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Purpose To develop an immunotype-based prognostic model for predicting the overall survival (OS) of patients with clear cell renal carcinoma (ccRCC). We explored novel immunotypes of patients with ccRCC, particularly those associated with overall survival. A risk-metastasis model was constructed by integrating the immunotypes with immune genes and used to test the accuracy of the immunotype model. Patients and Methods Patient cohort data were obtained from The Cancer Genome Atlas (TCGA) database, Gene Expression Omnibus (GEO) database, Renji database, and Surveillance, Epidemiology, and End Results (SEER) database. We employed the R software to select 3 immune cells and construct an immunotype-based prediction model. Immune genes selected using random Forest Algorithm were validated by immunohistochemistry (IHC). The H&L risk-metastasis model was constructed to assess the accuracy of the immunotype model through Multivariate COX regression analysis. Result Patients with ccRCC were categorized into immunotype H subgroup and immunotype L subgroup based on the overall survival rates. The immunotypes were found to be the independent prognostic index for ccRCC prognosis. As such, we constructed a new immunotypes-based SSIGN model. Three immune genes associated with difference between immunotype H and L were identified. An H&L risk-metastasis model was constructed to evaluate the accuracy of the immunotype model. Compared to the W-Risk-metastasis model which did not incorporate immunotypes, the H&L risk-metastasis model was more precise in predicting the survival of ccRCC patients. Conclusion The established immunotype model can effectively predict the survival of ccRCC patients. Except for mast cells, T cells and macrophages are positively associated with the overall survival of patients. The three immune genes identified, herein, can predict the survival rate of ccRCC patients, and expression of these immune genes is strongly linked to poor survival. The new SSIGN model provides an accurate tool for predicting the survival of ccRCC patients. H&L risk-metastasis model can effectively predict the risk of tumor metastasis.

The nanopore technique employs a nanoscale cavity to electrochemically confine individual molecules, achieving ultrasensitive single-molecule analysis based on evaluating the amplitude and duration of the ionic current. However, each nanopore sensing interface has its own intrinsic sensing ability, which does not always efficiently generate distinctive blockade currents for multiple analytes. Therefore, analytes that differ at only a single site often exhibit similar blockade currents or durations in nanopore experiments, which often produces serious overlap in the resulting statistical graphs. To improve the sensing ability of nanopores, herein we propose a novel shapelet-based machine learning approach to discriminate mixed analytes that exhibit nearly identical blockade current amplitudes and durations. DNA oligomers with a single-nucleotide difference, 5'-AAAA-3' and 5'-GAAA-3', are employed as model analytes that are difficult to identify in aerolysin nanopores at 100 mV. First, a set of the most informative and discriminative segments are learned from the time-series data set of blockade current signals using the learning time-series shapelets (LTS) algorithm. Then, the shapelet-transformed representation of the signals is obtained by calculating the minimum distance between the shapelets and the original signals. A simple logistic classifier is used to identify the two types of DNA oligomers in accordance with the corresponding shapelet-transformed representation. Finally, an evaluation is performed on the validation data set to show that our approach can achieve a high

Nanopores employ the ionic current from the single molecule blockage to identify the structure, conformation, chemical groups and charges of a single molecule. Despite the tremendous development in designing sensitive pore-forming materials, at some extent, the analyte with the single group difference still exhibits similar residual current or duration time. The serious overlap in the statistical results of residual current and duration time brings the difficulties in the nanopore discrimination of each single molecules from the mixture. In this paper, we present the AdaBoost-based machine learning model to identify the multiple analyte with single group difference in the mixed blockages. A set of feature vectors which is obtained from Hidden Markov Model (HMM) is used to train the AdaBoost model. By employing the aerolysin sensing of 5ʹ-AAAA-3ʹ (AA3) and 5ʹ-GAAA-3ʹ (GA3) as the model system, our results show that AdaBoost model increases the identification accuracy from ~ 0.293 to above 0.991. Furthermore, five sets of mixed blockages of AA3 and GA3 further validate the average accuracy of training and validation, which are 0.997 and 0.989, respectively. The proposed methods improve the capacity of wild-type biological nanopore in efficiently identify the single nucleotide difference without designing of protein and optimizing of the experimental condition. Therefore, the AdaBoost-based machine learning approach could promote the nanopore practical application such as genetic and epigenetic detection.

The adaptability to wide salinities remains a big challenge for artificial nanofluidic systems, which plays a vital role in water-energy nexus science. Here, inspired by euryhaline fish, sandwich-structured nanochannel systems are constructed to realize salinity self-adaptive nanofluidic diodes, which lead to high-performance salinity-gradient power generators with low internal resistance. Adaptive to changing salinity, the pore morphology of one side of the nanochannel system switches from a 1D straight nanochannel (45 nm) to 3D network pores (1.9 nm pore size and ≈10

The fault logs record the fault information generated during the operation process of industrial robots. It contains a large amount of fault knowledge and solution information. It is necessary to extract this information and build the fault diagnosis knowledge graph of industrial robots, which can support remote fault diagnosis of industrial robots without human help. At present, the research of fault diagnosis knowledge graph is still relatively scarce. In this paper, we propose a method of named entity recognition for extracting the knowledge of industrial robot fault diagnosis. The contribution of our paper is to establish the fault field dataset Fault-Data, propose the ontology concept of the fault diagnosis field, and obtain a good field recognition effect through the verification of the entity recognition model of fault diagnosis. Experimental results show that the F value of named entity recognition reaches 91.99%, which provides a certain reference significance for subsequent knowledge extraction and knowledge graph construction.

The Nothybidae of China are reviewed, including Nothybus absens Lonsdale & Marshall, 2016 which was previously known only from photographs, is here redescribed on the basis of male and female specimens. A key to Chinese species of Nothybidae is provided.

Methicillin-resistant Staphylococcus aureus (MRSA) and its biofilms infection is still a serious threat to global health. It is urgent to develop efficient drugs by repositioning or designing drugs to solve this problem. In this study, the antibacterial/biofilm activity and mechanisms of ivermectin (D) and its 4′′-position amino substitution derivative (D4) against MRSA were investigated. The minimum inhibitory concentration (MIC) of D was 20 μg/mL, which is four times higher than D4 (MIC = 5 μg/mL). The mechanism research demonstrated that D4 was more potent than D at destroying bacterial cell wall, permeating cell membrane (6.25–36.0% vs 1.92–6.04%) and binding to MRSA genomic DNA. Moreover, after incubation with 10–40 μg/mL D4 for 24 h, the percentages of biofilm decreased by 21.2–92.9%, which was more effective than D (no significant change at 40 μg/mL). The antibiofilm effect is achieved by regulating the expression of related genes (RSH, relQ, rsbU, sigB, spA, and icaD). Additionally, though the higher hemolysis makes D4 a safety risk for intravenous injection, other administration options could be considered as well. Therefore, all the results have indicated that D4 may be a potential candidate compound for the treatment of MRSA and its biofilm infections.

Background Renal cell carcinoma (RCC) is a common urologic malignancy. Although the relationship between clear cell RCC (ccRCC) and obesity has been well-established by several large-scale retrospective studies, the molecular mechanisms and genetic characteristics behind this correlation remains unclear. In the current study, several bioinformatics tools were used to identify the key genes in ccRCC related to obesity. Methods Microarray data comparing ccRCC with normal renal tissues in patients with and without obesity were downloaded from the GEO database for screening of differentially expressed genes (DEGs). The DEGs were verified with expression level and survival analysis using several online bioinformatics tools. Results In the current study, the differential expression of five genes correlated with both ccRCC and obesity; IGHA1 and IGKC as oncogenes, and MAOA, MUC20 and TRPM3 as tumor suppressor genes. These genes were verified by comparing the relationship between the expression levels and survival outcomes from open-source data in The Cancer Genome Atlas (TCGA) dataset. Conclusions In conclusion, the five genes differentially expressed in ccRCC and obesity are related to disease progression and prognosis, and therefore could provide prognostic value for patients with ccRCC.

Incremental learning of semantic segmentation has emerged as a promising strategy for visual scene interpretation in the open- world setting. However, it remains challenging to acquire novel classes in an online fashion for the segmentation task, mainly due to its continuously-evolving semantic label space, partial pixelwise ground-truth annotations, and constrained data availability. To ad- dress this, we propose an incremental learning strategy that can fast adapt deep segmentation models without catastrophic forgetting, using a streaming input data with pixel annotations on the novel classes only. To this end, we develop a uni ed learning strategy based on the Expectation-Maximization (EM) framework, which integrates an iterative relabeling strategy that lls in the missing labels and a rehearsal-based incremental learning step that balances the stability-plasticity of the model. Moreover, our EM algorithm adopts an adaptive sampling method to select informative train- ing data and a class-balancing training strategy in the incremental model updates, both improving the e cacy of model learning. We validate our approach on the PASCAL VOC 2012 and ADE20K datasets, and the results demonstrate its superior performance over the existing incremental methods., Comment: Accepted by ACM MM'21

Additional file 1: Table S1. Design of ppGpp metabolism and biofilm formation related genes primer. Fig. S1. Predictions of IDR-1018 (A, B) and 1018M (C, D) tertiary structures. Fig. S2. Liquid chromatogram of peptides and ppGpp binding.

To report our preliminary results of thermal ablation, including microwave and radiofrequency ablation assisted laparoscopic partial nephrectomy for cT1b renal tumors.A total of 56 patients with cT1b renal tumors who underwent microwave ablation or radiofrequency ablation assisted laparoscopic partial nephrectomy between January 2014 and May 2018 were enrolled. Thirty of them underwent microwave ablation assisted laparoscopic partial nephrectomy (MWA-LPN group), and the other 26 received radiofrequency ablation assisted laparoscopic partial nephrectomy (RFA-LPN group). Baseline, perioperative and follow-up data were compared between the two groups.There were no statistical differences with respect to patients' gender, age, tumor size, RENAL score, BMI and estimated glomerular filtration rate between the MWA-LPN and RFA-LPN group, nor were any differences observed in warm ischemia time, post-operative complications and hospital stay. Patients in the MWA-LPN group had shorter median operative time (Thermal ablation assisted laparoscopic partial nephrectomy is a safe, effective nephron-sparing treatment which provides acceptable results for selective cT1b renal tumors.

Glued-laminated timber arches are widely used in gymnasiums, bridges, and roof trusses. However, studies on their mechanical behaviours and design methods are still insufficient. This paper investigates the in-plane loading capacity of circular glued-laminated timber arches made of Douglas fir. Experiments were conducted on four timber-arch models with different rise-to-span ratios under concentrated loads at mid-span and quarter-point locations. The structural responses, failure modes, and loading capacity of the timber arch specimens were obtained. The results show that the timber arches presented symmetric and antisymmetric deformation under mid-point and quarter-point loading conditions, respectively. The downward shifting of the neutral axis of the cross section was observed under mid-point loading condition, which contributes to higher loading capacity compared to that under quarter-point loading condition. The loading condition significantly affects the ultimate loads and the strain distribution in the cross section. Based on the design formula in current standards for timber structures, an equivalent beam-column method was introduced to estimate the loading capacity of the laminated timber arches under vertical concentrated loads. The moment amplification factor in the formula was compared and discussed, and the value provided in the National Design Specification for Wood Construction was recommended with acceptable accuracy.

The traditional support vector machine algorithm is not enough to classify single-stranded DNA molecules, so this paper proposes an improved threshold extraction algorithm based on collaborative filter for the classification of single-stranded DNA. Firstly, according to the different characteristic curves of the blocking current signals formed by the four bases (A, T, C, and T) that make up DNA molecules crossing the nanopore, the collaborative filter feature extraction algorithm with improved threshold is proposed. Then, the feature information is reconstructed and sent to the SVM classifier for training. Finally, the unfiltered, collaborative filter, improved threshold collaborative filter, and Bessel filter data are, respectively, extracted and sent to the SVM classifier for classification and comparison research. The experimental results show that the improved collaborative filter algorithm has higher accuracy in single-stranded DNA molecular classification.

Methicillin-resistant Staphylococcus aureus (MRSA) is considered as one of the most dangerous clinical pathogens. Biofilms forming ability of MRSA is also a major cause of drug resistance. Hence, it is in urgent need to develop novel antibacterial/antibiofilm drugs. Fascaplysin with a unique cationic five-ring coplanar backbone is emerging as a potential antibacterial compound. In this study, aiming at developing novel and more effective agents, a series of fascaplysin derivatives and their corresponding β-carboline precursors have been synthesized. Then their antibacterial/antibiofilm activity and mechanisms against MRSA were investigated for the first time. The results showed that most fascaplysins rather than β-carboline precursors exhibit superior antimicrobial activity against MRSA ATCC43300, demonstrating the important role of cationic five-ring coplanar backbone playing in antibacterial activity. Among them, 14 and 18 are the most potent compounds with MIC value of 0.098 μg/ml (10-fold lower than vancomycin), and 18 featuring the lowest toxicity. Subsequent mechanisms exploration indicates that 18 has relatively stronger ability to destroy bacterial cell wall and membrane, higher binding affinity to bacterial genomic DNA. Molecular docking study revealed that besides the key role of cationic five-ring coplanar backbone, introduction of N-aryl amide at 9-position of fascaplysin promoted the combination of compound 18 and DNA via additional π-π stacking and hydrogen bonding of the naphthyl group. Moreover, fascaplysins could inhibit MRSA biofilm formation in vitro and bacterial infection in vivo. All these results illustrate that fascaplysin derivative 18 is a strong and safe multi-target antibacterial agent, which makes it an attractive candidate for the treatment of MRSA and its biofilm infections.

Gemcitabine (GEM)-based chemotherapy is a commonly used treatment for pancreatic cancer. However, acquired drug resistance, a major problem in pancreatic cancer treatment, causes a reduction in the survival rate of patients with cancer. In this study, we attempted to reveal the molecular mechanism of GEM resistance. Our data showed that GEM treatment inhibits cell growth, induces apoptosis, and activates autophagy via the AMP-activated protein kinase (AMPK) pathway. The combination of GEM treatment and AMPK knockdown resulted in a dramatic increase of apoptosis and inhibition of autophagy. Additionally, inhibition of mammalian target of Rapamycin induced autophagy. Our findings show the potential therapeutic implications of the combined treatment with GEM and AMPK inhibitors for pancreatic cancer.

Three-phase cascaded inverter with leakage current reduction for the transformerless PV system is investigated in this paper. The common-mode loop model of the conventional three-phase cascaded H4 grid-connected inverter is established. The relationship among the leakage current, common-mode voltage, and differential mode voltage is analyzed. The inherent reason that the conventional cascaded H4 grid-connected inverter fails to reduce the leakage current is clarified. In order to solve the problem, a novel three-phase cascaded H5 grid-connected inverter and its modulation strategy are proposed. It can significantly reduce the leakage current. Finally, the performance tests of the cascaded H4 and H5 grid-connected inverters are carried out. The results verify the effectiveness of the proposed solution.

The mitochondrial genome (mitogenome) of Nothybus sumatranus is described in the present paper, representing the first mitogenome reported from the family Nothybidae. The nearly complete mitochondr...

Design and preparation of biomass derived heteroatom-doped hierarchical porous carbons with excellent capacitive performances draw extensive research attention for supercapacitors. Herein, 3D nitrogen and sulfur co-doped hierarchical porous carbon (NSHPC) derived from mung bean jelly with mung bean starch as carbon source and thiourea as both nitrogen source and sulfur source is successfully prepared. By virtue of manipulating the preparation method, the obtained NSHPC possesses a high specific surface area of 2420 m2 g-1 and a large total pore volume of 1.64 cm3 g-1. The NSHPC electrode displays a high specific capacitance of 330.2 F g−1 at the current density of 0.5 A g−1 and still maintains 66.2% of its original specific at the high current density of 20 A g−1 in three-electrode system. In addition, a symmetric device based on NSHPC electrodes delivers an energy density of 8.3 W h kg−1 at the power density of 101.6 W kg−1, and more than 70.6% of energy density is kept even under the high power density of 19.3 kW kg−1. This study provides a facile and efficient method of applying biomass as a precursor to obtain heteroatom-doped hierarchical porous carbons for high performance supercapacitors.

In this paper, the Mth-order lump solutions for the (2+1)-dimensional Kadomtsev–Petviashvili I equation are studied. Firstly, the Nth-order wronskian determinant solutions of the Hirota bilinear form of the (2+1)-dimensional Kadomtsev–Petviashvili I equation are given. Then, the 1st-order lump solution is obtained by making elementary transformations and taking limit to the 2nd-order wronskian determinant solution. Next, the 2nd-order lump and the 3rd-order lump solutions are also similarly derived. The dynamic properties and characteristics of these low-order lump solutions are presented by three-dimensional images and the corresponding contour plots. Finally, based on the character of Vandermond determinant, the determinant expression of the Mth-order lump solutions is constructed by making elementary transformations and taking limit to the 2Mth-order wronskian determinant solutions.

Proteases play important roles in all living organisms and also have important industrial applications. Family M12A metalloproteases, mainly found throughout the animal kingdom, belong to the metzincin protease family and are synthesized as inactive precursors. So far, only flavastacin and myroilysin, isolated from bacteria, were reported to be M12A proteases, whereas the classification of myroilysin is still unclear due to the lack of structural information. Here, we report the crystal structures of pro-myroilysin from bacterium Myroides sp. cslb8. The catalytic zinc ion of pro-myroilysin, at the bottom of a deep active site, is coordinated by three histidine residues in the conserved motif HEXXHXXGXXH; the cysteine residue in the pro-peptide coordinates the catalytic zinc ion and inhibits myroilysin activity. Structure comparisons revealed that myroilysin shares high similarity with the members of the M12A, M10A, and M10B families of metalloproteases. However, a unique “cap” structure tops the active site cleft in the structure of pro-myroilysin, and this “cap” structure does not exist in the above structure-reported subfamilies. Further structure-based sequence analysis revealed that myroilysin appears to belong to the M12A family, but pro-myroilysin uses a “cysteine switch” activation mechanism with a unique segment, including the conserved cysteine residue, whereas other reported M12A family proteases use an “aspartate switch” activation mechanism. Thus, our results suggest that myroilysin is a new bacterial member of the M12A family with an exceptional cysteine switch activation mechanism. Our results shed new light on the classification of the M12A family and may suggest a divergent evolution of the M12 family.

The dance fly Chelipoda sp. belongs to the subfamily Hemerodromiinae of Empididae. The mitogenome (GenBank accession number: MT396991) of Chelipoda sp. was sequenced, the first representative of the mitogenome of the subfamily. The nearly complete mitogenome is 14,976 bp totally, consisting of 13 protein-coding genes, 2 rRNAs, and 22 transfer RNAs. All genes have the similar locations and strands compared with that of other published species of Empididae. The nucleotide composition biases toward A and T, which together made up 77.2％of the entirety. Bayesian inference analysis strongly supported the monophyly of Empidoidea, Empididae and Dolichopodidae. The phylogenetic relationship within Empidoidea is as follows: (Dolichopodinae + Neurigoninae) + (((Empidinae + Hemerodromiinae) + (Trichopezinae + Oreogetoninae)) + Ocydromiinae) in this study.

A serralysin family protease (Serralysin-like protease B, SPB) with unique V-shaped thermostable property was isolated and identified from the Serratia marcescens FS14 by biochemical and molecular biological methods. It is the first time to report the isolation of a native serralysin family protease directly from Serratia species except the well-studied serralysin. SPB has an optimum pH at 8.0 and an optimum temperature at 37°C. It shows high proteolytic activities after pretreated at 4-50°C for 10min respectively and almost no detectable activity after pretreated at 60°C. Surprisingly, increasing activities were observed after pretreated at 70-90°C respectively. Further study revealed that the reason behind this phenomenon may be the self-digestion property of SPB with an optimum temperature around 60°C. This self-digestion property may expand the SPB future application in industry. The bioassay using the healthy cotton bollworm Helicoverpa armigera larvae demonstrated that the serralysin and SPB from FS14 are toxic to the H. armigera larvae. This result implied that FS14 strain and/or the SPB and serralysin in FS14 might have a potential application in insect control.

To prevent short-circuits between the upper and lower switches of power converters from over-current protection, the dead time is mandatory in the switching gating signal for voltage source converters. However, this results in many negative effects on system operations, such as output voltage and current distortions (e.g., increased level of fifth and seventh harmonics), zero-current-clamping phenomenon, and output fundamental-frequency voltage reduction. Many solutions have been presented to cope with this problem. First, the dead-time effect is analyzed by taking into account factors such as the zero-clamping phenomenon, voltage drops on diodes and transistors, and the parameters of inverter loads, as well as the parasitic nature of semiconductor switches. Second, the state-of-the-art dead-time compensation algorithms are presented in this paper. Third, the advantages and disadvantages of existing algorithms are discussed, together with the future trends of dead-time compensation algorithms. This article provides a complete scenario of dead-time compensation with control strategies for voltage source converters for researchers to identify suitable solutions based on demand and application.

Gemcitabine (GEM)-based chemotherapy is a commonly used treatment for pancreatic cancer. However, acquired drug resistance, a major problem in pancreatic cancer treatment, causes a reduction in the survival rate of patients with cancer. In this study, we attempted to reveal the molecular mechanism of GEM resistance. Our data showed that GEM treatment inhibits cell growth, induces apoptosis, and activates autophagy via the AMP-activated protein kinase (AMPK) pathway. The combination of GEM treatment and AMPK knockdown resulted in a dramatic increase of apoptosis and inhibition of autophagy. Additionally, inhibition of mammalian target of Rapamycin induced autophagy. Our findings show the potential therapeutic implications of the combined treatment with GEM and AMPK inhibitors for pancreatic cancer.

High pathologic tumor-node-metastasis (pTNM) stage grade or Fuhrman grade indicates poor oncological outcome in renal cell carcinoma (RCC). Early diagnosis and screening of these RCCs and adjust surgical planning accordingly are greatly beneficial to patients. Raman spectroscopy is a highly specific fingerprint spectrum on molecular level, pretty appropriate for label-free and noninvasive cancer diagnosis. In this work we established a Raman spectrum-based supporting vector machine (SVM) model to accurately ex vivo distinguish human renal tumor from normal tissues and fat with an accuracy of 92.89%. The model can also be used to determine tumor boundary, showing consistent results to pathological staining analysis. This method can be additionally used to accomplish the classification purposes of renal tumor subtypes and grades with an accuracy of 86.79% and 89.53%, respectively. Therefore, we prove that Raman spectroscopy has great potential in the rapid and accurate clinical diagnosis of renal cancers.

We investigate the mixed interaction solutions of the coupled nonlinear Schrödinger equations (CNLSE) through the Darboux transformation method. First of all, we derive the nonsingular localized wave solutions for two cases of CNLSE by the Darboux transformation method and matrix analysis method. Furthermore, we take a limit technique to deduce rogue waves and divide the rogue waves into four categories through analyzing their dynamic behaviors. Based on the obtained theorems, the Darboux transformations are presented to solve interaction solutions between distinct nonlinear waves. In this paper, we mainly study four types. Finally, the dynamic characteristics of the constructed these solutions are analyzed by sequences of interesting figures plotted with the help of Maple.

346 Background: Alterations in DNA damage repair (DDR) genes are associated with human tumorigenesis and may be as potential biomarkers for vascular endothelial growth factor (VEGF) tyrosine kinase inhibitor (TKI) therapy in renal cell carcinoma. However, biologic significance and relevance to TKI targeted therapy in metastatic RCC are unknown. Methods: Genomic data and treatment outcomes were retrospectively collected for patients with metastatic RCC. Tumor and germline DNA were subject to targeted next generation sequencing across 642 genes of interest, including 60 DDR genes. Patients were dichotomized according to underlying DDR gene alteration into (1) DDR gene alterations present (Mut DDR); (2) wildtype (WT) DDR gene alterations present (WT DDR). Association between DDR status and therapeutic benefit was investigated separately for and vascular endothelial growth factor (VEGF) tyrosine kinase inhibitor (TKI) therapy. Results: Mut DDR were detected in 17/40 patients (42.5%). The most frequently DDR altered genes were TP53. For patients with TKI treatment, Mut DDR status was associated with superior progression free survival (log-rank p = 0.048), but not with superior overall survival (log-rank p = 0.39); after adjusting for International Metastatic Renal Cell Carcinoma Database Consortium risks and extent of prior therapy, the HR for Mut DDR was 2.68 (95% CI: 0.96–7.46; p = 0.059). Conclusions: DDR alterations are recurrent genomic events in patients with advanced RCC and were mostly clonal in this cohort. Dysfunction events in these genes may affect outcome with TKI therapy in adanced RCC, and these hypothesis-generating results deserve further study.

We discuss modulation instability for the generalized nonlinear Schrödinger equation based on nonzero background wave frequency. First of all, we analyze the existence condition of modulation instability under different perturbed frequency. The influences of the background amplitude, background frequency and perturbed frequency on the modulation instability gain are researched, respectively. Also, we obtain the correspondences between several nonlinear excitations (Kuznetsov-Ma breather, general breather, rogue wave, bright soliton and plane wave) and modulation instability according to new parameters. Furthermore, by the Fourier transformation method, we perform spectrum analyses of the first-order and second-order rogue waves. The perturbed frequency of the rogue wave can affect the location and profile of the spectrum. And we find that the spectrum of the second-order rogue wave is jagged due to the collision of the rogue waves. These results would help us further understand the dynamics of rogue wave in complex systems.

We report a rare case of culture negative L4-L5 discitis and epidural abscess in an immunocompetent child who had dry cupping therapy performed to treat low back strain. The causative pathogen was identified as Stenotrophomonas maltophilia by shotgun metagenomic sequencing of spinal cord aspirate after more than one month of unsuccessful empirical treatment with 6 different antibiotics. The patient was successfully treated with Sulfamethoxazole-trimethoprim and minocycline. Cupping therapy is a very popular medical procedure widely used in China, but the potential risk for severe infections such as discitis and epidural abscess described in this case should be recognized. Keywords: Stenotrophomonas maltophilia, Discitis, Epidural abscess, Shotgun metagenomic sequencing, Dry cupping therapy

Background. Due to the redundant information contained in multichannel electroencephalogram (EEG) signals, the classification accuracy of brain-computer interface (BCI) systems may deteriorate to a large extent. Channel selection methods can help to remove task-independent electroencephalogram (EEG) signals and hence improve the performance of BCI systems. However, in different frequency bands, brain areas associated with motor imagery are not exactly the same, which will result in the inability of traditional channel selection methods to extract effective EEG features. New Method. To address the above problem, this paper proposes a novel method based on common spatial pattern- (CSP-) rank channel selection for multifrequency band EEG (CSP-R-MF). It combines the multiband signal decomposition filtering and the CSP-rank channel selection methods to select significant channels, and then linear discriminant analysis (LDA) was used to calculate the classification accuracy. Results. The results showed that our proposed CSP-R-MF method could significantly improve the average classification accuracy compared with the CSP-rank channel selection method.

The subgenus Empis (Xanthempis) is newly recorded from South Korea with the following two species: E. (X.) sesquata (Ito, 1961) and E. (X.) suhisp. n.A key to the known species ofXanthempisfrom Eastern Asia is presented. The distribution ofXanthempisin eastern Asia is briefly discussed.

Background Many upper respiratory pathogens cause similar symptoms. In China, routine molecular tests for upper respiratory pathogens are not widely performed and antibiotics abuse in treating upper respiratory tract infections (URTIs) is a major public health concern. Methods We performed qualitative real-time PCR tests to detect common upper respiratory tract pathogens including 9 viruses and 3 bacteria in 1221 nasopharyngeal swabs from patients with fever and influenza-like symptoms in a Chinese city. A quantitative real-time PCR was also performed to measure the bacterial density of the colonizing Streptococcus pneumoniae in these samples. Results We found very diverse pathogens including 81.7% viruses, 11.6% bacteria and 6.7% mixed viruses and bacteria. S. pneumoniae colonization was found in 8.0% of the cases but most of them had low bacterial density (Mean = 3.9 log cfu/ml). We also discovered an increase of S. pneumoniae colonization frequency (but not the density) in patients with detectable upper respiratory tract pathogens, in a pathogen variety-dependent manner. Conclusions Our study provided strong evidence against empiric antibiotic use for treating URTIs, and highlighted a strong need for improving the diagnostic capacity for URTIs by using more molecular testing in China.

Background Metagenomic sequencing has shown tremendous promise in solving difficult infectious diseases cases. In this study, we utilized this technology to help guide the care of a critically ill patient with severe pneumonia, fever of unknown origin, and subsequent encephalitis in the intensive care unit (ICU). Methods Shotgun metagenomic sequencing was performed on the patient’s blood, bronchoalveolar lavage (BAL), and cerebral spinal fluid by using an Illumina MiniSeq sequencer. Results. A high load of human adenovirus B55 (HAdV-B55), a highly pathogenic adenovirus associated with numerous recently reported outbreaks and deaths in China, was detected in both blood and BAL, which explained the severity of the condition. The patient was treated with intravenous ribavirin, which cleared the virus after 26 days. Metagenomic sequencing also helped diagnose an unexpected herpes simplex virus–1 encephalitis during hospitalization, which led to timely treatment. Conclusions. This was the first successful case utilizing metagenomic sequencing to guide diagnosis and treatment in the ICU setting in China. We have proven the concept that metagenomic sequencing can play an important role in determining clinical approaches and ultimately in improving patient outcomes. We also hope to share our successful treatment protocol for the severe pneumonia and viremia caused by HAdV-B55.

Safety requirements describe risk mitigations against failures that may cause catastrophic consequences on human life, environment and facilities. To be able to implement the correct risk mitigations, it is fundamental that safety requirements are defined based on the results issued from the safety analysis. In this paper, we introduce a heuristic approach to elicit safety requirements based on the knowledge about hazard's causes, hazard's sources and hazard's consequences (i.e. hazard's components) acquired during the safety analysis. The proposed approach is based on a Hazard Ontology that is used to structure the knowledge about the hazards identified during the safety analysis in order to make it available and accessible for requirements elicitation. We describe how this information can be used to elicit safety requirements, and provide a guidance to derive the safety requirements which are appropriate to deal with the hazards they mitigate.

Preliminary hazard analysis (PHA) is a key safetyconcerned activity to identify potential hazards. However, since various stakeholders will be involved in the identification process, a common understanding of the nature of hazards among stakeholders, such as what a hazard consists of and how to describe it without ambiguities, is of crucial importance to achieve the goal of PHA. In this work, we propose a hazard modeling language (HML) based on a domain ontology to facilitate the specification of identified hazards. In addition, we present an approach to guide the transformation from natural language hazard descriptions into the HML specification. Finally, an industrial PHA example is used to illustrate the usefulness of our work.

Hazard identification is an essential and demanding task for the development of safety-critical systems (SCSs). Current practices suffer from one or several drawbacks: 1) a common hazard conceptualization is missing and thereby ambiguities may arise and, 2) there is still a need to formalize the experience of analysts and lessons learned from previous system development. It should be done in a structured way to facilitate future reuse and, 3) some hazard identification techniques require well-known system behaviors represented by models, such as automata and sequence diagrams, to identify hazards. However, such models are typically susceptible to changes or even not available in early stages of the development process. In this paper, we propose an ontological approach to support hazard identification in the early stages of the development of SCSs. The approach aims to improve the completeness of hazard identification results and to avoid ambiguities. A robotic strolling assistant system is used to evaluate the proposed approach.

The hazard concept has been extensively used in the literature and defined in an informal way, which serves as a guidance on identifying the potential hazards during the development of safety-criti ...

The dance fly Trichoclinocera yixianensis Li et Yang belongs to the subfamily Clinocerinae of Empididae. The mitogenome of T. yixianensis was sequenced, the first representative of the mitogenome of the subfamily. The nearly complete mitogenome is 15,595 bp totally, consisting of 13 protein-coding genes, 2 rRNAs, and 22 transfer RNAs. All genes have the similar locations and strands with that of other published species of Empididae. The nucleotide composition biases toward A and T, which together made up 80.1% of the entirety. Bayesian inference analysis strongly supported the monophyly of Empididae and Dolichopodidae. It suggested that Empididae is the sister group to the clade of Dolichopodidae and Empidinae is the sister group to the clade of Clinocerinae + Trichopezinae.

The targeting protein of serine/threonine protein phosphatase 5 (PPP5C) has been reported to be present in various malignancies. However, its functional role in pancreatic cancer (PC) remains unknown. In the present study, the function of PPP5C in PC cells treated with the first-line drug gemcitabine (GEM) was investigated. Short hairpin (sh)RNA targeting PPP5C was constructed to knockdown PPP5C in PANC-1 cells. Cell cycle and apoptosis analyses were performed in order to investigate the mechanisms underlying the effects induced by PPP5C silencing combined with GEM treatment. Western blot analysis was applied to detect the expression of certain key regulators of cell apoptosis in PANC-1 cells treated with GEM. shRNA against PPP5C effectively suppressed the proliferation of PANC-1 cells treated with GEM. Additionally, cell cycle analysis indicated that PPP5C knockdown resulted in a higher number of PANC-1 cells treated with GEM in G0/G1 phase arrest. Knockdown of PPP5C increased the expression of associated apoptotic markers, including cleaved caspase 3, poly (ADP-ribose) polymerase and phosphorylated (p)-p53. In addition, the combination of treatment with GEM and PPP5C silencing significantly increased the apoptosis of PANC-1 cells by affecting the expression levels of p-c-Jun N-terminal kinases and p-p38. The present study suggests that PPP5C may be a potential target for the treatment of PC and that it may enhance the gemcitabine sensitivity of PC cells.

Internet market has become the main sales channel in the era changing rapidly. Consumers change their consumption concepts, resulting in difficulties of traditional physical form of packaging in meeting the contemporary people's shopping patterns and aesthetic interests; therefore, the packaging design of online shopping goods arises at this historic moment. The innovative packaging of online shopping goods is based on the promotion of the Internet market and the online virtual trading market, as well as targeting at global consumers. The fashion and the unique way of online shopping in the Internet era has become the new orientation and design basis for the packaging of online shopping items. Unlike the package design of traditional shopping market, the most important characteristic of the package of online shopping goods is that consumers are unable to get practical shopping experience. How to make it accurately and clearly convey the information to help consumers make the right purchase decision and successfully complete the online trading is the principle of the package design of online shopping goods.

The environment, where a safety critical system (SCS) operates, is an important source from which safety requirements of the SCS can originate. By treating the system under construction as a black box, the environment is typically documented as a number of assumptions, based on which a set of environmental safety requirements will be elicited. However, it is not a trivial task in practice to capture the environmental assumptions to elicit safety requirements. The lack of certain assumptions or too strict assumptions will either result in incomplete environmental safety requirements or waste many efforts on eliciting incorrect requirements. Moreover, the variety of operating environment for an SCS will further complicate the task, since the captured assumptions are at risk of invalidity, and consequently the elicited requirements need to be revisited to ensure safety has not been compromised by the change. This short paper presents an on-going work aiming to 1) systematically organize the knowledge of system operating environment and, 2) facilitate the elicitation of environmental safety requirements. We propose an ontological approach to achieve the objectives. In particular, we utilize conceptual ontologies to organize the environment knowledge in terms of relevant environment concepts, relations among them and axioms. Environmental assumptions are captured by instantiating the environment ontology. An ontological reasoning mechanism is also provided to support elicitation of safety requirements from the captured assumptions.