms in 24 adzuki bean germplasms. The genetic map constructed in this study will be useful for screening genes related to other traits. Furthermore, the QTL analysis of seed size and the novel markers described herein may be relevant for future molecular investigations of adzuki bean and will be useful for exploiting the mechanisms underlying legume seed development.

Transition metal sulfides are favored as anode materials for the next generation of lithium-ion batteries because of their high theoretical capacities and abundant natural resources. However, serious volume changes during charging and discharging pose great challenges to their stability. In this work, petal-like MoS2/Co9S8/C nanohybrids were synthesized via the immobilization of molybdyl acetoacetonate MoO2(acac)2 in ZIF-67 and subsequent combined vulcanization and thermolysis process. Benefiting from the homogeneous bimetallic sulfide and highly conductive carbon layer, the as-obtained MoS2/Co9S8/C nanohybrids exhibited a high initial discharge capacity of 988.3 mAh g−1 at 200 mA g−1 and a capacity retention > 99.9% after 50 cycles. Even at a high current density of 1000 mA g−1, the reversible capacity of MoS2/Co9S8/C is still as high as 754.6 mAh g−1, revealing extraordinary rate ability. This work can provide a general approach to design and synthesize other advanced bimetallic chalcogenides for boosting lithium-ion batteries storage performance.

Mung bean (Vigna radiata L.) is an economically important grain legume cultivated in Asian countries. High-density genetic linkage is a valuable and effective tool for mapping quantitative trait loci (QTL). In the current study, a high-resolution genetic map containing 4,180 single-nucleotide polymorphisms (SNPs) was assigned to 11 linkage groups (LGs) and spanning 1,751.39 cM in length was constructed for mung bean, and the average distance between adjacent markers was 0.42 cM. Bruchids (Callosobruchus spp.) cause significant damage to and loss of legume seeds. A locus for bruchid resistance was detected. The gene Vradi05g03810, encoding a probable resistance-specific protein, was found to be the most likely key candidate gene in mung beans. A 69-bp sequence deletion was identified in the coding region by comparing the cDNA sequences of bruchid-resistant and bruchid-susceptible lines. This SNP-based high-density linkage map is one of the first to be constructed across the mung bean genome. This map will not only facilitate the genetic mapping of genes or complex loci that control important agronomic traits but also offer a tool for promoting future genetics and comparative genomic studies in Vigna.

Amantadine (AMD) is harmful to human health and has been forbidden as an antiviral drug in the livestock and poultry breeding. Thus, a rapid and sensitive detection method for AMD should be established. In this research, we have designed three kinds of haptens and then prepared three kinds of immunogens and coating antigens. A highly sensitive colloidal gold immunochromatographic assay (CG-ICA) for AMD detection by using heterologous coating antigen and mAb prepared with immunogen adding five carbons linker has been established. Under optimal conditions, the cut-off value of the CG-ICA was 2.5 ng/mL by naked eyes. The CG-ICA presented a good signal response to AMD in the concentration range of 0.1–2.5 ng/mL with low LOD at 0.077 ng/mL. These results indicated that the immunogen with carbon linker may obtain high-affinity antibody while the heterologous coating antigen may improve the sensitivity of ICA.

Abstract. Human coronavirus (HCoV) causes potentially fatal respiratory disease. Pregnancy is a physiological state that predisposes women to viral infection. In this review, we aim to present advances in the pathogenesis, clinical features, diagnosis, and treatment in HCoV in pregnancy. We retrieved information from the Pubmed database up to June 2020, using various search terms and relevant words, including coronaviruses, severe acute respiratory syndrome coronavirus, Middle East respiratory syndrome coronavirus, 2019 coronavirus disease, and pregnancy. Both basic and clinical studies were selected. We found no evidence that pregnant women are more susceptible to HCoV infection or that those with HCoV infection are more prone to developing severe pneumonia. There is also no confirmed evidence of vertical mother-to-child transmission of HcoV infection during maternal HCoV infection. Those diagnosed with infection should be promptly admitted to a negative-pressure isolation ward, preferably in a designated hospital with adequate facilities and multi-disciplinary expertise to manage critically ill obstetric patients. Antiviral treatment has been routinely used to treat pregnant women with HCoV infection. The timing and mode of delivery should be individualized, depending mainly on the clinical status of the patient, gestational age, and fetal condition. Early cord clamping and temporary separation of the newborn for at least 2 weeks is recommended. All medical staff caring for patients with HCoV infection should use personal protective equipment. This review highlights the advances in pathogenesis, maternal-fetal outcome, maternal-fetal transmission, diagnosis and treatment in HCoV including severe acute respiratory syndrome coronavirus, Middle East respiratory syndrome coronavirus, and coronavirus disease 2019 in pregnancy.

The stage of decompensation is termed end-stage liver cirrhosis. Patients with decompensated cirrhosis (DCC) often have a variety of comorbidities that contribute to exacerbation of the disease and its high mortality rate. By comparing differential gene expression, transcriptomic analysis is useful for exploring relevant functional changes during disease progression. The purpose of this study was to identify differentially expressed long noncoding RNAs (lncRNAs) and mRNAs in patients with decompensated cirrhosis and to further explore the functions as well as interactions between lncRNAs and mRNAs. Four patients with decompensated cirrhosis and four controls with liver cirrhosis were recruited in this study. RNA was isolated from peripheral blood mononuclear cells, and RNA-seq was used for transcriptome analysis. The functions of differentially expressed mRNAs were revealed by Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, and a regulatory network was also constructed. A total of 1046 differentially expressed mRNAs and 1175 lncRNAs were identified between the decompensated cirrhosis patients and cirrhosis controls. Functional enrichment analyses indicated enrichment of genes involved in pathways related to inflammation and cellular metabolic activities. In addition, the findings suggested that the phagosome/endosome/autophagy-lysosome pathway might play an important role in cirrhotic decompensation. In summary, this study identified differentially expressed mRNAs (DE-mRNAs) and DE-lncRNAs and predicted the biological processes and signaling pathways involved in cirrhotic decompensation, which might provide new ideas for further revealing the molecular mechanism of DCC pathogenesis.

Cowpea is an important leguminous crop in arid and semi-arid tropical regions. However, it is sensitive to the temperature and photoperiod. In this study, 41 new lines of cowpea were evaluated in sowing seasons of spring (SpS), summer (SuS), and autumn (AuS) at Wuming, Guangxi province, China. Nine agronomic and yield-related traits were investigated and analyzed. The results showed that the pod width (0.8 cm) was similar among sowing seasons. For all other traits, the values were lowest at SuS, except the number of branches per plant, which was lowest (2.5) at AuS. Strong correlations were detected for the growth period, plant height, pod length, pod width, and 100-seed weight (p < 0.01) across the sowing seasons. A principal component analysis revealed that the first three components could explain 72.47% of the total variations. On the basis of the possible yield, growth period, and growth habit, we identified nine new lines suitable for different sowing seasons in Guangxi. The results of this study suggest these new cowpea lines may be useful for increasing crop production and for breeding new varieties.

Microplastics is a type of widespread contaminant found in numerous aquatic ecosystems. Conventional methods of microplastic identification and quantitation require tedious sample pretreatment procedures and complex instrument, therefore, it is highly in demand to develop portable sensitive methods for rapid field application of detection. Herein, a sensitive detection method based on surface enhanced Raman spectroscopy (SERS) for trace microplastics in non-pretreated water samples was reported, which used a sponge supported Au nanoparticle (NPs) layer as the SERS substrate and locally concentrating microplastics. The sponge pores decorated with Au nanoparticles could effectively capture and concentrate microplastics in the pores from aquaes sample. Interestingly, the adjustable size of the sponge could allow the distance between the “hot spots” on the substrate surface to be controlled, hence controlling the SERS signal intensity. The Raman signal for microplastics in water was greatly enhanced on the proposed substrate, whereas no Raman signal enhancement was observed on the un-supported Au NPs. It has been demonstrated that trace microplastics could be readily detected when higher sample volume was used. Furthermore, the practical applicability of the developed method has been demonstrated by the successful detection of microplastics in snow water, seawater, river water, and rainwater. This sensitive platform provided a possible opportunity for in-field microplastic detection without pretreatment coupled with a portable Raman instrument.

BackgroundThe outbreak of COVID-19 in China occurred around the Chinese New Year (January 25, 2020), and infections decreased continuously afterward. General adoption of preventive measures during the Chinese New Year period was crucial in driving the decline. It is imperative to investigate preventive behaviors among Chinese university students, who could have spread COVID-19 when travelling home during the Chinese New Year break. ObjectiveIn this study, we investigated levels of COVID-19–related personal measures undertaken during the 7-day Chinese New Year holidays by university students in China, and associated COVID-19–related cognitive factors. MethodsA cross-sectional anonymous web-based survey was conducted during the period from February 1 to 10, 2020. Data from 23,863 students (from 26 universities, 16 cities, 13 provincial-level regions) about personal measures (frequent face-mask wearing, frequent handwashing, frequent home staying, and an indicator that combined the 3 behaviors) were analyzed (overall response rate 70%). Multilevel multiple logistic regression analysis was performed. ResultsOnly 28.0% of respondents (6684/23,863) had left home for >4 hours, and 49.3% (11,757/23,863) had never left home during the 7-day Chinese New Year period; 79.7% (19,026/23,863) always used face-masks in public areas. The frequency of handwashing with soap was relatively low (6424/23,863, 26.9% for >5 times/day); 72.4% (17,282/23,863) had frequently undertaken ≥2 of these 3 measures. COVID-19–related cognitive factors (perceptions on modes of transmission, permanent bodily damage, efficacy of personal or governmental preventive measures, nonavailability of vaccines and treatments) were significantly associated with preventive measures. Associations with frequent face-mask wearing were stronger than those with frequent home staying. ConclusionsUniversity students had strong behavioral responses during the very early phase of the COVID-19 outbreak. Levels of personal prevention, especially frequent home staying and face-mask wearing, were high. Health promotion may modify cognitive factors. Some structural factors (eg, social distancing policy) might explain why the frequency of home staying was higher than that of handwashing. Other populations might have behaved similarly; however, such data were not available to us.

Abstract Zombi pea (Vigna vexillata) is a legume crop that is resistant to several biotic and abiotic stresses. Callosobruchus maculatus and Callosobruchus chinensis are serious stored-insect pests of legume crops. We constructed a high-density linkage map and performed quantitative trait loci (QTLs) mapping for resistance to these insect species in zombi pea. An F2 population of 198 individuals from a cross between ‘TVNu 240’ (resistant) and ‘TVNu 1623’ (susceptible) varieties was used to construct a linkage map of 6,529 single nucleotide polymorphism markers generated from sequencing amplified fragments of specific loci. The map comprised 11 linkage groups, spanning 1,740.9 cM, with an average of 593.5 markers per linkage group and an average distance of 0.27 cM between markers. High levels of micro-synteny between V. vexillata and cowpea (Vigna unguiculata), mungbean (Vigna radiata), azuki bean (Vigna angularis) and common bean (Phaseolus vulgaris) were found. One major and three minor QTLs for C. chinensis resistance and one major and one minor QTLs for C. maculatus resistance were identified. The major QTLs for resistance to C. chinensis and C. maculatus appeared to be the same locus. The linkage map developed in this study will facilitate the identification of useful genes/QTLs in zombi pea.

Shear velocity is an important parameter in pre-stack seismic reservoir description. However, in the real study, the high cost of array acoustic logging leads to lacking a shear velocity curve. Thus, it is crucial to use conventional well-logging data to predict shear velocity. The shear velocity prediction methods mainly include empirical formulas and theoretical rock physics models. When using the empirical formula method, calibration should be performed to fit the local data, and its accuracy is low. When using rock physics modeling, many parameters about the pure mineral must be optimized simultaneously. We present a deep learning method to predict shear velocity from several conventional logging curves in tight sandstone of the Sichuan Basin. The XGBoost algorithm has been used to automatically select the feature curves as the model’s input after quality control and cleaning of the input data. Then, we construct a deep-feed neuro network model (DFNN) and decompose the whole model training process into detailed steps. During the training process, parallel training and testing methods were used to control the reliability of the trained model. It was found that the prediction accuracy is higher than the empirical formula and the rock physics modeling method by well validation.

Cytochrome P450 2E1 (CYP2E1) plays an essential role in the susceptibility to acute acrylonitrile (AN)-induced toxicity. Here, we investigated the toxicity and mechanism of AN in fasting mice and potential underlying mechanisms. Convulsions, loss of righting reflex, and death 4 h after AN treatment were observed and recorded for each group of mice. Relative to ad lib-fed mice, 48 h fasting significantly increased the acute toxicity of AN, as noted by a more rapid onset of convulsions and death. In addition, fasting significantly enhanced CYP2E1-mediated oxidative metabolism of AN, resulting in increased formation of CN- (one of the end-metabolites of AN). Moreover, fasting decreased hepatic GSH content, abrogating the detoxification of GSH. However, trans-1,2-dichloroethylene (DCE), a CYP2E1 inhibitor, altered the level of hepatic CYP2E1 activity in response to fasting, reduced the acute toxic symptoms of AN and the content of CN- in AN-treated mice. These data establish that fasting predisposes to AN toxicity, attributable to induced CYP2E1 and reduced hepatic GSH.

With the wide application of neodymium oxide nanoparticles (NPs-Nd2O3) in various fields, their health hazards have aroused public concern in recent years. However, data regarding the cytotoxicity of NPs-Nd2O3 is limited. In this study, we investigated the function and mechanism of long-chain non-coding RNAs (lncRNAs) in NPs-Nd2O3-induced airway inflammation. Treatment with NPs-Nd2O3 induced an inflammatory response in human bronchial epithelial cells (16HBE) by upregulating the expression of interleukin-6 (IL-6) and interleukin-8 (IL-8). The levels of LDH and intracellular ROS in the cells treated by various doses of NPs-Nd2O3 also increased significantly. After treatment with 10 μg/ml NPs-Nd2O3, RNA microarray and real-time quantitative polymerase chain reaction (qRT-PCR) showed a significant upregulation of lncRNA loc105377478. Functional experiments suggested lncRNA loc105377478 enhanced the expression of IL-6, IL-8 and ROS in NPs-Nd2O3-treated 16HBE cells, and it was further demonstrated that lncRNA loc105377478 promoted the activation of NF-κB by negatively regulating ADIPOR1 expression. Moreover, the expression of IL-6 and IL-8 in NPs-Nd2O3-treated 16HBE cells was regulated by lncRNA loc105377478, which was mediated by the NF-κB signaling pathway. In conclusion, lncRNA loc105377478 promotes NF-κB activation by negatively regulating ADIPOR1 expression, thereby upregulating the expression of IL-6 and IL-8 in 16HBE cells treated with NPs-Nd2O3.

Mung bean (Vigna radiata L.) is an important but understudied food legume in Asia and now worldwide. Genetic studies may help to accelerate the exploitation of new genes for breeding in this crop. Here, we used a recombination inbred line population to construct an SNP genetic linkage map by genome sequencing technology. We obtained 21,508 high-quality SNP markers integrated into 1,946 bin markers that were mapped onto 11 linkage groups (LGs) with 99–258 bin markers per LG. The total genetic length of the map was 1060.2 cM (38.76–168.03 cM per LG), with an average distance between markers of 0.54 cM. However, there were 18 gaps >5 cM, distribution on LG1, 3, 5, 7, and 9. Gene mapping for lobed and indented leaflets was conducted using the map. A major quantitative trait locus (QTL) associated with indented leaflets was detected on chromosome 10, with phenotypic variation explained (PVE) values of 39.7% and 45.4% under two different environments. Several QTLs for lobed leaflets were detected and most of them were tightly linked together on Chromosome 3. However, only one major QTL, which explained the largest phenotypic variation (27.7–69.5%), was stably detected under two different environments using both R and Q methods. In the two main stable QTLs regions on chromosomes 3 and 10, candidate genes for regulating the molecular mechanism of different leaflet shapes were detected by functional annotation. The overlap of major QTLs under different environments indicated that the present map would be good enough for precisely mapping genes, and both the QTL analysis and gene prediction were useful for investigating the mechanism of leaf development in mung bean or legumes.

For rapid and portable detection of ethylene in commercial fruit ripening storage rooms, we designed a smartphone-based optical fiber sensor (SOFS), which is composed of a 15 mW 365 nm laser for fluorescence signal excitation and a bifurcated fiber system for signal flow direction from probe to smartphone. Paired with a pyrene-tagged Grubbs catalyst (PYG) probe, our SOFS showed a wide linearity range up to 350 ppm with a detection limit of 0.6 ppm. The common gases in the warehouse had no significant interference with the results. The device is portable (18 cm × 8 cm × 6 cm) with an inbuilt power supply and replaceable optical fiber sensor tip. The images are processed with a dedicated smartphone application for RGB analysis and ethylene concentration. The device was applied in detection of ethylene generated from apples, avocados, and bananas. The linear correlation data showed agreement with data generated from a fluorometer. The SOFS provides a rapid, compact, cost-effective solution for determination of the fruit ethylene concentration dynamic during ripening for better fruit harvest timing and postharvest management to minimize wastage.

The goal of the recommender system is to learn the user’s preferences from the entity (user–item) historical interaction data, so as to predict the user’s ratings on new items or recommend new item sequences to users. There are two major challenges: (1) Datasets are usually sparse. The item side is often accompanied by some auxiliary information, such as attributes or context; it can help to slightly improve its representation. However, the user side is usually presented in the form of ID due to personal privacy. (2) Due to the influences of confounding factors, such as the popularity of items, users’ ratings on items often have bias that cannot be recognized by the traditional recommendation methods. In order to solve these two problems, in this paper, (1) we explore the use of a graph model to fuse the interactions between users and common rating items, that is, incorporating the “neighbor” information into the target user to enrich user representations; (2) the do() operator is used to deduce the causality after removing the influences of confounding factors, rather than the correlation of the data surface fitted by traditional machine learning. We propose the EGCI model, i.e., enhanced graph learning for recommendation via causal inference. The model embeds user relationships and item attributes into the latent semantic space to obtain high-quality user and item representations. In addition, the mixed bias implied in the rating process is calibrated by considering the popularity of items. Experimental results on three real-world datasets show that EGCI is significantly better than the baselines.

Adzuki beans are an important food legume crop in East Asia. A large number of adzuki bean accessions are maintained in the Chinese national seed genebank. A collection of 59 elite cultivars, 389 landraces, and 27 wild adzuki beans were selected and phenotyped extensively for yield and yield-related traits at two different locations (Nanning and Nanyang, China). Ten agronomic and yield-related traits were scored, and the data were subjected to analysis of variance (ANOVA), principal component analysis (PCA), correlation, and cluster analysis. Significant variation was observed for genotypes, locations, and genotype x environment interaction for most traits. Also, there were significant differences in the phenotypes among accessions of different germplasm types. The broad-sense heritability of traits studied ranged from 4.4% to 77.8%. The number of seeds per pod (77.8%), 100-seed weight (68.0%), and number of plant branches (63.9%) had a high heritability. A total of 10 traits were transformed into 3 comprehensive factors by principal component analysis, and the first three principal component factors contributed 72.31% of the total variability. Cluster analysis categorized the 475 adzuki bean accessions into five distinct groups. The results described in this study will be useful for adzuki bean breeders for the development of varieties with high end-use quality.

High yields, high stress resistance, and wide adaptability are important cultivar traits, especially for crops sensitive to the photoperiod and temperature. Mung bean (Vigna radiata) is a typical short-day plant, traditionally cultivated in Asian countries, and consumed all over the world. However, there has long been relatively little research regarding its genetic improvement until in recent decades. Zhonglv 5 is a mung bean cultivar that was developed via crossbreeding in China in the early part of this century. It has since played an important role in improving mung bean production in the country because of its high yields, high stress tolerance, and wide adaptability. We herein describe the development of Zhonglv 5, summarize its yield performance and adaptability in diverse eco-regions within China, and predict its potential future uses to provide information relevant for mung bean breeding, production, trade, and related industries.

Genetic resources from other countries or regions play an important role in broadening the genetic background of local breeding varieties. Here we describe observations on the adaptability of mung bean germplasm obtained from the United States Department of Agriculture and their genetic diversity assessment using SSR markers. Several accessions were shown to be mixtures, based on their phenotypes for some characters. Most accessions were able to complete their lifecycles when grown in Beijing, China, making them ideal for crossbreeding without day length control. High diversity was revealed by the SSR markers, with an average of 4.2 alleles per locus and a PIC value of 0.650 per locus. STRUCTURE analysis divided the accessions into six groups. There was no obvious trend of accessions forming groups according to their geographical origin, owing mainly to germplasm exchange and an uneven distribution of accessions. The present results indicate that this germplasm would enrich the local gene pool, and provide information for the further use of germplasm in breeding programs.

All current recommendation algorithms, when modeling user–item interactions, basically use dot product. This dot product calculation is derived from matrix factorization. We argue that an inherent drawback of matrix factorization is that latent semantic vectors of users or items sometimes do not satisfy triangular inequalities, which may affect the performance of the recommendation. Recently, metric factorization was proposed to replace matrix factorization and has achieved some improvements in terms of recommendation accuracy. However, similar to matrix factorization, metric factorization still uses a simple, linear fashion. In this paper, we explore leveraging nonlinear deep neural networks to realize Euclidean distance interaction between users and items. We propose a generic Neural Metric Factorization Framework (NMetricF), which learns representations for users and items by incorporating Euclidean metric factorization into deep neural networks. Extensive experiments on six real-world datasets show that, compared to the previous recommendation algorithms based purely on rating data, NMetricF achieves the best performance.

Vaccination is one of the most effective ways of controlling the COVID-19 pandemic. However, vaccine hesitancy is prevalent, and relatively few studies have explored how variables related to personal and external motives have affected the intention to vaccinate. The present study investigated the association between perceived personal benefits, variables reflecting external motives (i.e., perceived social benefits, collectivism, and national pride) and intention to receive COVID-19 vaccination among university students in China. The interaction between perceived personal benefits and the three factors reflecting external motives on intention to receive COVID-19 vaccination was also examined. A total of 6922 university students from five provinces of China completed a cross-sectional survey. Results showed that adjusting for significant background variables, perceived personal benefits, perceived social benefits, collectivism, and national pride were all significant factors of intention to receive COVID-19 vaccination. Results from interaction analyses also showed that the association between perceived personal benefits and COVID-19 vaccination intention was stronger among those with lower levels of national pride. Findings highlighted the important role of self-directed interest and external motives in promoting uptake of COVID-19 vaccination.

Sulfamethazine (SMZ) as a broad antibiotic is widely used in livestock and poultry. However, the abuse of SMZ in livestock feed can lead to SMZ residues in food and the resistance of bacteria to drugs. Thus, a method for the detection of SMZ in food is urgently needed. In this study, quantum dot (QD) nanobeads (QBs) were synthesized by encapsulating CdSe/ZnS QDs using a microemulsion technique. The prepared QBs as signal probes were applied in lateral flow immunoassay (LFIA) for the detection of SMZ in chicken and milk. Our proposed method had limits of detection of 0.1138–0.0955 ng/mL and corresponding linear ranges of 0.2–12.5, 0.1–15 ng/mL in chicken and milk samples, respectively. The recovery of LFIA for the detection of SMZ was 80.9–109.4% and 84–101.6% in chicken and milk samples, respectively. Overall, the developed QBs-LFIA had high reliability and excellent potential for rapid and sensitive screening of SMZ in food.

Cowpea (Vigna unguiculata) is an important legume crop with diverse uses. The species is presently a minor crop, and evaluation of its genetic diversity has been very limited. In this study, a total of 200 genic and 100 genomic simple sequence repeat (SSR) markers were developed from cowpea unigene and genome sequences, respectively. Among them, 27 genic and 27 genomic SSR markers were polymorphic and were used for assessment of genetic diversity and population structure in 105 selected cowpea accessions. A total of 155 alleles and 2.9 alleles per marker were identified, and the average polymorphic information content (PIC) value was 0.3615. The average PIC of genomic SSRs (0.3996) was higher than that of genic SSRs (0.3235), and most of the polymorphic genomic SSRs were composed of di- and trinucleotide repeats (51.9% and 37.0% of all loci, respectively). The low level of detected genetic diversity may be attributed to a severe genetic bottleneck that occurred during the cowpea domestication process. The accessions were classified by structure and cluster analysis into four subgroups that correlated well with their geographic origins or collection sites. The classification results were also consistent with the results from principal coordinate analysis and can be used as a guide during future germplasm collection and selection of accessions as breeding materials for cultivar improvement. The newly developed genic and genomic SSR markers described in this study will be valuable genomic resources for the assessment of genetic diversity, population structure, evaluation of germplasm accessions, construction of genetic maps, identification of genes of interest, and application of marker-assisted selection in cowpea breeding programs.

Abstract Background Cowpea [Vigna unguiculata (L.) Walp.] is one of the most important legumes in tropical and semi-arid regions. However, there is relatively little genomic information available for genetic research on and breeding of cowpea. The objectives of this study were to analyse the cowpea transcriptome and develop genic molecular markers for future genetic studies of this genus. Results Approximately 54 million high-quality cDNA sequence reads were obtained from cowpea based on Illumina paired-end sequencing technology and were de novo assembled to generate 47,899 unigenes with an N50 length of 1534 bp. Sequence similarity analysis revealed 36,289 unigenes (75.8%) with significant similarity to known proteins in the non-redundant (Nr) protein database, 23,471 unigenes (49.0%) with BLAST hits in the Swiss-Prot database, and 20,654 unigenes (43.1%) with high similarity in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Further analysis identified 5560 simple sequence repeats (SSRs) as potential genic molecular markers. Validating a random set of 500 SSR markers yielded 54 polymorphic markers among 32 cowpea accessions. Conclusions This transcriptomic analysis of cowpea provided a valuable set of genomic data for characterizing genes with important agronomic traits in Vigna unguiculata and a new set of genic SSR markers for further genetic studies and breeding in cowpea and related Vigna species.

Bruchid beetle (Callosobruchus chinensis) poses a serious threat to the production and storage of mung bean (Vigna radiata). Mapping bruchid resistance (Br) will provide an important basis for cloning the responsible gene(s) and elucidating its functional mechanism, and will also facilitate marker-assisted selection in mung bean breeding. Here, we report the construction of the genetic linkage groups of mung bean and mapping of the Br1 locus using an RIL population derived from a cross between Berken, a bruchid-susceptible line, and ACC41, a bruchid-resistant line. A total of 560 markers were mapped onto 11 linkage groups, with 38.0% of the markers showing distorted segregation. The lengths of the linkage groups ranged from 45.2 to 117.0 cM with a total coverage of 732.9 cM and an average interval of 1.3 cM between loci. Br1 was located on LG9 between BM202 (0.7 cM) and Vr2-627 (1.7 cM). Based on 270 shared SSR markers, most of the linkage groups were assigned to specific chromosomes. These results should further accelerate the genetic study of this crop.

COVID-19 has caused a devastating impact on public health and made the development of the COVID-19 vaccination a top priority. Herd immunity through vaccination requires a sufficient number of the population to be vaccinated. Research on factors that promote intention to receive the COVID-19 vaccination is warranted. Based on Diffusion of Innovations Theory, this study examines the association between the perceived efficacy of the COVID-19 vaccination, use of social media for COVID-19 vaccine-related information, openness to experience and descriptive norm with the intention to receive the COVID-19 vaccination, and the moderating role of openness to experience among 6922 university students in mainland China. The intention to receive the free and self-paid COVID-19 vaccination is 78.9% and 60.2%, respectively. Results from path analyses show that perceived efficacy of the COVID-19 vaccination, use of social media for COVID-19 vaccine-related information, and openness to experience and descriptive norm are all positively associated with the intention to receive COVID-19 free and self-paid vaccination. The association between the perceived efficacy of the COVID-19 vaccination and descriptive norm with the intention to receive the COVID-19 vaccination is stronger among those with a lower level of openness to experience. Our findings support the usefulness of Diffusion of Innovations Theory and the moderating role of openness of experience in explaining intention to receive the COVID-19 vaccination.