Search

ABSTRACTEnterohemorrhagic Escherichia coli (EHEC) O157:H7 is a common food-borne pathogen that can cause acute diseases. Lysine acetylation is a post-translational modification (PTM) that occurs in various prokaryotes and is regulated by CobB, the only deacetylase found in bacteria. Here, we demonstrated that CobB plays an important role in the virulence of EHEC O157:H7 and that deletion of cobB significantly decreased the intestinal colonization ability of bacteria. Using acetylation proteomic studies, we systematically identified several proteins that could be regulated by CobB in EHEC O157:H7. Among these CobB substrates, we found that acetylation at the K44 site of CesA, a chaperone for the type-III secretion system (T3SS) translocator protein EspA, weakens its binding to EspA, thereby reducing the stability of this virulence factor; this PTM ultimately attenuating the virulence of EHEC O157:H7. Furthermore, we showed that deacetylation of the K44 site, which is deacetylated by CobB, promotes the interaction between CesA and EspA, thereby increasing bacterial virulence in vitro and in animal experiments. In summary, we showed that acetylation influences the virulence of EHEC O157:H7, and uncovered the mechanism by which CobB contributes to bacterial virulence based on the regulation of CesA deacetylation.

Negative thermal expansion (NTE) defies the conventional wisdom of lattice dynamics and offers a novel way to control the expansion coefficient and address some challenges in modern science and technology. From an application standpoint, materials exhibiting NTE across a broad temperature range, including room temperature, are highly sought after. In this work, we propose the multi-doping strategy and prepared a series of rare-earth-based lithium oxides featuring negative thermal expansion, with the objective of adjusting their temperature range. The phase transition temperatures of these materials range from 202 K to 467 K, demonstrating a linear correlation with the average ionic radius of the rare-earth elements. By capitalizing on the synergistic effects of four rare-earth elements, we expand the full width at half maximum of the thermal expansion peak in Li(ErYHoDy)0.25O2 from 1.6 K to 14.5 K, a notable improvement of nearly tenfold is achieved. Additionally, we investigate the low-temperature magnetocaloric effects and inverse barocaloric effects within these rare-earth-based lithium oxides. Temperature- and pressure-dependent Raman scattering measurements indicate that the phase transitions and the barocaloric effects are associated with the stretching mode of the Li–O bond and the vibrational mode of the YO6 octahedron.

Abstract Nitric oxide (NO) is produced as an innate immune response against microbial infections. Salmonella Typhimurium (S. Typhimurium), the major causative pathogen of human gastroenteritis, induces more severe systemic disease in mice. However, host factors contributing to the difference in species-related virulence are unknown. Here, we report that host NO production promotes S. Typhimurium replication in mouse macrophages at the early infection stage by activating Salmonella pathogenicity island-2 (SPI-2). The NO signaling-induced SPI-2 activation is mediated by Fnr and PhoP/Q two-component system. NO significantly induced fnr transcription, while Fnr directly activated phoP/Q transcription. Mouse infection assays revealed a NO-dependent increase in bacterial burden in systemic organs during the initial days of infection, indicating an early contribution of host NO to virulence. This study reveals a host signaling-mediated virulence activation pathway in S. Typhimurium that contributes significantly to its systemic infection in mice, providing further insights into Salmonella pathogenesis and host–pathogen interaction.

The intracellular pathogen Salmonella enterica serovar Typhimurium (S. Typhimurium) exploits host macrophage as a crucial survival and replicative niche. To minimize host immune response stimulated by flagellin, the expression of flagellar genes is downregulated during S. Typhimurium growth within host macrophages. However, the underlying mechanisms are largely unknown. In this study, we show that STM14_1285 (named AsiR), a putative RpiR-family transcriptional regulator, which is downregulated within macrophages as previously reported and also confirmed here, positively regulates the expression of flagellar genes by directly binding to the promoter of flhDC. By generating an asiR mutant strain and a strain that persistently expresses asiR gene within macrophages, we confirmed that the downregulation of asiR contributes positively to S. Typhimurium replication in macrophages and systemic infection in mice, which could be attributed to decreased flagellar gene expression and therefore reduced flagellin-stimulated secretion of pro-inflammatory cytokines IL-1β and TNF-α. Furthermore, the acidic pH in macrophages is identified as a signal for the downregulation of asiR and therefore flagellar genes. Collectively, our results reveal a novel acidic pH signal-mediated regulatory pathway that is utilized by S. Typhimurium to promote intracellular replication and systemic pathogenesis by repressing flagellar gene expression.

Shigella is an intracellular pathogen that primarily infects the human colon and causes shigellosis. Shigella virulence relies largely on the type III secretion system (T3SS) and secreted effectors. VirF, the master Shigella virulence regulator, is essential for the expression of T3SS-related genes. In this study, we found that YhjC, a LysR-type transcriptional regulator, is required for Shigella virulence through activating the transcription of virF. Pathogenicity of the yhjC mutant, including colonization in the colons of guinea pigs as well as its ability for host cell adhesion and invasion, was significantly lowered. Expression levels of virF and nearly all VirF-dependent genes were downregulated by yhjC deletion, indicating that YhjC can activate virF transcription. Electrophoretic mobility shift assay analysis demonstrated that YhjC could bind directly to the virF promoter region. Therefore, YhjC is a novel virulence regulator that positively regulates the virF expression and promotes Shigella virulence. Additionally, genome-wide expression analysis identified the presence of other genes in the large virulence plasmid and a genome exhibiting differential expression in response to yhjC deletion, with 169 downregulated and 99 upregulated genes, indicating that YhjC also functioned as a global regulatory factor.

Salmonella Typhimurium establishes systemic infection by replicating in host macrophages. Here, Jiang et al. show that infected macrophages exhibit upregulated glycolysis and decreased serine synthesis, leading to accumulation of glycolytic intermediates that promote intracellular replication and virulence of S. Typhimurium.

The two-parameter constant false alarm rate (CFAR) detection algorithm uses the background average $u_{b}$ and the standard deviation $\sigma _{b}$ to determine the target detection threshold, which is simple and easy to implement. However, it is limited by the assumption of Gaussian distribution. Based on different probability distributions, the research improves the two-parameter CFAR algorithm, and proposes the two-parameter CFAR method based on initial detection, and the detection methods based on Loglogistic Distribution model and Adjoint Covariance Correction Model (ACCM). Three methods are used to detect and extract ocean targets in the same research area, and the results are compared and analyzed. The experimental results show that ACCM proposed in the research fits the long tail characteristic of the ocean background under complex ocean conditions well. Its goodness of fit is improved by nearly 50% compared with Loglogistic Distribution model, and its amount of false alarm of ocean target detection is 77.78% of Loglogistic model. In addition, in view of a large amount of calculation caused by the sliding window of the traditional two-parameter CFAR, OceanTDA9 deep learning model is designed for initial detection in research, which improves the detection speed of ocean targets.

Having been generated with a tremendous amount annually, paper waste (PW) represents a large proportion in municipal solid waste (MSW) and also a potential source of renewable energy production through the application of anaerobic digestion (AD). However, the recalcitrant lignocellulosic structure poses obstacles to efficient utilization in this way. Recently, anaerobic and microaerobic pretreatment have attracted attention as approaches to overcome the obstacles of biogas production. This study was set out to present a systematic comparison and assessment of anaerobic and microaerobic pretreatment of PW with different oxygen loadings by five microbial agents: composting inoculum (CI), straw-decomposing inoculum (SI), cow manure (CM), sheep manure (SM), and digestate effluent (DE). The hints of microbial community evolution during the pretreatment and AD were tracked by 16S rRNA high-throughput sequencing. The results demonstrated that PW pretreated by DE with an oxygen loading of 15 ml/gVS showed the highest cumulative methane yield (CMY) of 343.2 ml/gVS, with a BD of 79.3%. In addition to DE, SI and SM were also regarded as outstanding microbial agents for pretreatment because of the acceleration of methane production at the early stage of AD. The microbial community analysis showed that Clostridium sensu stricto 1 and Clostridium sensu stricto 10 possessed high relative abundance after anaerobic pretreatment by SI, while Bacteroides and Macellibacteroides were enriched after microaerobic pretreatment by SM, which were all contributable to the cellulose degradation. Besides, aerobic Bacillus in SI and Acinetobacter in SM and DE probably promoted lignin degradation only under microaerobic conditions. During AD, VadinBC27, Ruminococcaceae Incertae Sedis, Clostridium sensu stricto 1, Fastidiosipila, and Caldicoprobacter were the crucial bacteria that facilitated the biodegradation of PW. By comparing the groups with same microbial agent, it could be found that changing the oxygen loading might result in the alternation between hydrogenotrophic and acetoclastic methanogens, which possibly affected the methanogenesis stage. This study not only devised a promising tactic for making full use of PW but also provided a greater understanding of the evolution of microbial community in the pretreatment and AD processes, targeting the efficient utilization of lignocellulosic biomass in full-scale applications.

In recent years, the rapid development of Deep Learning (DL) has provided a new method for ship detection in Synthetic Aperture Radar (SAR) images. However, there are still four challenges in this task. (1) The ship targets in SAR images are very sparse. A large number of unnecessary anchor boxes may be generated on the feature map when using traditional anchor-based detection models, which could greatly increase the amount of computation and make it difficult to achieve real-time rapid detection. (2) The size of the ship targets in SAR images is relatively small. Most of the detection methods have poor performance on small ships in large scenes. (3) The terrestrial background in SAR images is very complicated. Ship targets are susceptible to interference from complex backgrounds, and there are serious false detections and missed detections. (4) The ship targets in SAR images are characterized by a large aspect ratio, arbitrary direction and dense arrangement. Traditional horizontal box detection can cause non-target areas to interfere with the extraction of ship features, and it is difficult to accurately express the length, width and axial information of ship targets. To solve these problems, we propose an effective lightweight anchor-free detector called R-Centernet+ in the paper. Its features are as follows: the Convolutional Block Attention Module (CBAM) is introduced to the backbone network to improve the focusing ability on small ships; the Foreground Enhance Module (FEM) is used to introduce foreground information to reduce the interference of the complex background; the detection head that can output the ship angle map is designed to realize the rotation detection of ship targets. To verify the validity of the proposed model in this paper, experiments are performed on two public SAR image datasets, i.e., SAR Ship Detection Dataset (SSDD) and AIR-SARShip. The results show that the proposed R-Centernet+ detector can detect both inshore and offshore ships with higher accuracy than traditional models with an average precision of 95.11% on SSDD and 84.89% on AIR-SARShip, and the detection speed is quite fast with 33 frames per second.

The dynamic map is applied instead of traditional static maps in the teaching of geographic information science (GIS)‐related majors so as to meet the need for teaching animations and teaching interaction in new teaching methods such as mobile personalized learning, massive open online course, and Flipped Classroom. The research introduces the concept and the making tools of dynamic maps, studies the making principles and key technologies of dynamic maps, and constructs the relevant theories such as the "frame" model based on time granularity, the dynamic interpolation algorithm based on spatial characteristics, dynamic symbolic logic model, and algorithm. Based on the above principles and theories, taking a dynamic map of the change in the population of each city in Shandong province as an example, the research demonstrates the making method and process of the dynamic maps for teaching with Flash MX. At last, it analyzes the role of dynamic map in GIS‐related courses teaching and evaluates the teaching effect of dynamic maps. [ABSTRACT FROM AUTHOR]

To adapt to the needs of teaching modes such as network distance education and mobile online learning, and overcome the space‐time limitation of traditional offline education, the construction of online courses has become an important task of informatization in education. The research analyzes several key technologies for the construction of online courses and proposes solutions for making dynamic maps and demonstration animations, sharing relevant teaching resources, cloud classroom design, special experiment design, and online testing and question & answer (Q & A). On this basis, with the index system of "Modern Distance Education Standards" as a reference, the national standard and evaluation plan of online courses as guides, and computer technology and multimedia technology as means, the research develops an online course case of Marine Geographic Information System (MGIS). Based on the.NET platform, construct a teaching resource website supporting MGIS. The online course and its supporting teaching resources website have realized the characteristic function of personalized self‐learning, dynamic demonstration of knowledge, online testing according to different learning stages, interesting experiments to stimulate learning enthusiasm, intelligent feedback learning effect, and so on. Through application and practice in teaching, the website of online courses and resources has achieved a good teaching effect. [ABSTRACT FROM AUTHOR]

Constant False‐Alarm Rate (CFAR) algorithm is a mature method in marine target detection at present, the key of which is the choice of probability model. The most classical probability model is Gaussian distribution, which is suitable for modeling the calm ocean surface. Complex ocean conditions generally do not obey to Gaussian distribution, which limits the performance of CFAR algorithm. Therefore, we propose Adjoint Covariance Correction Model (ACCM) to improve the performance of CFAR marine target detection. Analyzing the distribution characteristic of ocean clutter under complex ocean conditions based on experiments, we find that it has long‐tail characteristic. Aiming at this characteristic, we have conducted fitting experiment on 23 kinds of probability density functions (PDFs) and find Loglogistic distribution has a better fitting effect on long‐tail characteristic, therefore, we use it to model ocean clutter under complex ocean conditions for the first time. In order to further improve the fitting goodness, we add a variance correction term to the Loglogistic model to construct ACCM for marine target extraction. The experiment result shows that ACCM effectively fits the long‐tail characteristic caused by Synthetic Aperture Radar backscatter under complex ocean conditions. The goodness of fit improves by 50% compared with Loglogistic model, and the amount of false alarms is 81.42% of that of Loglogistic model. The extraction accuracy of marine target characteristic parameter based on ACCM is 11.58% higher than that of Loglogistic model, and 12.18% higher than that of two‐parameter CFAR model based on standard error function (named SEF‐CFAR). Key Points: Propose Adjoint Covariance Correction Model and derive its formula, improve accuracyFind long tail feature, use Loglogistic to modelUse OceanTD to initially detect [ABSTRACT FROM AUTHOR]

On the basis of summarizing the research results of visual variables, we define six dynamic visual variables of the map symbol in this paper. We analyze the related attributes of dynamic symbols, and then construct a dynamic map expression model based on symbols. A key technology to realize dynamic expression, the key frame transform algorithm is present in the paper. The cartography process of the urban population proportion dynamic change map of the cities in Shandong province are taken as an example to demonstrate the methods and process of dynamic mapping based on the above map dynamic expression theories and models, which includes base map digitization, sorting and processing of attribute data, adding the map elements, the creation of special dynamic effect such as color transform, continuous flashing and object moving, and realization of interactive function. Finally, the paper shows the dynamic map of sea level rising influence on Qingdao, the Typhoon Soulik traveling map and other dynamic map effect at the end of the article. [ABSTRACT FROM AUTHOR]

This paper puts forward the new definition on the basis of the original concept of the navigation electronic map, designs the structure of the navigation electronic map system which contains three parts: hardware equipment, data system and software system, and analyzes each part of them in detail, finally this paper discusses the functional framework of the navigation electronic map. [ABSTRACT FROM AUTHOR]