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Abstract Magnaporthe oryzae is one of the most destructive pathogens that threaten rice production around the world. Previous studies mainly focus on pathogenic mechanism of M. oryzae during infection on rice at leaf stage. However, the pathogenic mechanism of M. oryzae infection on panicle tissue is not well understood. In the present study, we performed RNA sequencing (RNA-seq) to study gene expression patterns of M. oryzae during infection at leaf stage and at panicle stage, respectively. The differentially expressed genes (DEGs) of M. oryzae in the infected leaf and panicle tissues were analyzed. Gene ontology (GO) enrichment analysis of DEGs revealed that M. oryzae genes involved in the biological processes were different at leaf and panicle stages. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of DEGs indicates that genes related to individual and important pathways may function at different infection stages. In particular, CAZymes carbohydrate esterases (CEs), carbohydrate-binding modules (CBMs), and glycoside hydrolases (GHs) may play important roles during M. oryzae infection on rice leaves, while glycosyltransferases (GTs) and GHs may play important roles during infection at rice panicle stage. Further analysis of effectors (BAS3, BAS113, BAS162, MoCDIP4, and MoHEG13) and their homologous genes suggest that they are involved in host defense suppression. Our findings provide insights into understanding the infection mechanisms of M. oryzae for rice leaf blast and panicle blast disease.

Abstract Although the functions of most protein effectors secreted by fungi are not predictable, they are known to modulate host immunity and facilitate infection. Fusarium graminearum is one of the 10 most abundant plant pathogenic fungi worldwide. To date, few effector proteins secreted by F. graminearum have been identified. In this study, we screened a putative effector protein Fg62 from proteins that contain signal peptides and unknown functional domains in F. graminearum secretome. Fg62 expression was highly upregulated during the early stages of F. graminearum infection, and its deletion reduced F. graminearum virulence in wheat and soybean. Transient expression of Fg62 or the recombinant protein led to plant cell death in Nicotiana benthamiana, and the signal peptide of Fg62 was required for cell death activation. Fg62 homologs are distributed in two species of the F. sambucinum species complex, which are also able to induce cell death in N. benthamiana. Fg62 activated plant immunity by increasing the expression of defense-related genes, and the recombinant Fg62 protein induced plant resistance to various pathogens. Overall, our results revealed that the extracellular effector Fg62 contributes to both pathogen virulence and plant immunity induction, providing new avenues for the development of environmentally friendly crop disease control strategies utilizing nonpolluting immune-inducing factors.

Abstract Climate change has a significant impact on the growth and distribution of vegetation worldwide. Hydrangea macrophylla is widely distributed and considered a model species for studying the distribution and responses of shrub plants under climate change. These results can inform decision‐making regarding shrub plant protection, management, and introduction of germplasm resources, and are of great importance for formulating ecological countermeasures to climate change in the future. We used the maximum entropy model to predict the change, scope expansion/reduction, centroid movement, and dominant climate factors that restrict the growth and distribution of H. macrophylla in China under current and future climate change scenarios. It was found that both precipitation and temperature affect the distribution of suitable habitat for H. macrophylla. Akaike information criterion (AICc) was used to select the feature combination (FC) and the regularization multiplier (RM). After the establishment of the optimal model (FC = QP, RM = 0.5), the complexity and over‐fitting degree of the model were low (delta AICc = 0, omission rate = 0.026, difference between training and testing area under the curve values = 0.0009), indicating that it had high accuracy in predicting the potential geographical distribution of H. macrophylla (area under the curve = 0.979). Overall, from the current period to future, the potential suitable habitat of this species in China expanded to the north. The greenhouse effect caused by an increase in CO2 emissions would not only increase the area of high‐suitability habitat in Central China, but also expand the area of total suitable habitat in the north. Under the maximum greenhouse gas emission scenario (RCP8.5), the migration distance of the centroid was the longest (e.g., By 2070s, the centroids of total and highly suitable areas have shifted 186.15 km and 89.84 km, respectively).

Background: Hepatocellular carcinoma (HCC) is a highly lethal cancer and is the second leading cause of cancer-related deaths worldwide. Unlike apoptosis, necroptosis (NCPS) triggers an immune response by releasing damage-related molecular factors. However, the clinical prognostic features of necroptosis-associated genes in HCC are still not fully explored.Methods: We analyzed the single-cell datasets GSE125449 and GSE151530 from the GEO database and performed weighted co-expression network analysis on the TCGA data to identify the necroptosis genes. A prognostic model was built using COX and Lasso regression. In addition, we performed an analysis of survival, immunity microenvironment, and mutation. Furthermore, the hub genes and pathways associated with HCC were localized within the single-cell atlas.Results: Patients with HCC in the TCGA and ICGC cohorts were classified using a necroptosis-related model with significant differences in survival times between high- and low-NCPS groups (p < 0.05). High-NCPS patients expressed more immune checkpoint-related genes, suggesting immunotherapy and some chemotherapies might prove beneficial to them. In addition, a single-cell sequencing approach was conducted to investigate the expression of hub genes and associated signaling pathways in different cell types.Conclusion: Through the analysis of single-cell and bulk multi-omics sequencing data, we constructed a prognostic model related to necroptosis and explored the relationship between high- and low-NCPS groups and immune cell infiltration in HCC. This provides a new reference for further understanding the role of necroptosis in HCC.

Background: Gastric cancer (GC) is the second leading cause of cancer-related mortality and the fifth most common cancer worldwide. However, the underlying mechanisms of competitive endogenous RNAs (ceRNAs) in GC are unclear. This study aimed to construct a ceRNA regulation network in correlation with prognosis and explore a prognostic model associated with GC.Methods: In this study, 1,040 cases of GC were obtained from TCGA and GEO datasets. To identify potential prognostic signature associated with GC, Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) regression were employed. The prognostic value of the signature was validated in the GEO84437 training set, GEO84437 test set, GEO15459 set, and TCGA-STAD. Based on the public databases, TargetScan and starBase, an mRNA-miRNA-lncRNA regulatory network was constructed, and hub genes were identified using the CytoHubba plugin. Furthermore, the clinical outcomes, immune cell infiltration, genetic variants, methylation, and somatic copy number alteration (sCNA) associated with the ceRNA network were derived using bioinformatics methods.Results: A total of 234 prognostic genes were identified. GO and GSEA revealed that the biological pathways and modules related to immune response and fibroblasts were considerably enriched in GC. A nomogram was generated to provide accurate prognostic outcomes and individualized risk estimates, which were validated in the training, test dataset, and two independent validation datasets. Thereafter, an mRNA-miRNA-lncRNA regulatory network containing 4 mRNAs, 22 miRNAs, 201 lncRNAs was constructed. The KCNQ1OT1/hsa-miR-378a-3p/RBMS1 ceRNA network associated with the prognosis was obtained by hub gene analysis and correlation analysis. Importantly, we found that the KCNQ1OT1/miR-378a-3p/RBMS1 axis may play a vital role in the diagnosis and prognosis of GC patients based on Cox regression analyses. Furthermore, our findings demonstrated that mutations and sCNA of the KCNQ1OT1/miR-378a-3p/RBMS1 axis were associated with increased immune infiltration, while the abnormal upregulation of the axis was primarily a result of hypomethylation.Conclusion: Our findings suggest that the KCNQ1OT1/miR-378a-3p/RBMS1 axis may be a potential prognostic biomarker and therapeutic target for GC. Moreover, such findings provide insights into the molecular mechanisms of GC pathogenesis.

The response of soil microorganisms to altered nitrogen (N) and rainfall patterns plays an important role in understanding ecosystem carbon and nitrogen cycling processes under global change. Previous studies have separately focused on the effects of N addition and rainfall on soil microbial diversity and community composition. However, the combined and interactive impact of N addition and rainfall on soil microbial diversity and function mediated by plant and soil processes have been poorly investigated for grassland ecosystems. Here, we conducted a field experiment with simulated N addition (N addition: 10 g N m–2yr–1) and altered rainfall pattern [control, rainfall reduction (compared to control –50%); rainfall addition (compared to control + 50%)] to study their interactive effects on soil microbial diversity and function in a temperate steppe of Inner Mongolia. Our results showed that N addition and rainfall addition significantly increased soil bacterial diversity, and the bacterial diversity was positively correlated with soil microbial biomass nitrogen, inorganic nitrogen, and Stipa krylovii root exudate C:N ratio, Allium polyrhizum root exudate C and N, and A. polyrhizum root exudate C:N ratio. N addition and rainfall reduction significantly reduced fungal diversity, which correlated closely with soil microbial biomass carbon and the C:N ratio of A. polyrhizum root exudates. Bacteria were mainly eutrophic r-strategists, and the responses of bacterial function guilds to the interaction between N addition and rainfall pattern were not significant. However, the arbuscular mycorrhizal fungi (AMF), in the functional classification of fungi, were significantly reduced under the condition of N addition and rainfall reduction, and the absolute abundance of the phylum Glomeromycota increased under rainfall addition, suggesting that AMFs are sensitive to altered N and rainfall patterns over short timescales (1 year). Collectively, our results have important implications for understanding the plant–soil–microbe system of grasslands under climate change.

The process of human exploration of the universe has accelerated, and aerospace technology has developed rapidly. The health management and prognosis guarantee of spacecraft systems has become an important basic technology. However, with thousands of telemetry data channels and massive data scales, spacecraft systems are increasingly complex. The anomaly detection that relied on simple threshold judgment and expert manual annotation in the past is no longer applicable. In addition, the particularity of the anomaly detection task leads to the lack of fault data for training. Therefore, a data-driven deep transfer learning-based approach is needed for rapid analysis and accurate detection of large-scale data. The control moment gyroscope (CMG) is a significant inertial actuator in the process of large-scale, long-life spacecraft in-orbit operation and mission execution. Its anomaly detection plays a major role in the prevention and elimination of early failures. Based on the research of SincNet and Long Short-Term Memory (LSTM) networks, this paper proposed a Sinc-LSTM neural network based on transfer learning and working condition classification for CMG anomaly detection. First, a two-stage pre-training method is proposed to alleviate the data imbalance, using the Mars Reconnaissance Orbiter (MRO) dataset and a satellite dataset from NASA. Second, the Sinc-LSTM network is designed to enhance the local fitting and long-period memory ability of the model for CMG time series data. Finally, a dynamic threshold judgment anomaly detection method based on working condition classification is designed to accommodate threshold changes for CMG full-cycle anomaly detection. The method is validated on the spacecraft CMG dataset.

The complexity of changeable marine backgrounds makes ship detection from satellite remote sensing images a challenging task. The ubiquitous interference of cloud and fog led to missed detection and false-alarms when using imagery-based optical satellite remote sensing. An off-shore ship detection method with scene classification and a saliency-tuned YOLONet is proposed to solve this problem. First, the image blocks are classified into four categories by a density peak clustering algorithm (DPC) according to their grayscale histograms, i.e., cloudless areas, thin cloud areas, scattered clouds areas, and thick cloud areas. Secondly, since the ships can be regarded as salient objects in a marine background, the spectral residue saliency detection method is used to extract prominent targets from different image blocks. Finally, the saliency tuned YOLOv4 network is designed to quickly and accurately detect ships from different marine backgrounds. We validated the proposed method using more than 2000 optical remote sensing images from the GF-1 satellite. The experimental results demonstrated that the proposed method obtained a better detection performance than other state-of-the-art methods.

Introduction: The development of diphtheria-tetanus-acellular pertussis-Haemophilus influenzae type b (Hib) conjugate vaccine combinations culminated with hexavalent vaccines, the largest, most complex vaccine combinations in the immunization calendar. Hexavalent vaccines are used widely in Europe and are co-administered with multiple other recommended vaccines. Hib immunogenicity may reduce when combined with acellular pertussis antigens, or in some co-administrations. We reviewed the epidemiology of H. influenzae disease in Europe aiming to evaluate the current level of Hib control and indirectly assess the effectiveness against Hib of GSK’s hexavalent vaccine in 10 countries where it is/has been used almost exclusively. Areas covered: We reviewed surveillance data from the European Union Invasive Bacterial Infections Surveillance Network and the European Surveillance System database from 1999–2014 and extracted case and incidence/notification rates (per 100,000 population) of invasive H. influenzae disease. We included age and serotype/strains distribution among countries in the European Union/European Economic Area region that reported to the European Centre for Disease Prevention and Control surveillance system. Expert commentary: The impact of Hib vaccination in Europe is sustained, testifying to continued effectiveness against invasive Hib disease after the implementation of hexavalent vaccines into immunization programs, which, since 2006, has been almost exclusively GSK´s hexavalent DTPa-HBV-IPV/Hib vaccine.

Abstract Tight gas sandstone samples are imaged at high resolution industrial X-ray computed tomography (ICT) systems to provide a three-dimensional quantitative characterization of the fracture geometries. Fracture networks are quantitatively analyzed using a combination of 2-D slice analysis and 3-D visualization and counting. The core samples are firstly scanned to produce grayscale slices, and the corresponding fracture area, length, aperture and fracture porosity as well as fracture density were measured. Then the 2-D slices were stacked to create a complete 3-D image using volume-rendering software. The open fractures (vug) are colored cyan whereas the calcite-filled fractures (high density objects) are colored magenta. The surface area and volume of both open fractures and high density fractures are calculated by 3-D counting. Then the fracture porosity and fracture aperture are estimated by 3-D counting. The fracture porosity and aperture from ICT analysis performed at atmospheric pressure are higher than those calculated from image logs at reservoir conditions. At last, the fracture connectivity is determined through comparison of fracture parameters with permeability. Distribution of fracture density and fracture aperture determines the permeability and producibility of tight gas sandstones. ICT has the advantage of performing three dimensional fracture imaging in a non-destructive way.

Abstract Background The need to translate research into policy, i.e. making research findings a driving force in agenda-setting and policy change, is increasingly acknowledged. However, little is known about translation mechanisms in the field of sexual and reproductive health (SRH) outside North American or European contexts. This paper seeks to give an overview of the existing knowledge on this topic as well as to document practical challenges and remedies from the perspectives of researchers involved in four SRH research consortium projects in Latin America, sub-Saharan Africa, China and India. Methods A literature review and relevant project documents were used to develop an interview guide through which researchers could reflect on their experiences in engaging with policy-makers, and particularly on the obstacles met and the strategies deployed by the four project consortia to circumvent them. Results Our findings confirm current recommendations on an early and steady involvement of policy-makers, however they also suggest that local barriers between researchers and policy-making spheres and individuals can represent major hindrances to the realization of translation objectives. Although many of the challenges might be common to different contexts, creating locally-adapted responses is deemed key to overcome them. Researchers’ experiences also indicate that - although inevitable - recognizing and addressing these challenges is a difficult, time- and energy-consuming process for all partners involved. Despite a lack of existing knowledge on translation efforts in SRH research outside North American or European contexts, and more particularly in low and middle-income countries, it is clear that existing pressure on health and policy systems in these settings further complicates them. Conclusions This article brings together literature findings and researchers’ own experiences in translating research results into policy and highlights the major challenges research conducted on sexual and reproductive health outside North American or European contexts can meet. Future SRH projects should be particularly attentive to these potential obstacles in order to tailor appropriate and consistent strategies within their existing resources.

Two generations of carbonate cement as Type I (microcrystalline calcite and dolomite) and Type II (mainly Fe-calcite and Fe-dolomite) are recognized in Chang 8 sandstones, Ordos basin. Carbonate cement in Chang 8 sandstones is closely related to the dissolved carbon from thermal maturation of organic matters. Carbonate cement in the loosely packed framework grains precipitated shortly after deposition, and late-stage ferroan calcite and ferroan dolomite formed with progressive burial. The early diagenetic carbonate cement is partially to completely replaced by late-stage ferroan calcite and ferroan dolomite. Carbonate cement is much more commonly observed in sand bodies adjacent to Chang 7 source rocks. With increasing distance from the Chang 7 oil layers, the carbonate cement content gradually decreases. However, some tight carbonate cemented zones also occur at the sandstone-mudstone interfaces. Dissolution of Ca-feldspars by organic acids-rich fluids, together with clay mineral transformations such as illitization of smectite, would provide Ca2+ and Mg2+ ions for carbonate cementation. Organic acids and CO2 rich fluids would charge into the reservoirs with the hydrocarbons, and when the CO2 and acids were buffered by the framework grain dissolution, carbonate cement would precipitate with a decrease in CO2 concentration.

Background: Gastric cancer (GC) is the second leading cause of cancer-related mortality and the fifth most common cancer worldwide. However, the underlying mechanisms of competitive endogenous RNAs (ceRNAs) in GC are unclear. This study aimed to construct a ceRNA regulation network in correlation with prognosis and explore a prognostic model associated with GC. Methods: In this study, 1,040 cases of GC were obtained from TCGA and GEO datasets. To identify potential prognostic signature associated with GC, Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) regression were employed. The prognostic value of the signature was validated in the GEO84437 training set, GEO84437 test set, GEO15459 set, and TCGA-STAD. Based on the public databases, TargetScan and starBase, an mRNA-miRNA-lncRNA regulatory network was constructed, and hub genes were identified using the CytoHubba plugin. Furthermore, the clinical outcomes, immune cell infiltration, genetic variants, methylation, and somatic copy number alteration (sCNA) associated with the ceRNA network were derived using bioinformatics methods. Results: A total of 234 prognostic genes were identified. GO and GSEA revealed that the biological pathways and modules related to immune response and fibroblasts were considerably enriched in GC. A nomogram was generated to provide accurate prognostic outcomes and individualized risk estimates, which were validated in the training, test dataset, and two independent validation datasets. Thereafter, an mRNAmiRNA-lncRNA regulatory network containing 4 mRNAs, 22 miRNAs, 201 lncRNAs was constructed. The KCNQ1OT1/hsa-miR-378a-3p/RBMS1 ceRNA network associated with the prognosis was obtained by hub gene analysis and correlation analysis. Importantly, we found that the KCNQ1OT1/miR-378a-3p/RBMS1 axis may play a vital role in the diagnosis and prognosis of GC patients based on Cox regression analyses. Furthermore, our findings demonstrated that mutations and sCNA of the KCNQ1OT1/miR-378a-3p/RBMS1 axis were associated with increased immune infiltration, while the abnormal upregulation of the axis was primarily a result of hypomethylation. Conclusion: Our findings suggest that the KCNQ1OT1/miR-378a-3p/RBMS1 axis may be a potential prognostic biomarker and therapeutic target for GC. Moreover, such findings provide insights into the molecular mechanisms of GC pathogenesis. [ABSTRACT FROM AUTHOR]