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This article proposes an integer ambiguity determination method based on Beidou system-reflectometry (Beidou-R) observations of the carrier phase at the B1I and B3I frequencies. To enhance the accuracy of sea surface height (SSH) estimation, this study introduces a parallel filtering algorithm and an adaptive iterative fusion algorithm, enabling data fusion based on the variance at B1I and B3I frequencies. To validate and evaluate the proposed method, a coastal experiment was conducted at the Shenxian River. In this experiment, reflected signals from GEO and IGSO satellites were collected. Data analysis reveals that the method is effective, demonstrating that the root mean square error (RMSE) of SSH achieves 2.85 cm and 2.89 cm for PRN 04 and PRN 33, respectively. Furthermore, the impact of the elevation angle on measurement accuracy is analyzed. This study aims to propose a method to enhance coastal sea surface height estimation, offering potential advancements in sea surface altimetry.

BackgroundIn 2013, a tuberculosis (TB) outbreak occurred in a middle school in Henan province of China. An outbreak survey was carried out in the school.ObjectivesThis study was undertaken to investigate the detection rate of TB cases and those with strong Mantoux positive (SMP), defined as tuberculin skin test (TST) indurations of 15mm or larger and/or blisters, necrosis or lymphangitis, and to identify their risk factors.MethodsThe TST, chest x-ray/radiography, and TB-suspicious symptoms interview were used to screen for TB cases. Their diagnosis was made by sputum smear microscopy, liquid culture, computed tomography (CT), and diagnostic therapy if necessary. We retrospectively analyzed the outbreak survey data of 4082 students and 278 staff in the school. Logistic regression models were used to identify the risk factors associated with SMP and TB disease.ResultsApproximately 3.55% of students and 16.55% of staff were SMP. SMP rate in students was significantly lower than that in staff (pConclusionSame dormitory-floor, same classroom, same teaching-floor and same teaching-building with the index case were all risk factors for both TB infection and disease for students in the outbreak, and the closer the contact was with the index case, the higher the risk was observed. Attention should also be paid to students with TST indurations

Recent research has demonstrated that characteristic gene selection based on gene expression data remains faced with considerable challenges. This is primarily because gene expression data are typically high dimensional, negative, non-sparse and noisy. However, existing methods for data analysis are able to cope with only some of these challenges. In this paper, we address all of these challenges with a unified method: nonnegative matrix factorization via the L2,1-norm (NMF-L2,1). While L2,1-norm minimization is applied to both the error function and the regularization term, our method is robust to outliers and noise in the data and generates sparse results. The application of our method to plant and tumor gene expression data demonstrates that NMF-L2,1 can extract more characteristic genes than other existing state-of-the-art methods.

Candida tropicalis is considered as the leading pathogen in nosocomial fungemia and hepatosplenic fungal infections in patients with cancer, particularly in leukemia. The yeast-filament transition is required for virulent infection by Candida. Several studies have explored the genome-wide transcription profile of Candida, however, no report on the transcriptional profile of C. tropicalis under yeast-filament transition has been published. In this study, the transcriptomes of three C. tropicalis isolates with different adhesion and biofilm formation abilities, identified in our previous studies, were analyzed in both the yeast and filament states using RNA-Seq. Differentially expressed genes were found for each isolate during the transition. A total of 115 genes were up- or down- regulated in the two hyphal-producing isolates (ZRCT 4 and ZRCT 45). Among these differentially expressed genes, only two were down-regulated during the yeast-filament transition. Furthermore, six filament-associated genes were up-regulated in the hyphae-producing isolates. According to Candida Hypha Growth Database established in this study, 331 hyphae- related genes were discovered in C. tropicalis. ALS1 and ALS3 were down-regulated and up-regulated, respectively, during filamentous growth of C. tropicalis. These findings proved a better understanding of gene expression dynamics during the yeast-filament transition in C. tropicalis.

In current molecular biology, it becomes more and more important to identify differentially expressed genes closely correlated with a key biological process from gene expression data. In this paper, based on the Schatten p-norm and Lp-norm, a novel p-norm robust feature extraction method is proposed to identify the differentially expressed genes. In our method, the Schatten p-norm is used as the regularization function to obtain a low-rank matrix and the Lp-norm is taken as the error function to improve the robustness to outliers in the gene expression data. The results on simulation data show that our method can obtain higher identification accuracies than the competitive methods. Numerous experiments on real gene expression data sets demonstrate that our method can identify more differentially expressed genes than the others. Moreover, we confirmed that the identified genes are closely correlated with the corresponding gene expression data.

In terms of making genes expression data more interpretable and comprehensible, there exists a significant superiority on sparse methods. Many sparse methods, such as penalized matrix decomposition (PMD) and sparse principal component analysis (SPCA), have been applied to extract plants core genes. Supervised algorithms, especially the support vector machine-recursive feature elimination (SVM-RFE) method, always have good performance in gene selection. In this paper, we draw into class information via the total scatter matrix and put forward a class-information-based penalized matrix decomposition (CIPMD) method to improve the gene identification performance of PMD-based method. Firstly, the total scatter matrix is obtained based on different samples of the gene expression data. Secondly, a new data matrix is constructed by decomposing the total scatter matrix. Thirdly, the new data matrix is decomposed by PMD to obtain the sparse eigensamples. Finally, the core genes are identified according to the nonzero entries in eigensamples. The results on simulation data show that CIPMD method can reach higher identification accuracies than the conventional gene identification methods. Moreover, the results on real gene expression data demonstrate that CIPMD method can identify more core genes closely related to the abiotic stresses than the other methods.

Galectins are a lectin family characterized by a conserved sequence motif in the carbohydrate recognition domain, which preferential binds to galactosyl moieties. However, few studies about the biological roles of galectins in invertebrates have been reported except for the galectin (CvGal1) from the eastern oyster Crassostrea virginica. Furthermore, galectins have been described in only a few crustacean species, and no functional studies have been reported so far. In this study, we identified and functionally characterized a galectin from the kuruma shrimp Marsupenaeus japonicus, which we designated MjGal. Upon Vibrio anguillarum challenge, expression of MjGal was up-regulated mostly in hemocytes and hepatopancreas, and the protein bound to both Gram-positive and Gram-negative bacteria through the recognition of lipoteichoic acid (LTA) or lipopolysaccharide (LPS), respectively. By also binding to the shrimp hemocyte surface, MjGal functions as an opsonin for microbial pathogens, promoting their phagocytosis. Further, as shown by RNA interference, MjGal participates in clearance of bacteria from circulation, and thereby contributes to the shrimp's immune defense against infectious challenge. Elucidation of functional and mechanistic aspects of shrimp immunity will enable the development of novel strategies for intervention in infectious diseases currently affecting the shrimp farming industry worldwide.

The sparse representation-based classification (SRC) has been proven to be a robust face recognition method. However, its computational complexity is very high due to solving a complex l(1)-minimization problem. To improve the calculation efficiency, we propose a novel face recognition method, called sparse representation-based classification on k-nearest subspace (SRC-KNS). Our method first exploits the distance between the test image and the subspace of each individual class to determine the k nearest subspaces and then performs SRC on the k selected classes. Actually, SRC-KNS is able to reduce the scale of the sparse representation problem greatly and the computation to determine the k nearest subspaces is quite simple. Therefore, SRC-KNS has a much lower computational complexity than the original SRC. In order to well recognize the occluded face images, we propose the modular SRC-KNS. For this modular method, face images are partitioned into a number of blocks first and then we propose an indicator to remove the contaminated blocks and choose the k nearest subspaces. Finally, SRC is used to classify the occluded test sample in the new feature space. Compared to the approach used in the original SRC work, our modular SRC-KNS can greatly reduce the computational load. A number of face recognition experiments show that our methods have five times speed-up at least compared to the original SRC, while achieving comparable or even better recognition rates.

Nearest subspace (NS) classification based on linear regression technique is a very straightforward and efficient method for face recognition. A recently developed NS method, namely the linear regression-based classification (LRC), uses downsampled face images as features to perform face recognition. The basic assumption behind this kind method is that samples from a certain class lie on their own class-specific subspace. Since there are only few training samples for each individual class, which will cause the small sample size (SSS) problem, this problem gives rise to misclassification of previous NS methods. In this paper, we propose two novel LRC methods using the idea that every class-specific subspace has its unique basis vectors. Thus, we consider that each class-specific subspace is spanned by two kinds of basis vectors which are the common basis vectors shared by many classes and the class-specific basis vectors owned by one class only. Based on this concept, two classification methods, namely robust LRC 1 and 2 (RLRC 1 and 2), are given to achieve more robust face recognition. Unlike some previous methods which need to extract class-specific basis vectors, the proposed methods are developed merely based on the existence of the class-specific basis vectors but without actually calculating them. Experiments on three well known face databases demonstrate very good performance of the new methods compared with other state-of-the-art methods.

Conventional gene selection methods based on principal component analysis (PCA) use only the first principal component (PC) of PCA or sparse PCA to select characteristic genes. These methods indeed assume that the first PC plays a dominant role in gene selection. However, in a number of cases this assumption is not satisfied, so the conventional PCA-based methods usually provide poor selection results. In order to improve the performance of the PCA-based gene selection method, we put forward the gene selection method via weighting PCs by singular values (WPCS). Because different PCs have different importance, the singular values are exploited as the weights to represent the influence on gene selection of different PCs. The ROC curves and AUC statistics on artificial data show that our method outperforms the state-of-the-art methods. Moreover, experimental results on real gene expression data sets show that our method can extract more characteristic genes in response to abiotic stresses than conventional gene selection methods.

Plants and invertebrates can suppress viral infection through RNA silencing, mediated by RNA-induced silencing complex (RISC). Trans-activation response RNA-binding protein (TRBP), consisting of three double-stranded RNA-binding domains, is a component of the RISC. In our previous paper, a TRBP homologue in Fenneropenaeus chinensis (Fc-TRBP) was reported to directly bind to eukaryotic initiation factor 6 (Fc-eIF6). In this study, we further characterized the function of TRBP and the involvement of TRBP and eIF6 in antiviral RNA interference (RNAi) pathway of shrimp. The double-stranded RNA binding domains (dsRBDs) B and C of the TRBP from Marsupenaeus japonicus (Mj-TRBP) were found to mediate the interaction of TRBP and eIF6. Gel-shift assays revealed that the N-terminal of Mj-TRBP dsRBD strongly binds to double-stranded RNA (dsRNA) and that the homodimer of the TRBP mediated by the C-terminal dsRBD increases the affinity to dsRNA. RNAi against either Mj-TRBP or Mj-eIF6 impairs the dsRNA-induced sequence-specific RNAi pathway and facilitates the proliferation of white spot syndrome virus (WSSV). These results further proved the important roles of TRBP and eIF6 in the antiviral response of shrimp.

20-hydroxyecdysone (20E) and juvenile hormone (JH) signaling pathways interact to mediate insect development, but the mechanism of this interaction is poorly understood. Here, a calponin homologue domain (Chd) containing protein (HaCal) is reported to play a key role in the cross talk between 20E and JH signaling by varying its phosphorylation. Chd is known as an actin binding domain present in many proteins including some signaling proteins. Using an epidermal cell line (HaEpi), HaCal was found to be up-regulated by either 20E or the JH analog methoprene (JHA). 20E induced rapid phosphorylation of HaCal whereas no phosphorylation occurred with JHA. HaCal could be quickly translocated into the nuclei through 20E or JH signaling but interacted with USP1 only under the mediation of JHA. Knockdown of HaCal by RNAi blocked the 20E inducibility of USP1, PKC and HR3, and also blocked the JHA inducibility of USP1, PKC and JHi. After gene silencing of HaCal by ingestion of dsHaCal expressed by Escherichia coli, the larval development was arrested and the gene expression of USP1, PKC, HR3 and JHi were blocked. These composite data suggest that HaCal plays roles in hormonal signaling by quickly transferring into nucleus to function as a phosphorylated form in the 20E pathway and as a non-phosphorylated form interacting with USP1 in the JH pathway to facilitate 20E or JH signaling cascade, in short, by switching its phosphorylation status to regulate insect development.

When an insect molts, old cuticle on the outside of the integument is shed by apolysis and a new cuticle is formed under the old one. This process is completed by the epidermal cells which are controlled by 20-hydroxyecdysone (20E) and juvenile hormone. To understand the molecular mechanisms of integument remolding and hormonal regulation on the gene expression, an epidermal cell line from the 5th instar larval integument of Helicoverpa armigera was established and named HaEpi. The cell line has been cultured continuously for 82 passages beginning on June 30, 2005 until now. Cell doubling time was 64 h. The chromosomes were granular and the chromosome mode was from 70 to 76. Collagenase I was used to detach the cells from the flask bottom. Non-self pathogen AcMNPV induced the cells to apoptosis. The cell line was proved to be an epidermal cell line based on its unique gene expression pattern. It responded to 20E and the non-steroidal ecdysone agonist RH-2485. Its gene expression could be knocked down using RNA interference. Various genes in the cell line were investigated based on their response to 20E. This new cell line represents a platform for investigating the 20E signaling transduction pathway, the immune response mechanism in lepidopteran epidermis and interactions of the genes.

Recent research has demonstrated that characteristic gene selection based on gene expression data remains faced with considerable challenges. This is primarily because gene expression data are typically high dimensional, negative, non-sparse and noisy. However, existing methods for data analysis are able to cope with only some of these challenges. In this paper, we address all of these challenges with a unified method: nonnegative matrix factorization via the L2,1-norm (NMF-L2,1). While L2,1-norm minimization is applied to both the error function and the regularization term, our method is robust to outliers and noise in the data and generates sparse results. The application of our method to plant and tumor gene expression data demonstrates that NMF-L2,1 can extract more characteristic genes than other existing state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Galectins are a lectin family characterized by a conserved sequence motif in the carbohydrate recognition domain, which preferential binds to galactosyl moieties. However, few studies about the biological roles of galectins in invertebrates have been reported except for the galectin (CvGal1) from the eastern oyster Crassostrea virginica. Furthermore, galectins have been described in only a few crustacean species, and no functional studies have been reported so far. In this study, we identified and functionally characterized a galectin from the kuruma shrimp Marsupenaeus japonicus, which we designated MjGal. Upon Vibrio anguillarum challenge, expression of MjGal was up-regulated mostly in hemocytes and hepatopancreas, and the protein bound to both Gram-positive and Gram-negative bacteria through the recognition of lipoteichoic acid (LTA) or lipopolysaccharide (LPS), respectively. By also binding to the shrimp hemocyte surface, MjGal functions as an opsonin for microbial pathogens, promoting their phagocytosis. Further, as shown by RNA interference, MjGal participates in clearance of bacteria from circulation, and thereby contributes to the shrimp’s immune defense against infectious challenge. Elucidation of functional and mechanistic aspects of shrimp immunity will enable the development of novel strategies for intervention in infectious diseases currently affecting the shrimp farming industry worldwide. [ABSTRACT FROM AUTHOR]

Pattern recognition receptors (PPRs) are part of the initial step of a host defense against pathogens in detecting pathogen-associated molecular patterns. However, determinants of the specificity of this recognition by innate immune molecules of invertebrates remain largely unknown. In this study, we investigated the potential involvement of an invertebrate PRR C-type lectin in the antimicrobial response of the crustacean Eriocheir sinensis. Based on the initial expressed sequence tags (EST) of a hepatopancreatic cDNA library, the full-length EsLecF cDNA was cloned and determined to contain a 477-bp open reading frame encoding a putative 158-amino-acid protein. A comparison with other reported invertebrate and vertebrate C-type lectin superfamily sequences revealed the presence of a common carbohydrate recognition domain (CRD). EsLecF transcripts in E. sinensis were mainly detected in the hepatopancreas and were inducible by a lipopolysaccharide (LPS) injection. The recombinant EsLecF (rEsLecF) protein produced via a prokaryotic expression system and affinity chromatography was found to have a wide spectrum of binding activities towards various microorganisms, and its microbial-binding activity was calcium-independent. Moreover, the binding of rEsLecF induced the aggregation of microbial pathogens. Results of the microorganism growth inhibitory assay and antibacterial assay revealed capabilities of rEsLecF in suppressing microorganism growth and directly killing bacteria, respectively. Furthermore, rEsLecF could enhance cellular encapsulation in vitro. Collectively, the findings presented here demonstrated the successful isolation of a novel C-type lectin in a crustacean and highlighted its critical role in the innate immunity of an invertebrate. [ABSTRACT FROM AUTHOR]

Pattern recognition receptors (PPRs) are part of the initial step of a host defense against pathogens in detecting pathogen-associated molecular patterns. However, determinants of the specificity of this recognition by innate immune molecules of invertebrates remain largely unknown. In this study, we investigated the potential involvement of an invertebrate PRR C-type lectin in the antimicrobial response of the crustacean Eriocheir sinensis. Based on the initial expressed sequence tags (EST) of a hepatopancreatic cDNA library, the full-length EsLecF cDNA was cloned and determined to contain a 477-bp open reading frame encoding a putative 158-amino-acid protein. A comparison with other reported invertebrate and vertebrate C-type lectin superfamily sequences revealed the presence of a common carbohydrate recognition domain (CRD). EsLecF transcripts in E. sinensis were mainly detected in the hepatopancreas and were inducible by a lipopolysaccharide (LPS) injection. The recombinant EsLecF (rEsLecF) protein produced via a prokaryotic expression system and affinity chromatography was found to have a wide spectrum of binding activities towards various microorganisms, and its microbial-binding activity was calcium-independent. Moreover, the binding of rEsLecF induced the aggregation of microbial pathogens. Results of the microorganism growth inhibitory assay and antibacterial assay revealed capabilities of rEsLecF in suppressing microorganism growth and directly killing bacteria, respectively. Furthermore, rEsLecF could enhance cellular encapsulation in vitro. Collectively, the findings presented here demonstrated the successful isolation of a novel C-type lectin in a crustacean and highlighted its critical role in the innate immunity of an invertebrate. [ABSTRACT FROM AUTHOR]

Whey acidic proteins (WAP) belong to a large gene family of antibacterial peptides, which are critical in the host immune response against microbial invasion. The common feature of these proteins is a single WAP domain maintained by at least one four-disulfide core (4-DSC) structure rich in cysteine residues. In this study, a double WAP domain (DWD)-containing protein, Es-DWD1, was first cloned from the Chinese mitten crab (Eriocheir sinensis). The full-length Es-DWD1cDNA was 1193 bp, including a 411 bp open reading frame (ORF) encoding 136 amino acids with a signal peptide of 22 amino acids in the N-terminus. A comparison with other reported invertebrate and vertebrate sequences revealed the presence of WAP domains characteristic of WAP superfamilies. As determined by quantitative real-time RT-PCR, Es-DWD1 transcripts were ubiquitously expressed in all tissues, but it was up-regulated in hemocytes post-challenge with pathogen-associated molecular patterns (PAMPs). The mature recombinant Es-DWD1 (rEs-DWD1) protein exhibited different binding activities to bacteria and fungus. Moreover, rEs-DWD1 could exert agglutination activities against Bacillus subtilis and Pichia pastoris and demonstrated inhibitory activities against the growth of Staphylococcus aureus, Aeromonas hydrophila and P. pastoris. Furthermore, rEs-DWD1 showed a specific protease inhibitory activity in B. subtilis. Coating of rEs-DWD1 onto agarose beads enhanced encapsulation of the beads by crab hemocytes. Collectively, the results suggest that Es-DWD1 is a double WAP domain containing protein with antimicrobial and proteinase inhibitory activities, which play significant roles in the immunity of crustaceans. [ABSTRACT FROM AUTHOR]