Draft genome sequence analysis of a mcr-1-producing Klebsiella pneumoniae ST661 isolated from a mink in China.

OBJECTIVES: Klebsiella pneumoniae is a major opportunistic pathogen that is a member of the Enterobacteriaceae. Klebsiella pneumoniae causes pneumonia in mink and has become the primary infectious disease that limits mink farming. In this study, we report the draft genome sequence of a multidrug-resistant (MDR) strain of K. pneumoniae that harbours the mcr-1 gene isolated from a mink in China. METHODS: The agar microdilution method was used to determine the minimum inhibitory concentration of the strain. The entire genomic DNA was sequenced using an Illumina MiSeq platform. A multilocus sequence type (MLST) and a core genome SNP phylogenetic tree analysis with a heatmap of the resistance genes and virulence genes were performed. RESULTS: The size of the genome was 5451.826 kb, and it included one chromosome and one plasmid. The draft genome of K. pneumoniae indicated that the isolate was a member of MLST 661. Four types of virulence genes were detected. The results of antimicrobial susceptibility testing showed multiple drug resistance, and 17 resistance genes were identified. CONCLUSION: The genome sequence reported in this study will help to reveal the key role of antibiotic resistance and pathogenic mechanisms. It will provide useful information for the role of mobile genetic elements in the adaptive translocation and spread of antimicrobial resistance.

Pleosmaranes A-R, Isopimarane and 20-nor Isopimarane Diterpenoids with Anti-inflammatory Activities from the Mangrove Endophytic Fungus Pleosporales sp. HNQQJ-1.

Pleosmaranes A-R (1-18), 18 new isopimarane-type diterpenoids, together with four known analogs (19-22), were isolated from the mangrove endophytic fungus Pleosporales sp. HNQQJ-1. Their structures and absolute configurations were established by analysis of their spectroscopic data and electronic circular dichroism (ECD) calculations. Compounds 1-9 possess an unusual aromatic B ring and a 20-nor-isopimarane skeleton. Compounds 15-17 contain a unique 2-oxabicyclo[2.2.2]octane moiety. Compound 18 features an unexpected 2-oxabicyclo[3.2.1]octane moiety. Compounds 8 and 12 exhibited a moderate inhibitory effect against LPS-induced NO production, with IC50 values of 19 and 25 µM, respectively.

MX1 and UBE2L6 are potential metaflammation gene targets in both diabetes and atherosclerosis.

Background: The coexistence of diabetes mellitus (DM) and atherosclerosis (AS) is widespread, although the explicit metabolism and metabolism-associated molecular patterns (MAMPs) responsible for the correlation are still unclear. Methods: Twenty-four genetically wild-type male Ba-Ma mini pigs were randomly divided into five groups distinguished by different combinations of 90 mg/kg streptozotocin (STZ) intravenous injection and high-cholesterol/lipid (HC) or high-lipid (HL) diet feeding for 9 months in total. Pigs in the STZ+HC and STZ+HL groups were injected with STZ first and then fed the HC or HL diet for 9 months. In contrast, pigs in the HC+STZ and HL+STZ groups were fed the HC or HL diet for 9 months and injected with STZ at 3 months. The controls were only fed a regular diet for 9 months. The blood glucose and abdominal aortic plaque observed through oil red O staining were used as evaluation indicators for successful modelling of DM and AS. A microarray gene expression analysis of all subjects was performed. Results: Atherosclerotic lesions were observed only in the HC+STZ and STZ+HC groups. A total of 103 differentially expressed genes (DEGs) were identified as common between them. The most significantly enriched pathways of 103 common DEGs were influenza A, hepatitis C, and measles. The global and internal protein-protein interaction (PPI) networks of the 103 common DEGs consisted of 648 and 14 nodes, respectively. The top 10 hub proteins, namely, ISG15, IRG6, IRF7, IFIT3, MX1, UBE2L6, DDX58, IFIT2, USP18, and IFI44L, drive aspects of DM and AS. MX1 and UBE2L6 were the intersection of internal and global PPI networks. The expression of MX1 and UBE2L6 was 507.22 ± 342.56 and 96.99 ± 49.92 in the HC+STZ group, respectively, which was significantly higher than others and may be linked to the severity of hyperglycaemia-related atherosclerosis. Further PPI network analysis of calcium/micronutrients, including MX1 and UBE2L6, consisted of 58 and 18 nodes, respectively. The most significantly enriched KEGG pathways were glutathione metabolism, pyrimidine metabolism, purine metabolism, and metabolic pathways. Conclusions: The global and internal PPI network of the 103 common DEGs consisted of 648 and 14 nodes, respectively. The intersection of the nodes of internal and global PPI networks was MX1 and UBE2L6, suggesting their key role in the comorbidity mechanism of DM and AS. This inference was partly verified by the overexpression of MX1 and UBE2L6 in the HC+STZ group but not others. Further calcium- and micronutrient-related enriched KEGG pathway analysis supported that MX1 and UBE2L6 may affect the inflammatory response through micronutrient metabolic pathways, conceptually named metaflammation. Collectively, MX1 and UBE2L6 may be potential common biomarkers for DM and AS that may reveal metaflammatory aspects of the pathological process, although proper validation is still needed to determine their contribution to the detailed mechanism.

Cytosporones with Anti-Inflammatory Activities from the Mangrove Endophytic Fungus Phomopsis sp. QYM-13.

Six previously undescribed cytosporone derivatives (phomotones A-E (1-5) and phomotone F (13)), two new spiro-alkanol phombistenes A-B (14-15), and seven known analogs (6-12) were isolated from the mangrove endophytic fungus Phomopsis sp. QYM-13. The structures of these compounds were elucidated using spectroscopic data analysis, electronic circular dichroism (ECD), and 13C NMR calculations. Compound 14 features an unprecedented 1,6-dioxaspiro[4.5]decane ring system. All isolates were evaluated for their inhibitory effect on nitric oxide (NO) in LPS-induced RAW264.7 cells. The results showed that compounds 1, 6, 8, and 11 exhibited potent bioactivities by comparing with positive control. Then, compound 1 displayed the anti-inflammatory effect by inhibiting the MAPK/NF-κB signaling pathways. Molecular docking further revealed the possible mechanism of compound 1 interaction with ERK protein.

Metabolites isolated from the mangrove endophytic fungus Didymella sp. CYSK-4 and their cytotoxic activities.

Two new 12- or 13- membered-ring macrocyclic alkaloids ascomylactam D and E (1 & 2), and a pair of new enantiomer (+)- and (-)- didymetone (3) were purified from the mangrove endophytic fungus Didymella sp. CYSK-4. Their structures and absolute configurations were determined by extensive spectroscopic analysis, single-crystal X-ray diffraction, ECD and 13C NMR calculations. Compound 2 exhibited significant cytotoxicity against human A549 and KYSE 150 cancer cell lines with IC50 values of 2.8 µM and 5.9 µM, respectively.

Efficient evaluation of photodynamic therapy on tumor based on deep learning.

Photodynamic therapy (PDT) is a non-invasive treatment method for treating tumors. Under laser irradiation, photosensitizers in tumor tissues generate biotoxic reactive oxygen, which can kill tumor cells. The traditional live/dead staining method of evaluating the cell mortality caused by PDT mainly depends on manual counting, which is time-consuming and relies on dye quality. In this paper, we have constructed a dataset of cells after PDT treatment and trained the cell detection model YOLOv3 to count both the dead and live cells. YOLO is a real time AI object detection algorithm. The achieved results demonstrate that the proposed method has a good performance in cell detection, with a mean average precision (mAP) of 94% for live cells and 71.3% for dead cells. This approach can efficiently evaluate the effectiveness of PDT treatment, thus speeding up treatment development effectively.

A heuristic method for rapid and automatic radiofrequency ablation planning of liver tumors.

PURPOSE: Preprocedural planning is a key step in radiofrequency ablation (RFA) treatment for liver tumors, which is a complex task with multiple constraints and relies heavily on the personal experience of interventional radiologists, and existing optimization-based automatic RFA planning methods are very time-consuming. In this paper, we aim to develop a heuristic RFA planning method to rapidly and automatically make a clinically acceptable RFA plan. METHODS: First, the insertion direction is heuristically initialized based on tumor long axis. Then, the 3D RFA planning is divided into insertion path planning and ablation position planning, which are further simplified into 2D by projections along two orthogonal directions. Here, a heuristic algorithm based on regular arrangement and step-wise adjustment is proposed to implement the 2D planning tasks. Experiments are conducted on patients with liver tumors of different sizes and shapes from multicenter to evaluate the proposed method. RESULTS: The proposed method automatically generated clinically acceptable RFA plans within 3 min for all cases in the test set and the clinical validation set. All RFA plans of our method achieve 100% treatment zone coverage without damaging the vital organs. Compared with the optimization-based method, the proposed method reduces the planning time by dozens of times while generating RFA plans with similar ablation efficiency. CONCLUSION: The proposed method demonstrates a new way to rapidly and automatically generate clinically acceptable RFA plans with multiple clinical constraints. The plans of our method are consistent with the clinical actual plans on almost all cases, which demonstrates the effectiveness of the proposed method and can help reduce the burden on clinicians.

Establishment of type 2 diabetes mellitus models using streptozotocin after 3 months high-fat diet in Bama minipigs.

In the past twenty years, the number of adults with diabetes has tripled. Most studies have been conducted using rodent models of type 2 diabetes mellitus (T2DM), and the developed drugs have low clinical conversion efficiency. Therefore, it is urgent to establish a more human-like large animal model to explore T2DM pathogenesis and formulate new disease prevention and control strategies. This study was designed to establish and validate a T2DM model using minipigs fed a high-fat or high-cholesterol/high-fat diet and injected with low-dose streptozotocin (STZ). We examined the influence of the STZ injection timing with a diet high in fat (HFD) compared with one high in cholesterol and fat (HCFD) on the atherosclerotic lesions accelerated by T2DM. Male Bama minipigs (n = 24) were randomly divided into five groups. The control group was fed a normal diet for 9 months. The STZ + HFD and STZ + HCFD groups were infused with 90 mg/kg STZ and then fed a high-fat diet or high-cholesterol and high-fat diet for 9 months, respectively. The HFD + STZ and HCFD + STZ groups were fed a high-fat diet or a high-cholesterol and high-fat diet, respectively, for 9 months (after 3 months, these pigs were injected intravenously with 90 mg/kg STZ). During the induction period, animal body weight, BMI, and serum GLU, INS, TG, TC, HDL-C, LDL-C, FFA, ALT, AST, CRE, and BUN were detected monthly intervals. IVGTT and insulin release tests were performed at 3-month intervals. At the end of the test, the coronary artery and abdominal aorta were examined by computed tomography and pathological observations, and the thickness of the basement membrane of the capillary of the retina and kidney glomerulus was measured under a transmission electron microscope. The serum glucose concentrations were normal in all groups except the HFD + STZ and HCFD + STZ groups. Animals fed an HFD for 9 months did not develop apparent atherosclerotic lesions, but atherosclerotic lesions were seen in the animals fed an HCFD. Hyperglycemia accelerated the formation of atherosclerotic lesions on the intimal surface of the abdominal aorta. Low-dose STZ after 3 months of HFD or HCFD successfully established a T2DM model in minipigs. The HFD did not induce apparent atherosclerotic lesions, but these were seen with the HCFD. Hyperglycemia accelerated atherosclerosis in the minipigs.

The Role and Mechanism of Polysaccharides in Anti-Aging.

The elderly proportion of the population is gradually increasing, which poses a great burden to society, the economy, and the medical field. Aging is a physiological process involving multiple organs and numerous reactions, and therefore it is not easily explained or defined. At present, a growing number of studies are focused on the mechanisms of aging and potential strategies to delay aging. Some clinical drugs have been demonstrated to have anti-aging effects; however, many still have deficits with respect to safety and long-term use. Polysaccharides are natural and efficient biological macromolecules that act as antioxidants, anti-inflammatories, and immune regulators. Not surprisingly, these molecules have recently gained attention for their potential use in anti-aging therapies. In fact, multiple polysaccharides have been found to have excellent anti-aging effects in different animal models including Caenorhabditis elegans, Drosophila melanogaster, and mice. The anti-aging qualities of polysaccharides have been linked to several mechanisms, such as improved antioxidant capacity, regulation of age-related gene expression, and improved immune function. Here, we summarize the current findings from research related to anti-aging polysaccharides based on various models, with a focus on the main anti-aging mechanisms of oxidative damage, age-related genes and pathways, immune modulation, and telomere attrition. This review aims to provide a reference for further research on anti-aging polysaccharides.

Optimized Deconvolutional Algorithm-based CT Perfusion Imaging in Diagnosis of Acute Cerebral Infarction.

To apply deconvolution algorithm in computer tomography (CT) perfusion imaging of acute cerebral infarction (ACI), a convolutional neural network (CNN) algorithm was optimized first. RIU-Net was applied to segment CT image, and then equipped with SE module to enhance the feature extraction ability. Next, the BM3D algorithm, Dn CNN, and Cascaded CNN were compared for denoising effects. 80 patients with ACI were recruited and grouped for a retrospective analysis. The control group utilized the ordinary method, and the observation group utilized the algorithm proposed. The optimized model was utilized to extract the feature information of the patient's CT images. The results showed that after the SE module pooling was added to the RIU-Net network, the utilization rate of the key features was raised. The specificity of patients in observation group was 98.7%, the accuracy was 93.7%, and the detected number was (1.6 ± 0.2). The specificity of patients in the control group was 93.2%, the accuracy was 87.6%, and the detected number was (1.3 ± 0.4). Obviously, the observation group was superior to the control group in all respects (P < 0.05). In conclusion, the optimized model demonstrates superb capabilities in image denoising and image segmentation. It can accurately extract the information to diagnose ACI, which is suggested clinically.

Companion Animals as Potential Reservoirs of Antibiotic Resistant Diarrheagenic Escherichia coli in Shandong, China.

Antibiotic resistance genes of Escherichia coli (E. coli) from companion animals were still poorly understood. Here, we investigated the extended-spectrum ß-lactamases (ESBLs) resistance genes of E. coli from companion animals in Shandong, China. A total of 79 isolates (80.6%) were recovered from 98 healthy or diarrheal companion animals in 2021, among which ESBLs-producing isolates accounted for 43.0% (34/79), and more than half of ESBL E. coli (ESBL-EC) strains (n = 19) were isolated from healthy companion animals. Diarrheagenic E. coli isolates (45.6%, n = 36) were represented by enterotoxigenic (ETEC) (32.9%), enteropathogenic (EPEC) (10.1%) and enteroinvasive (EIEC) (2.6%), 20 isolates of which were from healthy pets. Among tested antibiotics, resistance to tetracycline (64.6%) was the most commonly observed, followed by doxycycline (59.5%) and ampicillin (53.2%). Notably, all isolates were susceptible to meropenem. The multidrug-resistant (MDR) rate was 49.4%, 20 isolates of which were ESBLs producers; moreover, 23.4%, 16.4% of ESBL-EC strains were resistant to 5 or more, 7 or more antibiotics, respectively. Among the 5 ß-lactamase resistance genes, the most frequent gene was blaCTX-M (60.76%), followed by blaSHV (40.51%). The plasmid-mediated quinolone resistance (PMQR) gene aac(6')-Ib-cr was detected in 35 isolates. Additionally, ESBL-associated genes (i.e., blaCTX-M, blaSHV) were found in 76.5% ESBL-EC strains, with six isolates carrying blaCTX-M and blaSHV. The marker gene of high-pathogenicity island gene irp2 (encoding iron capture systems) was the most frequency virulence gene. Our results showed that ESBL-EC were widespread in healthy or diarrhea companion animals, especially healthy pets, which may be a potential reservoir of antibiotic resistance, therefore, enhancing a risk to public and animal health.

Prediction of early recurrence of hepatocellular carcinoma after liver transplantation based on computed tomography radiomics nomogram.

BACKGROUND: Early recurrence results in poor prognosis of patients with hepatocellular carcinoma (HCC) after liver transplantation (LT). This study aimed to explore the value of computed tomography (CT)-based radiomics nomogram in predicting early recurrence of patients with HCC after LT. METHODS: A cohort of 151 patients with HCC who underwent LT between December 2013 and July 2019 were retrospectively enrolled. A total of 1218 features were extracted from enhanced CT images. The least absolute shrinkage and selection operator algorithm (LASSO) logistic regression was used for dimension reduction and radiomics signature building. The clinical model was constructed after the analysis of clinical factors, and the nomogram was constructed by introducing the radiomics signature into the clinical model. The predictive performance and clinical usefulness of the three models were evaluated using receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA), respectively. Calibration curves were plotted to assess the calibration of the nomogram. RESULTS: There were significant differences in radiomics signature among early recurrence patients and non-early recurrence patients in the training cohort (P < 0.001) and validation cohort (P < 0.001). The nomogram showed the best predictive performance, with the largest area under the ROC curve in the training (0.882) and validation (0.917) cohorts. Hosmer-Lemeshow testing confirmed that the nomogram showed good calibration in the training (P = 0.138) and validation (P = 0.396) cohorts. DCA showed if the threshold probability is within 0.06-1, the nomogram had better clinical usefulness than the clinical model. CONCLUSIONS: Our CT-based radiomics nomogram can preoperatively predict the risk of early recurrence in patients with HCC after LT.

Diversified Polyketides With Anti-inflammatory Activities From Mangrove Endophytic Fungus Daldinia eschscholtzii KBJYZ-1.

In total, five new polyketide derivatives: eschscholin B (2), dalditone A and B (3 and 4), (1R, 4R)-5-methoxy-1,2,3,4-tetrahydronaphthalene-1,4-dio (5), and daldilene A (6), together with 10 known as analogs (1, 7-15) were isolated from the mangrove endophytic fungus Daldinia eschscholtzii KBJYZ-1. Their structures and absolute configurations were established by extensive analysis of NMR and HRESIMS spectra data combined with ECD calculations and the reported literature. Compounds 2 and 6 showed significant cell-based anti-inflammatory activities with IC50 values of 19.3 and 12.9 µM, respectively. In addition, western blot results suggested that compound 2 effectively inhibits the expression of iNOS and COX-2 in LPS-induced RAW264.7 cells. Further molecular biology work revealed the potential mechanism of 2 exerts anti-inflammatory function by inactivating the MAPK and NF-κB signaling pathways.

Robotic laser position versus freehand in CT-guided percutaneous microwave ablation for single hepatocellular carcinoma (diameter < 3 cm): a preliminary study.

PURPOSE: To compare the accuracy and safety of robotic laser position (RLP) versus freehand for antenna CT-guided microwave ablation (MWA) of single hepatocellular carcinoma (HCC) (diameter < 3 cm). MATERIALS AND METHODS: This retrospective study was conducted between May 2020 and June 2021. A total of 40 patients with early HCC who underwent CT-guided MWA were divided into two groups: a freehand group (n = 20) and a RLP group (n = 20). Based on in-plane and out-of-plane data, the actual puncture point error (APPE), number of repositioning procedures, and operative duration were compared using the Mann-Whitney U test. Ablation-related complications were compared using the Chi-squared test. RESULTS: The mean diameter of HCC patients who received MWA was 2.4 ± 0.5 cm. For in-plane APPE, APPE was comparable between the two groups (p = 0.299). However, for the out-of-plane position, the APPE in the freehand group was higher than that in the RLP group (p = 0.027). The number of repositioning procedures was 0 (range, 0-0) for RLP-guided procedures and 3 (range, 2-5) for freehand procedures, showing a statistically significant difference between the two groups (p < 0.001). The mean operative duration for freehand procedures was 39 min, compared with 26 min for RLP-guided procedures, showing a significant difference (p = 0.013). No deaths or major complications were directly related to MWA. Minor complications in the freehand group were comparable with those in the RLP group (p = 0.313). CONCLUSION: RLP guidance significantly reduces the number of antenna repositioning procedures in MWA and improves puncture accuracy for target HCC out-of-plane. In addition, the operative duration of robotic guidance was shorter than that of freehand guidance.

Harmonizing Pathological and Normal Pixels for Pseudo-Healthy Synthesis.

Synthesizing a subject-specific pathology-free image from a pathological image is valuable for algorithm development and clinical practice. In recent years, several approaches based on the Generative Adversarial Network (GAN) have achieved promising results in pseudo-healthy synthesis. However, the discriminator (i.e., a classifier) in the GAN cannot accurately identify lesions and further hampers from generating admirable pseudo-healthy images. To address this problem, we present a new type of discriminator, the segmentor, to accurately locate the lesions and improve the visual quality of pseudo-healthy images. Then, we apply the generated images into medical image enhancement and utilize the enhanced results to cope with the low contrast problem existing in medical image segmentation. Furthermore, a reliable metric is proposed by utilizing two attributes of label noise to measure the health of synthetic images. Comprehensive experiments on the T2 modality of BraTS demonstrate that the proposed method substantially outperforms the state-of-the-art methods. The method achieves better performance than the existing methods with only 30% of the training data. The effectiveness of the proposed method is also demonstrated on the LiTS and the T1 modality of BraTS. The code and the pre-trained model of this study are publicly available at https://github.com/Au3C2/Generator-Versus-Segmentor.

Cytotoxic Bromine- and Iodine-Containing Cytochalasins Produced by the Mangrove Endophytic Fungus Phomopsis sp. QYM-13 Using the OSMAC Approach.

Twelve new cytochalasins, phomopchalasins D-O (1-3, 5-12, and 14), including one brominated (2) and two iodinated cytochalasins (3 and 6), together with six known analogues (4, 13, and 15-18) were isolated from the mangrove-derived fungus Phomopsis sp. QYM-13 treated with 3% NaBr or 3% KI in potato liquid medium. Their structures and absolute configurations were established by extensive spectroscopic analysis (1D and 2D NMR, HRESIMS), electronic circular dichroism calculations, and a single-crystal X-ray diffraction experiment. Compounds 3 and 6 represent the first iodinated cytochalasins. Compounds 2, 15, 17, and 18 exhibited significant cytotoxicity against human cancer cell line MDA-MB-435 with IC50 values ranging from 0.2 to 8.2 µM.

Metabolites With Cytotoxic Activities From the Mangrove Endophytic Fungus Fusarium sp. 2ST2.

Two new 3-decalinoyltetramic acid derivatives with peroxide bridge fusarisetins E (1) and F (2), one new chromone fusarimone A (5), two new benzofurans fusarifurans A (9) and B (10), three new isocoumarins fusarimarins A-C (11-13), as well as five known analogues 3, 4, 6-8 and 14 were isolated from mangrove endophytic fungus Fusarium sp. 2ST2. Their structures and absolute configurations were established by spectroscopic analysis, density functional theory-gauge invariant atomic orbital NMR calculation with DP4+ statistical analysis, and electronic circular dichroism calculation. Compounds 1 and 2 showed significant cytotoxicity against human A549 cell lines with IC50 values of 8.7 and 4.3 µM, respectively.

Detection of Carbapenem Resistance of Proteus mirabilis Strains Isolated from Foxes, Raccoons and Minks in China.

Proteus mirabilis, an opportunistic pathogen, is found to be an emerging threat to both animals and humans for a variety of infections. However, the characteristics of P. mirabilis infections from foxes, raccoons and minks remain unclear. In this context, we identified the antibiotic resistance genes and virulence genes of P. mirabilis isolates from foxes, raccoons and minks in China. Most isolates showed resistance to florfenicol (90.57%), trimethoprim-sulfamethoxazole (73.58%), and imipenem (71.70%). A total of 73.58% of isolates were resistant to antibiotics from at least three or more classes, and were categorized as multi-drug resistant. A total of 33.33% of the isolates were resistant to antibiotics from seven classes. The most prevalent resistant were sul1 (94.34%), followed by floR, blaTEM, aac(6')Ib-cr and blaOXA-1 with the detection rate of 88.68%, 83.02%, 71.70% and 60.38%, respectively. Among the 51 P. mirabilis isolates that were resistant to beta-lactam antibiotics, all isolates carried at least one beta-lactam gene. In addition, blaNDM and blaOXA-24 genes were firstly reported in carbapenem-resistant P. mirabilis isolates from foxes, raccoons and minks. All isolates exhibited the virulence genes ureC, zapA, pmfA, atfA and mrpA. P. mirabilis isolates carrying all detected 10 virulence genes from different animal species showed different lethal abilities in a G. mellonella larvae model. More importantly, the profiles of antibiotic resistance genes of isolates from fur animals and the environment were generally similar, and phylogenetic analysis showed that the P. mirabilis isolates from farm environment samples may have close relatedness with that from animals.

Recombinase polymerase amplification assay for rapid detection of Seneca Valley Virus.

Seneca Valley virus (SVV) is related to vesicular disease in pigs, and its clinical symptoms are indistinguishable from other notifiable clinical symptoms of vesicular disease such as foot-and-mouth disease. The rapid and accurate detection of SVV is essential to confirm the pathogenic factors and initiate the implementation of control measures. The development of a rapid, simple, convenient, and low-cost molecular (nucleic acid amplification) test that can be used at the sample collection point has been identified as a key component for controlling SVV. This study describes the development and demonstration of recombinase polymerase amplification (RPA) test targeting the conserved regions of SVV for detection of SVV. The Primers and probes designed by us have shown good sensitivity and specificity in RPA test, which is helpful for RPA to be an effective tool for rapid diagnosis of SVV.

Few-shot medical image segmentation using a global correlation network with discriminative embedding.

Despite impressive developments in deep convolutional neural networks for medical imaging, the paradigm of supervised learning requires numerous annotations in training to avoid overfitting. In clinical cases, massive semantic annotations are difficult to acquire where biomedical expert knowledge is required. Moreover, it is common when only a few annotated classes are available. In this study, we proposed a new approach to few-shot medical image segmentation, which enables a segmentation model to quickly generalize to an unseen class with few training images. We constructed a few-shot image segmentation mechanism using a deep convolutional network trained episodically. Motivated by the spatial consistency and regularity in medical images, we developed an efficient global correlation module to model the correlation between a support and query image and incorporate it into the deep network. We enhanced the discrimination ability of the deep embedding scheme to encourage clustering of feature domains belonging to the same class while keeping feature domains of different organs far apart. We experimented using anatomical abdomen images from both CT and MRI modalities.