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Abstract Background Motor neuron disease (MND) is a fatal neurodegenerative disorder that leads to progressive loss of motor neurons. Chlamydia psittaci (C. psittaci) is a rare etiology of community-acquired pneumonia characterized primarily by respiratory distress. We reported a case of C. psittaci pneumonia complicated with motor neuron disease (MND). Case presentation A 74-year-old male was referred to the Shaoxing Second Hospital at January, 2022 complaining of fever and fatigue for 2 days. The patient was diagnosed of MND with flail arm syndrome 1 year ago. The metagenomic next-generation sequencing (mNGS) of sputum obtained through bedside fiberoptic bronchoscopy showed C. psittaci infection. Then doxycycline was administrated and bedside fiberoptic bronchoscopy was performed to assist with sputum excretion. Computed Tomography (CT) and fiberoptic bronchoscopy revealed a significant decrease in sputum production. On day 24 after admission, the patient was discharged with slight dyspnea, limited exercise tolerance. One month later after discharge, the patient reported normal respiratory function, and chest CT showed significant absorption of sputum. Conclusions The mNGS combined with bedside fiberoptic bronchoscopy could timely detect C. psittaci infection. Bedside fiberoptic bronchoscopy along with antibiotic therapy may be effective for C. psittaci treatment.

With the rapid development of the modern world, it is imperative to achieve effective and efficient monitoring for territories of interest, especially for the broad ocean area. For surveillance of ship targets at sea, a common and powerful approach is to take advantage of satellite synthetic aperture radar (SAR) systems. Currently, using satellite SAR images for ship classification is a challenging issue due to complex sea situations and the imaging variances of ships. Fortunately, the emergence of advanced satellite SAR sensors has shed much light on the SAR ship automatic target recognition (ATR) task, e.g., utilizing dual-polarization (dual-pol) information to boost the performance of SAR ship classification. Therefore, in this paper we have developed a novel cross-polarimetric interaction network (CPINet) to explore the abundant polarization information of dual-pol SAR images with the help of deep learning strategies, leading to an effective solution for high-performance ship classification. First, we establish a novel multiscale deep feature extraction framework to fully mine the characteristics of dual-pol SAR images in a coarse-to-fine manner. Second, to further leverage the complementary information of dual-pol SAR images, we propose a mixed-order squeeze–excitation (MO-SE) attention mechanism, in which the first- and second-order statistics of the deep features from one single-polarized SAR image are extracted to guide the learning of another polarized one. Then, the intermediate multiscale fused and MO-SE augmented dual-polarized deep feature maps are respectively aggregated by the factorized bilinear coding (FBC) pooling method. Meanwhile, the last multiscale fused deep feature maps for each single-polarized SAR image are also individually aggregated by the FBC. Finally, four kinds of highly discriminative deep representations are obtained for loss computation and category prediction. For better network training, the gradient normalization (GradNorm) method for multitask networks is extended to adaptively balance the contribution of each loss component. Extensive experiments on the three- and five-category dual-pol SAR ship classification dataset collected from the open and free OpenSARShip database demonstrate the superiority and robustness of CPINet compared with state-of-the-art methods for the dual-polarized SAR ship classification task.

IntroductionIn the era of the Internet, online digital traces have become a new way to study the online attention of scenic spots and tourists’ purchase behavior. The public’s information search on major search platforms is a series of manifestations of potential tourists’ attention and interest in scenic spots, but there are few studies on how attention, interest and information search affect potential tourists to generate real purchase behavior.MethodThis paper selects four dimensions of short video platform, travel website, search engine and social media to comprehensively measure the online attention of high-quality scenic spots in Yunnan Province, and then establishes a gray association analytic hierarchy process based on the relevant variables of the AISAS model to empirically analyze the primary and secondary factors affecting tourists’ purchase behavior.Results(1) From the perspective of the online attention of scenic spots on different platforms, the intensity of the public’s scenic spots online attention on the four types of media platforms is in the order of travel websites, search engines, short videos and social media (2) From the perspective of spatial distribution characteristics, the online attention of high-quality scenic spots in Yunnan Province is unevenly distributed, that is, there is a big difference between the attention of higher star scenic spots and their star rating and popularity, while the attention of low-star scenic spots is not much different from their star rating and popularity (3) From the perspective of spatial agglomeration characteristics, the comprehensive online attention of high-quality scenic spots in Yunnan Province presents the spatial agglomeration characteristics of “the multi-core linkage of high-density in the east and north, and sub-high-density in the south” (4) The factors influencing the purchase behavior of potential tourists are sharing experience, attracting attention, generating interest and searching information.DiscussionBy exploring the formation mechanism of high-quality scenic spots online attention in Yunnan Province and the mechanism of its spatial differentiation, this study not only enriches the logical chain of “tourism information source → potential tourists → demand driven → tourism information search → travel preference → destination selection → purchase decision → travel experience → real tourists → feelings after traveling → focus on feedback → tourism information source,” but also broadens the application scenarios and application boundaries of travel preference theory and AISAS behavior model to a certain extent.

Prevalence of carbapenem-resistant Klebsiella pneumoniae (CRKP) has compromised antimicrobial efficacy against severe infections worldwide. To monitor global spread, we conducted a comprehensive genomic epidemiologic study comparing sequences from 21 blaOXA-232–carrying CRKP isolates from China with K. pneumoniae sequence type (ST) 15 strains from 68 countries available in GenBank. Phylogenetic and phylogeographic analyses revealed all blaOXA-232–carrying CRKP isolates belonged to ST15 lineage and exhibited multidrug resistance. Analysis grouped 330 global blaOXA-232–carrying ST15 CRKP strains into 5 clades, indicating clonal transmission with small genetic distances among multiple strains. The lineage originated in the United States, then spread to Europe, Asia, Oceania, and Africa. Most recent common ancestor was traced back to 2000; mutations averaged ≈1.7 per year per genome. Our research helps identify key forces driving global spread of blaOXA-232–carrying CRKP ST15 lineage and emphasizes the importance of ongoing surveillance of epidemic CRKP.

In this paper, we give another definition of Ruston elements and almost Ruston elements, which is equivalent to the definitions given by Mouton and Raubenheimer in the case that the homomorphism has a closed range and Riesz property. For two homomorphisms, we consider the preserver problems of Fredholm theory and Fredholm spectrum theory. In addition, we study the spectral mapping theorems of Fredholm (Weyl, Browder, Ruston, and almost Ruston) elements relative to a homomorphism. Last but not least, the dependence of Fredholm theory on three homomorphisms is considered, and meanwhile, the transitivity of Fredholm theory relative to three homomorphisms is illustrated. Furthermore, we consider the Fredholm theory relative to more homomorphisms.

Colistin is considered as one of the last-resort antimicrobial agents for treating multidrug-resistant bacterial infections. Multidrug-resistant E. asburiae has been increasingly isolated from clinical patients, which posed a great challenge for antibacterial treatment. This study aimed to report a mcr-10 and blaNDM-1 co-carrying E. asburiae clinical isolate 5549 conferred a high-level resistance against colistin. Antibiotic susceptibility testing was performed using the microdilution broth method. Transferability of mcr-10 and blaNDM-1-carrying plasmids were investigated by conjugation experiments. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) was used to identify modifications in lipid A. Whole genome sequencing and phylogenetic analysis between strain 5549 and a total of 301 E. asburiae genomes retrieved from NCBI database were performed. The genetic characteristics of mcr-10 and blaNDM-1-bearing plasmids were also analyzed. Our study indicated that strain 5549 showed extensively antibiotic-resistant trait, including colistin and carbapenem resistance. The mcr-10 and blaNDM-1 were carried by IncFIB/IncFII type p5549_mcr-10 (159417 bp) and IncN type p5549_NDM-1 (63489 bp), respectively. Conjugation assays identified that only the blaNDM-1-carrying plasmid could be successfully transferred to E. coli J53. Interestingly, mcr-10 did not mediate colistin resistance when it was cloned into E. coli DH5α. Mass spectrometry analysis showed the lipid A palmitoylation of the C-lacyl-oxo-acyl chain to the chemical structure of lipid A at m/z 2063 in strain 5549. In summary, this study is the first to report a mcr-10 and blaNDM-1 co-occurrence E. asburiae recovered from China. Our investigation revealed the distribution of different clonal lineage of E. asburiae with epidemiology perspective and the underlying mechanisms of colistin resistance. Active surveillance is necessary to control the further dissemination of multidrug-resistant E. asburiae.

Synthetic Aperture Radar (SAR) imagery is significant in remote sensing, but the limited spatial resolution results in restricted detail and clarity. Current super-resolution methods confront challenges such as complex network structure, insufficient sensing capability, and difficulty extracting features with local and global dependencies. To address these challenges, DMSC-GAN, a SAR image super-resolution technique based on the c-GAN framework, is introduced in this study. The design objective of DMSC-GAN is to enhance the flexibility and controllability of the model by utilizing conditional inputs to modulate the generated image features. The method uses an encoder–decoder structure to construct a generator and introduces a feature extraction module that combines convolutional operations with Deformable Multi-Head Self-Attention (DMSA). This module can efficiently capture the features of objects of various shapes and extract important background information needed to recover complex image textures. In addition, a multi-scale feature extraction pyramid layer helps to capture image details at different scales. DMSC-GAN combines perceptual loss and feature matching loss and, with the enhanced dual-scale discriminator, successfully extracts features from SAR images for high-quality super-resolution reconstruction. Extensive experiments confirm the excellent performance of DMSC-GAN, which significantly improves the spatial resolution and visual quality of SAR images. This framework demonstrates strong capabilities and potential in advancing super-resolution techniques for SAR images.

ABSTRACT: Objectives: Carbapenem-resistant Klebsiella pneumoniae (CRKP) is increasingly reported worldwide and has posed a serious challenge for public health. Here we report the complete genome sequence of a multidrug-resistant (MDR) K. pneumoniae carrying one blaNDM-1 and two copies of blaKPC-2 genes isolated from a cerebrospinal fluid specimen in China. Methods: The minimal inhibitory concentrations (MICs) of 26 antimicrobial agents against K. pneumoniae strain KP46 were measured. The complete genome sequence of KP46 was determined using Illumina and Nanopore platforms. The derived short and long reads were assembled using Unicycler. Multilocus sequence typing (MLST), antimicrobial resistance genes, virulence genes, and plasmid replicons were predicted in silico using the BacWGSTdb server. The phylogenetic relationship between KP46 and 454 ST15 K. pneumoniae strains obtained from NCBI GenBank database was analysed based on a core genome MLST (cgMLST) strategy. Results: K. pneumoniae strain KP46 was resistant to all antimicrobial agents tested, except for tigecycline, colistin, cefiderocol, and fosfomycin. The genome sequence of KP46 belonged to sequence type 15 (ST15), which contained seven circularized contigs comprising 5 674 521 bp, including one chromosome and six plasmids. Serval antimicrobial resistance genes were identified, including a blaNDM-1 gene located in a 53 096 bp IncX3 plasmid, and two copies of blaKPC-2 gene located both in a 103 807 bp IncX6 and an 88 164 bp IncFII plasmid, respectively. The most closely related strain was another ST15 strain also isolated from China with five cgMLST loci differences. Conclusion: We reported the first complete genome sequence of a K. pneumoniae ST15 clinical isolate coharbouring blaNDM-1 and two copies of blaKPC-2 in China. This study will provide insight into the antimicrobial resistance mechanisms and phylogeny of carbapenem-resistant ST15 K. pneumoniae.

In the context of actively dealing with global climate change and accelerating green and low-carbon development, hydrogen energy, as a new energy carrier and a potential fuel, has attracted more and more attention. Unlike the fossil fuels, hydrogen energy can actually achieve carbon neutralization. Herein, focusing on the transportation and application of hydrogen energy, analysis was performed for current research situation of a series of processes for the whole hydrogen energy industry chain: preparation, storage, transportation, fueling and terminal utilization. In addition, the key technical problems for the transportation and utilization of hydrogen energy were summarized, the future development trend was defined and suggestions were proposed accordingly. According to the analysis, some progress has been made in the research on hydrogen energy at home and abroad, but due to the bottlenecks of technical cost and safety, hydrogen energy has not been applied at a large scale. In the future, core technology research on the key links of hydrogen energy industry chain should be carried out to accelerate the development of hydrogen energy industry, so as to realize the hydrogen energy supply in an economical, safe and efficient way.

High-resolution range profile (HRRP), characterized by its high availability and rich target structural information, has been extensively studied. However, HRRP-based target recognition methods using closed datasets exhibit limitations when it comes to identifying new classes of targets. The scarcity of samples for new classes leads to overfitting during the deep learning process, and the similarity in the scattering structures of different ships, combined with the significant structural differences among samples of the same ship, contribute to a high level of confusion among targets. To address these challenges, this paper proposed Task-Specific Mate-learning (TSML) for few-shot HRRP. Firstly, a Task-Adaptive Mixed Transfer (TAMT) strategy is proposed, which combines basic learning with meta-learning, to reduce the likelihood of overfitting and enhance adaptability for recognizing new classes of ships. Secondly, a Prototype Network is introduced to enable the recognition of new classes of targets with limited samples. Additionally, a Space-Adjusted Meta Embedding (SAME) is proposed based on the Prototype Network. This embedding function, designed for HRRP data, modifies the distances between samples in meta-tasks by increasing the distances between samples from different ships and decreasing the distances between samples from the same ship. The proposed method is evaluated based on an actual measured HRRP dataset and the experimental results prove that the proposed method can more accurately recognize the unknown ship classes with a small number of labels by learning the known classes of ships. In addition, the method has a degree of robustness to the number of training samples and a certain generalization ability, which can produce improved results when applied to other backbones.

Introduction: The development of tourism economy depends on air quality to a large extent, and good air quality is conducive to promoting the development of tourism economy. And it is crucial to understand the coupled and coordinated relationship between them. However, few studies have explored the coupling relationship between tourism and air quality. Therefore, it is necessary to further study the coupling relationship between tourism and air quality.Methods: In this study, an index system was constructed to evaluate the development status of tourism economy and air quality system, and the entropy value method was used to weight the indexes. Using panel data of Chinese provinces from 2014 to 2020, a coupled coordination model was established, focusing on the degree of coordination between tourism economy and air quality.Results: The empirical results show that during the sample period, China’s tourism economic index is decreasing, and the regional development is unbalanced, showing the gradient of eastern region > central region > western region. The air quality index, on the other hand, fluctuates and increases, showing a spatial distribution pattern of “weekly high, high and low” of western region > eastern region > central region. The coupling coordination level of both regions shows an increasing trend, with the eastern region having the highest coupling coordination level and always in the stage of barely balanced development; the central region has the second highest coupling coordination level and the coupling coordination level is steadily increasing; the western region has the worst coupling coordination level and the coupling system tends to decline. The main type of coupling coordination effect is tourism economy lagged type, and the overall performance shows that the ambient air quality condition is better than the tourism economy development.Discussion: This study clearly reveals the evolution, degree and types of coupling coordination in the tourism economy and air quality of the two systems, which contributes to the understanding of coupling and synergy of industrial development and ecological environment. This research also expands the application field of the CCDM model, and has a certain methodology contribution for further exploring the synergy and symbiosis mechanism of tourism economy development and environmental change.

Ureaplasma spp. and Mycoplasma hominis, frequent colonizers in the lower urogenital tract, have been implicated in various infections, with antibiotic resistance growing and varying regionally. This study aims to investigate the prevalence and antibiotic resistance profiles of Ureaplasma spp. and M. hominis in outpatients in Hangzhou, China, from 2013 to 2019. A total of 135,263 outpatients were examined to determine the prevalence of Ureaplasma spp. and M. hominis, including 48,638 males and 86,625 females. Furthermore, trends in antibiotic susceptibility of Ureaplasma spp. and M. hominis during 1999–2019 were analyzed. The cultivation, identification, and antibiotic susceptibility of the bacteria (ofloxacin, ciprofloxacin, erythromycin, clarithromycin, azithromycin, josamycin, tetracycline, doxycycline, and pristinamycin) were determined using the Mycoplasma IST2 kit. Our study indicated that the overall prevalence of total Ureaplasma spp./M. hominis was 38.1% from 2013 to 2019. Ureaplasma spp. were the most frequently isolated species (overall prevalence, 31.3%), followed by Ureaplasma spp./M. hominis coinfection (6.0%) and single M. hominis infection (0.8%). The prevalence of Ureaplasma spp. and M. hominis was significantly higher in females than in males, and the highest positive rates of total Ureaplasma spp./M. hominis were observed in both female and male outpatients aged 14–20 years. During 2013–2019, josamycin, tetracycline, doxycycline, and pristinamycin maintained exceptionally high activity (overall resistance rates, 70%). During 1999–2019, the rates of resistance to ofloxacin and ciprofloxacin increased against both Ureaplasma spp. and M. hominis but decreased to erythromycin, clarithromycin, azithromycin, tetracycline, and doxycycline against Ureaplasma spp. In conclusion, our study demonstrates a high prevalence of Ureaplasma spp. compared to M. hominis and Ureaplasma spp./M. hominis, and their distribution was associated with sex and age. Josamycin, doxycycline, and tetracycline are promising antibiotics that have remarkable activity against Ureaplasma species and M. hominis.

ABSTRACT The in vitro activity of two new fluoroquinolones, delafloxacin and finafloxacin, were evaluated against M. hominis and Ureaplasma spp. The MICs of delafloxacin, finafloxacin, and two classical fluoroquinolones (moxifloxacin and levofloxacin) were tested against 29 M. hominis and 67 Ureaplasma spp. isolates using the broth microdilution method. The molecular mechanisms underlying fluoroquinolone resistance were also investigated. Delafloxacin exhibited low MICs against M. hominis and Ureaplasma spp., including the levofloxacin-resistant isolates. For M. hominis, delafloxacin showed low MIC90 value of 1 μg/mL (MIC range, 32 μg/mL for levofloxacin. The two mutations GyrA S153L and ParC S91I were commonly identified in fluoroquinolone-resistant M. hominis, and ParC S83L was the most frequent mutation identified in fluoroquinolone-resistant Ureaplasma spp. Delafloxacin displayed lower MICs against fluoroquinolone-resistant isolates of both M. hominis and Ureaplasma spp. that have mutations in the quinolone resistance determining regions (QRDRs) than the two classical fluoroquinolones. Delafloxacin is a promising fluoroquinolone with low MICs against fluoroquinolone-resistant M. hominis and Ureaplasma spp. Our study confirms the potential clinical use of delafloxacin in treating antimicrobial-resistant M. hominis and Ureaplasma spp. infections. IMPORTANCE Fluoroquinolone resistance in Mycoplasma hominis and Ureaplasma spp. is on the rise globally, which has compromised the efficacy of the currently available antimicrobial agents. This study evaluated the antimicrobial activity of two new fluoroquinolones, delafloxacin and finafloxacin, for the first time, against M. hominis and Ureaplasma spp. clinical isolates. Delafloxacin and finafloxacin displayed different antimicrobial susceptibility profiles against M. hominis and Ureaplasma spp. in vitro. Delafloxacin was found to be more effective against M. hominis and Ureaplasma spp. than three classical fluoroquinolones (finafloxacin, moxifloxacin, and levofloxacin). Finafloxacin displayed activity similar to moxifloxacin but superior to levofloxacin against M. hominis and Ureaplasma spp. Our findings demonstrate that delafloxacin is a promising fluoroquinolone with outstanding activity against fluoroquinolone-resistant M. hominis and Ureaplasma spp.

Synthetic Aperture Radar (SAR) can provide rich feature information under all-weather and day-night conditions because it is not affected by climatic conditions. However, multiplicative speckle noise exists in SAR images, which makes it difficult to accurately identify some fuzzy targets in SAR images, such as roads and rivers, during semantic segmentation. This paper proposes an improved Deeplabv3+ network that can be effectively applied to the semantic segmentation task of SAR images. Firstly, this paper added the attention mechanism and, combined with the idea of an image pyramid, proposed the Feature Post-Processing Module (FPPM) to post-process the network output feature map, obtain better fine image features, and solve the problem of fuzzy texture and spectral features of SAR images. Compared to the original Deeplabv3+ network, the segmentation accuracy has been improved by 3.64% and mIoU improved by 1.09%. Secondly, to solve the problems of limited SAR image data and an unbalanced sample, this paper used the focal loss function to improve the backbone function of the network, which increased the mIoU by 1.01%. Finally, the Atrous Spatial Pyramid Pooling (ASPP) module was improved and the 3 × 3 void convolution in ASPP was decomposed into 2D, which can maintain the void ratio and effectively reduce the calculation amount of the module, shorten the training time by 19 ms and improve the semantic segmentation effect.

For the problem where the existing hyperspectral unmixing methods do not take full advantage of the correlations and differences between all these bands, resulting in affecting the final unmixing results, we design an enhanced 2DTV (E-2DTV) regularization term and suggest a blind hyperspectral unmixing method with the E-2DTV regularization term (E-gTVMBO), which adds E-2DTV regularization to the previous blind hyperspectral unmixing based on g-TV model. The E-2DTV regularization term is based on the gradient mapping of all bands of HSI, and the sparsity is calculated on the basis of the subspace, rather than applying sparsity to the gradient map itself, which can utilize the correlations and differences between all bands naturally. The experimental results prove the superiority of the E-gTVMBO method from both qualitative and quantitative perspectives. The research results can be applied to land cover classification, mineral analysis, and other fields.

The presence and dissemination of carbapenem-resistant Klebsiella pneumoniae (CRKP) often cause life-threatening infections worldwide, but the therapeutic option is limited. In this study, whole-genome sequencing (WGS) was applied to assess the epidemiological characteristics and transmission dynamics of CRKP isolates recovered from two fetal outbreaks of nosocomial infections. Between April 2016 and March 2018, a total of 70 isolates of K. pneumoniae were collected from sterile samples in a tertiary hospital in Hangzhou, China. The minimal inhibitory concentrations (MICs) of 21 antimicrobial agents were determined using the broth microdilution methods. Pulsed-field gel electrophoresis (PFGE) was performed on 47 CRKP isolates, and 16 clonally related isolates were further characterized by Illumina sequencing. In addition, the complete genome sequences of three representative isolates (KP12, KP36, and KP37) were determined by Oxford Nanopore sequencing. The K. pneumoniae isolates were recovered from patients diagnosed with pulmonary infection, cancer, or encephalopathy. For all CRKP isolates, PFGE separated three clusters among all strains. The most predominant PFGE cluster contained 16 isolates collected from patients who shared close hospital units and represented a potential outbreak. All 16 isolates showed an extremely high resistance level (≥87.5%) to 18 antimicrobials tested but remain susceptible to colistin (CST). Multiple antimicrobial resistance and virulence determinants, such as the carbapenem resistance gene blaKPC-2, and genes encoding the virulence factor aerobactin and the regulator of the mucoid phenotype (rmpA and rmpA2), were observed in the 16 CRKP isolates. These isolates belonged to sequence type 11 (ST11) and capsular serotype KL64. A core genome single nucleotide polymorphism (cgSNP)-based phylogenetic analysis indicated that the 16 CRKP isolates could be partitioned into two separate clades (≤15 SNPs), suggesting the two independent transmission scenarios co-occurred. Moreover, a high prevalence of IncFIB/IncHI1B type virulence plasmid with the iroBCDN locus deleted, and an IncFII/IncR type blaKPC-2-bearing plasmid was co-harbored in ST11-KL64 CRKP isolates. In conclusion, our data indicated that the nosocomial dissemination of ST11-KL64 CRKP clone is a potential threat to anti-infective therapy. The development of novel strategies for surveillance, diagnosis, and treatment of this high-risk CRKP clone is urgently needed.

Multidrug-resistant (MDR) Klebsiella pneumoniae is a severe threat to public health worldwide. Worryingly, colistin resistance, one of the last-line antibiotics for the treatment of MDR K. pneumoniae infection, has been increasingly reported. This study aims to investigate the emergence of evolved colistin resistance in a carbapenem-resistant K. pneumoniae isolate during colistin treatment. In this study, a pair of sequential carbapenem-resistant K. pneumoniae isolates were recovered from the same patient before and after colistin treatment, named KP1-1 and KP1-2, respectively. Antibiotic susceptibility testing was performed by the microdilution broth method. Whole genome sequencing was performed, and putative gene variations were analyzed in comparison of the genome sequence of both isolates. The bacterial whole genome sequence typing and source tracking analysis were performed by BacWGSTdb 2.0 server. Validation of the role of these variations in colistin resistance was examined by complementation experiments. The association between colistin resistance and the expression level of PhoP/PhoQ signaling system and its regulated genes was evaluated by quantitative real-time PCR (qRT-PCR) assay. Our study indicated that KP1-1 displayed extensively antibiotic resistant trait, but only susceptible to colistin. KP1-2 showed additional resistance to colistin. Both isolates belonged to Sequence Type 11 (ST11). The whole genome sequence analysis uncovered multiple resistance genes and virulence genes in both isolates. No plasmid-mediated mcr genes were found, but genetic variations in five chromosomal genes, especially the Gln30∗ alteration in MgrB, were detected in colistin-resistant isolate KP1-2. Moreover, only complementation with wild-type mgrB gene restored colistin susceptibility, with colistin MIC decreased from 32 to 1 mg/L. Expression assays revealed an overexpression of the phoP, phoQ, and pmrD genes in the mgrB-mutated isolate KP1-2 compared to the wild-type isolate KP1-1, confirming the MgrB alterations was responsible for increased expression levels of those genes. This study provides direct in vivo evidence that Gln30∗ alteration of MgrB is a critical region responsible for colistin resistance in K. pneumoniae clinical strains.

Objectives: Mycoplasma hominis is one of the smallest free-living opportunistic human pathogens responsible for a diverse range of infections. However, knowledge regarding the genetic and pathogenic mechanisms of M. hominis is still very limited. This study aimed to investigate the genomic features of a multidrug-resistant M. hominis isolate recovered from a synovial fluid sample in China. Methods: Antimicrobial susceptibility of M. hominis MH-1 was determined by broth microdilution. Genomic DNA was extracted and was sequenced using an Illumina HiSeq X Ten platform. De novo genome assembly was performed using SPAdes, and the draft genome was annotated using the NCBI Prokaryotic Genome Annotation Pipeline (PGAP). Core genome single nucleotide polymorphism (cgSNP) analysis between M. hominis MH-1 and all 25 M. hominis strains retrieved from the NCBI GenBank database was performed using BacWGSTdb server. Results: Antimicrobial susceptibility testing showed that M. hominis MH-1 was resistant to macrolides and fluoroquinolones. The genome size was calculated as 720 262 bp, with 608 protein-coding sequences and a G + C content of 26.8%. Several antimicrobial resistance genes, virulence genes, genomic islands and insertion sequences were identified in the genome. Phylogenetic analysis showed that the strains retrieved from NCBI as well as M. hominis MH-1 were not epidemiologically related. The closest relative of M. hominis MH-1 was recovered from the USA, which differed by 5898 SNPs. Conclusion: This study reports the first genome sequence of a multidrug-resistant M. hominis isolate in China. These data may help to understand the genomic features and antimicrobial resistance mechanisms of this pathogen.

The traditional fully connected convolutional conditional random field has a proven robust performance in post-processing semantic segmentation of SAR images. However, the current challenge is how to improve the richness of image features, thereby improving the accuracy of image segmentation. This paper proposes a polarization SAR image semantic segmentation method based on a dual-channel multi-size fully connected convolutional conditional random field. Firstly, the full-polarization SAR image and the corresponding optical image are input into the model at the same time, which can increase the richness of feature information. Secondly, multi-size input integrates image information of different sizes and models images of various sizes. Finally, the importance of features is introduced to determine the weights of polarized SAR images and optical images, and CRF is improved into a potential function so that the model can adaptively adjust the degree of influence of different image features on the segmentation effect. The experimental results show that the proposed method achieves the highest mean intersection over union (mIoU) and global accuracy (GA) with the least running time, which verifies the effectiveness of our method.

To solve the problems such as obvious speckle noise and serious spectral distortion when existing fusion methods are applied to the fusion of optical and SAR images, this paper proposes a fusion method for optical and SAR images based on Dense-UGAN and Gram–Schmidt transformation. Firstly, dense connection with U-shaped network (Dense-UGAN) are used in GAN generator to deepen the network structure and obtain deeper source image information. Secondly, according to the particularity of SAR imaging mechanism, SGLCM loss for preserving SAR texture features and PSNR loss for reducing SAR speckle noise are introduced into the generator loss function. Meanwhile in order to keep more SAR image structure, SSIM loss is introduced to discriminator loss function to make the generated image retain more spatial features. In this way, the generated high-resolution image has both optical contour characteristics and SAR texture characteristics. Finally, the GS transformation of optical and generated image retains the necessary spectral properties. Experimental results show that the proposed method can well preserve the spectral information of optical images and texture information of SAR images, and also reduce the generation of speckle noise at the same time. The metrics are superior to other algorithms that currently perform well.

Abstract The pathophysiologic mechanisms of epileptogenesis are poorly understood, and no effective therapy exists for suppressing epileptogenesis. Numerous reports have shown that nicotinamide adenine dinucleotide (NAD+) has neuroprotective effects, suggesting its potential use for treating epileptogenesis. Here we evaluated the effects of NAD+ on epileptogenesis and the mechanisms underlying these effects. In pilocarpine-induced status epilepticus (SE) model mice, NAD+ was injected three times within 24.5 h after SE. NAD+ intervention significantly reduced the incidence of spontaneous recurrent seizure (SRS) and abnormal electroencephalogram (EEG) activity, rescued contextual fear memory formation, reduced neuronal loss in the CA1 region of the hippocampus at SRS stage. Furthermore, exogenous supply of NAD+ distinctly reversed the seizure-induced depletion of endogenous NAD+, reduced neuronal apoptosis in the CA1 region of the hippocampus, and reversed the augmented Acp53/p53 ratio at the early stage of epileptogenesis. Our findings demonstrated that early-stage intervention with NAD+ prevents epileptogenesis in pilocarpine-induced SE mice by suppressing neuronal apoptosis.

The data presented in this article are related to the published entitled “Whole-genome sequencing of Bacillus velezensis LS69, a strain with a broad inhibitory spectrum against pathogenic bacteria” (Liu et al., 2017) [1]. Genome analysis revealed B. velezensis LS69 has a good potential for biocontrol and plant growth promotion. This article provides an extended analysis of the genetic islands, core genes and amylolysin loci of B. velezensis LS69.

A novel two-stage gridless sparsity-based method for sparse linear array direction-of-arrival (DOA) estimation is presented. First, the covariance matrix gridless sparse representation method based on atomic norm minimisation is proposed for corresponding structured Toeplitz matrix construction and source number detection. Then, the conventional MUSIC algorithm can be employed for DOA estimation. Compared with conventional subspace-based algorithms, the proposed two-stage method can be carried out without knowing source number and directly detect more source signals than sensors. Numerical simulations demonstrate the effectiveness and outperformance of the proposed method.

Purpose: Epilepsy is a highly disabling neurological disorder. Brain insult is the most critical cause of epilepsy in adults. This study aimed to find reliable and efficient biomarkers for predicting secondary epilepsy.Materials and methods: The LiCl-pilocarpine (LiCl-Pilo) chronic epilepsy rat model was used, and rat cerebrospinal fluid (CSF) was collected 5 days after status epilepticus (SE). The CSF was analyzed using the label-free LC-ESI-Q-TOF-MS/MS. Differential expression of proteins was confirmed using enzyme-linked immunosorbent assay (ELISA) and Western blotting. The corresponding protein level in the CSF of patients with encephalitis in the postacute phase was determined using ELISA and compared between patients with and without symptomatic epilepsy after encephalitis during a 2-year follow-up.Results: The proteomics and ELISA results showed that the protein level of kininogen (KNG) was obviously elevated in both CSF and hippocampus, but not in serum, 5 days after the onset of SE in LiCl-Pilo chronic epilepsy model rats. In patients with encephalitis, the protein level of KNG in the CSF in the postacute phase was significantly elevated in patients with a recurrent epileptic seizure during a 2-year follow-up than in patients without a recurrent seizure.Conclusion: KNG in the CSF may serve as a potential biomarker for predicting epileptogenesis in patients with encephalitis.

In terms of land cover classification, optical images have been proven to have good classification performance. Synthetic Aperture Radar (SAR) has the characteristics of working all-time and all-weather. It has more significant advantages over optical images for the recognition of some scenes, such as water bodies. One of the current challenges is how to fuse the benefits of both to obtain more powerful classification capabilities. This study proposes a classification model based on random forest with the conditional random fields (CRF) for feature-level fusion classification using features extracted from polarized SAR and optical images. In this paper, feature importance is introduced as a weight in the pairwise potential function of the CRF to improve the correction rate of misclassified points. The results show that the dataset combining the two provides significant improvements in feature identification when compared to the dataset using optical or polarized SAR image features alone. Among the four classification models used, the random forest-importance_ conditional random fields (RF-Im_CRF) model developed in this paper obtained the best overall accuracy (OA) and Kappa coefficient, validating the effectiveness of the method.

Synthetic aperture radar (SAR) provides rich information about the Earth’s surface under all-weather and day-and-night conditions, and is applied in many relevant fields. SAR imagery semantic segmentation, which can be a final product for end users and a fundamental procedure to support other applications, is one of the most difficult challenges. This paper proposes an encoding-decoding network based on Deeplabv3+ to semantically segment SAR imagery. A new potential energy loss function based on the Gibbs distribution is proposed here to establish the semantic dependence among different categories through the relationship among different cliques in the neighborhood system. This paper introduces an improved channel and spatial attention module to the Mobilenetv2 backbone to improve the recognition accuracy of small object categories in SAR imagery. The experimental results show that the proposed method achieves the highest mean intersection over union (mIoU) and global accuracy (GA) with the least running time, which verifies the effectiveness of our method.

Unmanned aerial vehicles (UAV) have had significant progress in the last decade, which is applied to many relevant fields because of the progress of aerial image processing and the convenience to explore areas that men cannot reach. Still, as the basis of further applications such as object tracking and terrain classification, semantic image segmentation is one of the most difficult challenges in the field of computer vision. In this paper, we propose a method for urban UAV images semantic segmentation, which utilizes the geographical information of the region of interest in the form of a digital surface model (DSM). We introduce an Affiliated Fusion Conditional Random Field (AF-CRF), which combines the information of visual pictures and DSM, and a multi-scale strategy with attention to improve the segmenting results. The experiments show that the proposed structure performs better than state-of-the-art networks in multiple metrics.

Ureaplasma spp. have gained increasing recognition as pathogens in both adult and neonatal patients with multiple clinical presentations. However, the clonality of this organism in the male population and infertile couples in China is largely unknown. In this study, 96 (53 U. parvum and 43 U. urealyticum) of 103 Ureaplasma spp. strains recovered from genital specimens from male patients and 15 pairs of infertile couples were analyzed using multilocus sequence typing (MLST)/expanded multilocus sequence typing (eMLST) schemes. A total of 39 sequence types (STs) and 53 expanded sequence types (eSTs) were identified, with three predominant STs (ST1, ST9 and ST22) and eSTs (eST16, eST41 and eST82). Moreover, phylogenetic analysis revealed two distinct clusters that were highly congruent with the taxonomic differences between the two Ureaplasma species. We found significant differences in the distributions of both clusters and sub-groups between the male and female patients (P < 0.001). Moreover, 66.7% and 40.0% of the male and female partners of the infertile couples tested positive for Ureaplasma spp. The present study also attained excellent agreement of the identification of both Ureaplasma species between paired urine and semen specimens from the male partners (k > 0.80). However, this concordance was observed only for the detection of U. urealyticum within the infertile couples. In conclusion, the distributions of the clusters and sub-groups significantly differed between the male and female patients. U. urealyticum is more likely to transmit between infertile couples and be associated with clinical manifestations by the specific epidemic clonal lineages.

The multilocus sequence typing (MLST) scheme of Ureaplasma based on four housekeeping genes (ftsH, rpL22, valS, and thrS) was described in our previous study; here we introduced an expanded MLST (eMLST) scheme with improved discriminatory power, which was developed by adding two putative virulence genes (ureG and mba-np1) to the original MLST scheme. To evaluate the discriminatory power of eMLST, a total of 14 reference strains of Ureaplasma serovars and 269 clinical strains (134 isolated from symptomatic patients and 135 obtained from asymptomatic persons) were investigated. Our study confirmed that all 14 serotype strains could successfully be differentiated into 14 eMLST STs (eSTs), while some of them could not even be differentiated by the MLST, and a total of 136 eSTs were identified among the clinical isolates we investigated. In addition, phylogenetic analysis indicated that two genetically significantly distant clusters (cluster I and II) were revealed and most clinical isolates were located in cluster I. These findings were in accordance with and further support for the concept of two well-known genetic lineages (Ureaplasma parvum and Ureaplasma urealyticum) in our previous study. Interestingly, although both clusters were associated with clinical manifestation, the sub-group 2 of cluster II had pronounced and adverse effect on patients and might be a potential risk factor for clinical outcomes. In conclusion, the eMLST scheme offers investigators a highly discriminative typing tool that is capable for precise epidemiological investigations and clinical relevance of Ureaplasma.

Prevalence of carbapenem-resistant Klebsiella pneumoniae (CRKP) has compromised antimicrobial efficacy against severe infections worldwide. To monitor global spread, we conducted a comprehensive genomic epidemiologic study comparing sequences from 21 blaOXA-232-carrying CRKP isolates from China with K. pneumoniae sequence type (ST) 15 strains from 68 countries available in GenBank. Phylogenetic and phylogeographic analyses revealed all blaOXA-232-carrying CRKP isolates belonged to ST15 lineage and exhibited multidrug resistance. Analysis grouped 330 global blaOXA-232-carrying ST15 CRKP strains into 5 clades, indicating clonal transmission with small genetic distances among multiple strains. The lineage originated in the United States, then spread to Europe, Asia, Oceania, and Africa. Most recent common ancestor was traced back to 2000; mutations averaged -1.7 per year per genome. Our research helps identify key forces driving global spread of blaOXA-232-carrying CRKP ST15 lineage and emphasizes the importance of ongoing surveillance of epidemic CRKP. [ABSTRACT FROM AUTHOR]