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Stroke classification for online handwriting and sketches, aimed at grouping strokes into different semantic categories, has drawn considerable attention due to its wide applications. This task is challenging since individual strokes look similar and are easily confused with each other. The key is to consider both the individual strokes and the contextual information jointly for making prediction. Previous methods are insufficient in modeling and exploiting complex contextual information of strokes. To overcome this limitation, we propose a Transformer-based model for Online Handwriting and Sketches (T-OHS), with novel relation encoding schemes to take advantage of temporal and spatial information in stroke sequence. Particularly, we introduce a coarse-to-fine hierarchical encoding approach based on the polar coordinate system for precisely modeling spatial relations between strokes. Experiments on three types of handwriting data, including online handwritten documents, diagrams, and sketches, demonstrate that our method is universal and provides state-of-the-art performance. • We propose a novel stroke classification method for online handwriting and sketches. • We design an effective encoding scheme to represent the spatial relations among strokes. • Extensive experiments demonstrate that our method is universal and provides the SOTA performance. [ABSTRACT FROM AUTHOR]

Polarization and phase manipulations have gained widespread applications across various fields. The emergence of metasurface provides a new platform for the manipulation of electromagnetic waves. However, most metasurfaces are limited to modulating only one single property. Here, a coding metasurface that achieves 1‐bit phase manipulations of both co‐polarized and cross‐polarized reflected waves for linear and circular polarization wave excitations. Notably, the proposed metasurface enables co‐polarized 1‐bit phase responses for incident electric fields with arbitrary orientations and spin directions. The simulated results demonstrate an operating efficiency over −1.7 dB in the frequency range from 7 to 11.1 GHz, with a relative bandwidth of 45.3%. Furthermore, the introduction of space‐polarization coding strategies facilitates the beam and polarization manipulations. To verify the feasibility of the coding metasurface, a sample and conduct experiments are fabricated, revealing good agreement between the simulations and measurements. These findings hold significant promise for the advancement of radar, imaging, and wireless communication systems, with potential applications in various domains. [ABSTRACT FROM AUTHOR]

• We illustrate a novel prototype-based methodology to tackle the problem of online semi-supervised learning (OSSL). • Two effective strategies based on clustering assumption are incorporated into the learning process of unlabeled data. • An online modulation technique considers how to combine supervised learning criterion with unsupervised learning criterion. • Compared to previous OSSL approaches, the proposed algorithm achieves better classification performance with lower computational cost. Online semi-supervised learning (OSSL) is a learning paradigm simulating human learning, in which the data appear in a sequential manner with a mixture of both labeled and unlabeled samples. Despite the recent advances, there are still many unsolved problems in this area. In this paper, we propose a novel OSSL method based on learning vector quantization (LVQ). LVQ classifiers, which represent the data of each class by a set of prototypes, have found their usage in a wide range of pattern recognition problems and can be naturally adapted to the online scenario by updating the prototypes with stochastic gradient optimization. However, most of the existing LVQ algorithms were designed for supervised classification. To extract useful information from unlabeled data, we propose two simple and computationally efficient methods based on clustering assumption. To be specific, we use the maximum conditional likelihood criterion for updating prototypes when data sample is labeled, and the Gaussian mixture clustering criterion or neural gas clustering criterion for adjusting prototypes when data sample is unlabeled. These two criteria are utilized alternatively according to the availability of label information to make full use of both supervised and unsupervised data to boost the performance. By extensive experiments, we show that the proposed method exhibits higher accuracy compared with the baseline methods and graph-based methods and is much more efficient than graph-based methods in both training and test time. [ABSTRACT FROM AUTHOR]

• We propose a dynamic stroke classification approach, named DyGAT, for online handwritten documents and sketches. Different from previous methods, it can make real-time prediction during writers' writing process. • DyGAT is featured by a novel graph construction algorithm, which enables graph neural networks to better exploit the contextual information under the time constraint. • To evaluate the effectiveness and generality of DyGAT, we apply it to sketch semantic segmentation, document layout analysis, and diagram recognition. Extensive experiments have been conducted to analyze our method and demonstrate its superiority. Online handwriting is widely used in human-machine interface, education, office automation, and so on. Stroke classification for online handwritten documents and sketches aims to divide strokes into several semantic categories and is a necessary step for document recognition and understanding. Previous methods are essentially static in that they have to wait for the user to finish the whole sketch before making prediction. However, in practice, the more user-friendly way is to make real-time prediction as the user is writing. In this paper, we introduce Dynamic Graph ATtention network (DyGAT) to solve the dynamic stroke classification problem. The core of our method is to formalize a document/sketch into a multi-feature graph, in which nodes represent strokes, edges represent the relationships between strokes, and multiple nodes are applied to one stroke to control the information flow. The proposed method is general and is applicable to online handwritten data of many types. We conduct experiments on popular public datasets to perform sketch semantic segmentation, document layout analysis and diagram recognition, and experimental results show competitive performance. Particularly, the proposed method achieves stroke classification accuracies which are only slightly lower than those of static classification. [ABSTRACT FROM AUTHOR]

Seed reserves play vital roles in seed germination and seedling growth and their variation may be related to various environment factors, plant traits and phylogenetic history. Here, the evolutionary correlation associated with seed mass and altitude and carbon (C), nitrogen (N) and phosphorus (P) allocation of seeds among 253 alpine herbaceous plants was tested. In this study, phylogeny had strong limitations on nutrient allocation of seeds across species, and species from younger phylogenetic groups tended to have higher N and P contents, which might be considered as the evolutionary selection of seed plants. Higher seed N and P content would help seedlings to gain more survival chance and stronger competitive capacity, and their progeny would be more likely to be preserved. When phylogeny was considered, altitude only had a significant positive effect on P content, but the negative effects on seed mass were all expressed. The independent effects of altitude and seed mass suggest that the nutrient allocation of seeds might be affected by both environment and plant traits. In addition, altitude and seed mass displayed partial overlapping effects on nutrient allocation of seeds. The negative effects of seed mass were affected slightly by altitude, whereas altitude only had a significant positive effect on P content when seed mass was controlled. Above all, seed P content showed obvious and general correlations with seed mass, altitude and age of clade, which indicated that higher seed P content might be an adaptive selection of species associated with growth and survival of progeny. [ABSTRACT FROM AUTHOR]

Series of Sr 2 Fe (1+ x ) MoO 6 ( x = 0, 0.03, 0.05, 0.08) ceramics have been synthesized by introducing metal Fe at grain boundaries. The increasing of Fe segregation changes the Fe/Mo anti-site defect (ASD) and decreases grain boundary (GB) strength significantly. Fe/Mo ASD contributes to low-field magnetoresistance (LFMR) negatively, but GB positively. When x ≤ 0.03, the ASD content of the maternal Sr 2 FeMoO 6 (10%, x = 0) decreases to 8% ( x = 0.03), which compensates the lowering of GB strength partially, and hence a slightly improved LFMR behavior is observed. However, when x ≥ 0.03 ( x = 0.05, 0.08), Fe impurity bring about heavy ASD content and decreasing GB strength, so the LFMR property is suppressed greatly. The magnetoresistance behavior has been explored by a fitting model further. We believe that, our work may provide a facile and effective strategy for adjusting magnetoresistance response by tuning B-site ordering and GB strength of the double perovskite. [ABSTRACT FROM AUTHOR]

In this paper, we propose an adaptive spatial pooling method for enhancing the discriminability of feature representation for image classification. The core idea is to adopt a spatial distribution matrix to define how the image patches are pooled together. By formulating the pooling distribution learning and classifier training jointly, our method can extract multiple spatial layouts of arbitrary shapes rather than regular rectangular regions. By proper mathematical transformation, the distributions can be learned via a boosting-like algorithm, which improves the efficiency of learning especially for large distribution matrices. Further, our method allows category-specific pooling operations to take advantage of the different spatial layouts of different categories. Experimental results on three benchmark datasets UIUC-Sports, 21-Land-Use and Scene 15 demonstrate the effectiveness of our method. [ABSTRACT FROM AUTHOR]

Backgrounds: To preliminary evaluate the application of novel SaCoVLM video laryngeal mask -guided intubation for anesthetized children. Methods: One hundred twenty-four children with microtia (ages 5-15 years,) who required general intubation anaesthesia, were enrolled in the study. After induction of general anesthesia,guided tracheal intubation under direct vision of the SaCoVLM was performed. Our primary outcome was first-pass success rate of guided tracheal tube placement. Secondary outcome included glottic visualization grades, the first-attempt success rate of LMA placement, the time for LMA placement and time to endotracheal intubation as well as the time for LMA removal after successful intubation, the fiberoptic grade of laryngeal view, the baseline and postinduction hemodynamic parameters were also recorded,and the incidence 24 h complications after operation. Results: The first-pass success rate of guided tracheal tube placement was 91.1% (95%CI = 1.04–1.14), the status of glottic visualization was classified: grade 1 in 27cases, grade 2 in 36 cases, grade 3 in 41 cases and grade 4 in 20 cases. The first success rate of LMA placement was 92.7% (95%CI = 1.03–1.13), the time for LMA insertion was 15.7 (±9.1) s, intubation time was 30.9 (±17.6) s and withdrawl time was 24.9 (±9.3) s. The incidence of postoperative sore throat at 2 h was 29%, and 16.1% at 24 h, without dysphagia and hypoxia. Conclusion: The SaCoVLM video laryngeal mask-guided intubation is feasible in children, with a high success rate, could be a new promising device to guide intubation in airway management. Trial registration: This study was approved by the University's Institutional Review Board and written informed consent was obtained from all subjects participating in the trial. The trial was registered prior to patient enrollment at clinicaltrials.gov (ChiCTR2200061481, http://www.chictr.org.cn. Principal investigator: Juan Zhi; Date of registration: 26/06/2022. [ABSTRACT FROM AUTHOR]

Abstract: Semi-Markov conditional random fields (semi-CRFs) are usually trained with maximum a posteriori (MAP) criterion which adopts the 0/1 cost for measuring the loss of misclassification. In this paper, based on our previous work on handwritten Chinese/Japanese text recognition (HCTR) using semi-CRFs, we propose an alternative parameter learning method by minimizing the risk on the training set, which has unequal misclassification costs depending on the hypothesis and the ground-truth. Based on this framework, three non-uniform cost functions are compared with the conventional 0/1 cost, and training data selection is incorporated to reduce the computational complexity. In experiments of online handwriting recognition on databases CASIA-OLHWDB and TUAT Kondate, we compared the performances of the proposed method with several widely used learning criteria, including conditional log-likelihood (CLL), softmax-margin (SMM), minimum classification error (MCE), large-margin MCE (LM-MCE) and max-margin (MM). On the test set (online handwritten texts) of ICDAR 2011 Chinese handwriting recognition competition, the proposed method outperforms the best system in competition. [Copyright &y& Elsevier]

Abstract: Classical swine fever (CSF) caused by virulent strains of classical swine fever virus (CSFV) is a haemorrhagic disease of pigs, characterized by disseminated intravascular coagulation, thrombocytopenia and immunosuppression. The cell adhesion molecule, integrin β3, plays a central role in maintaining and regulating vascular permeability. In view of the haemorrhagic pathology of the disease, the effect of CSFV infection on integrin β3 expression was investigated using the swine umbilical vein endothelial cell (SUVEC) line, in conjunction with quantitative PCR and Western blotting techniques. Following infection, the expression levels of integrin β3 were significantly up-regulated along with corresponding transcription levels. The infected endothelial cells adhered onto immobilized extracellular matrix (ECM) with more extensive spreading than that of the control, and such interaction was strongly inhibited by an anti-integrin β3 monoclonal antibody (mAb). This study revealed the up-regulation of integrin β3 in vascular endothelial cells by CSFV infection, and cell adhesion molecules of this kind possibly play an important role in the changes of haemostatic balance in haemorrhagic pathology of CSF. [Copyright &y& Elsevier]

Abstract: The present study was designed to examine whether photoperiod alone was effective to induce seasonal regulations in physiology in root voles (Microtus oeconomus) from the Qinghai–Tibetan plateau noted for its extreme cold environment. Root voles were randomly assigned into either long photoperiod (LD; 16L:8D) or short photoperiod (SD; 8L:16D) for 4 weeks at constant temperature (20 °C). At the end of acclimation, SD voles showed lower body mass and body fat coupled with higher energy intake than LD voles. SD greatly enhanced thermogenic capacities in root voles, as indicated by elevated basal metabolic rate (BMR), nonshivering thermogenesis (NST), mitochondrial protein content and uncoupling protein-1 (UCP1) content in brown adipose tissue (BAT). Although no variations in serum leptin levels were found between SD and LD voles, serum leptin levels were positively correlated with body mass and body fat mass, and negatively correlated with energy intake and UCP1 content in BAT, respectively. To summarize, SD alone is effective in inducing higher thermogenic capacities and energy intake coupled with lower body mass and body fat mass in root voles. Leptin is potentially involved in the photoperiod induced body mass regulation and thermogenesis in root voles. [Copyright &y& Elsevier]

• A framework for joint text/non-text stroke classification and text line grouping in online handwritten documents is proposed. • Stroke classification and text line grouping problems are formulated as node classification/clustering problems in graph. • An edge pooling attention network (EPAT) is proposed to efficiently aggregate information of nodes and edges. • Superior performance of both stroke classification and text line grouping is achieved on public datasets. Stroke classification and text line grouping are important tasks in online handwritten document segmentation. In the past, the two tasks were usually performed using different models which are trained independently and perform sequentially. This cannot optimize the integration of contextual information and the system may suffer from error accumulation in stroke classification. In this paper, we propose a method for joint text/non-text stroke classification and text line grouping in online handwritten documents using attention based graph neural network. In our framework, the stroke classification and text line grouping problems are formulated as node classification and node clustering problems in a relational graph, which is constructed based on the temporal and spatial relationship between strokes. We propose a new graph network architecture, called edge pooling attention network (EPAT) to efficiently aggregate information between the features of neighboring nodes and edges. The proposed model is trained by multi-task learning with cross entropy loss for node classification and distance metric loss for node clustering. In experiments on two online handwritten document datasets IAMOnDo and Kondate, the proposed method is demonstrated effective, yielding superior performance in both stroke classification and text line grouping. [ABSTRACT FROM AUTHOR]

Objectives: The treatment of refractory and recurrent acute myeloid leukaemia (AML) is still a challenge with poor response rates and short survival times. In an attempt to solve this problem, we constructed a tandem bispecific chimeric antigen receptor (CAR) targeting CD123 and C‐type lectin‐like molecule 1 (CLL‐1), two different AML antigens, and verified its cytotoxic effects in vitro. Methods: We established and cultured K562 cell lines expressing both CD123 and CLL1 antigens. Single‐target CAR‐T cells specific to CD123 and CLL1 were engineered, alongside tandem CD123/CLL1 bispecific CAR‐T cells. Flow cytometry was used to determine cell phenotypes, transfection efficiencies, cytokine release, and CAR‐T‐cell proliferation, and an lactate dehydrogenase assay was used to detect the cytotoxicity of CD123/CLL‐1 bispecific tandem CAR‐T cells in vitro. Results: Two types of tandem CAR‐T cells exhibited significant killing effects on CLL‐1 + CD123+ leukaemia cell lines and primary AML tumour cells. The killing efficiency of tandem CAR‐T cells in the case of single antigen expression is comparable to that of single target CAR‐T cells. When faced with dual target tumour cells, dual target CAR‐T cells significantly surpass single target CAR‐T cells. CD123/CLL‐1 CAR‐T cells in tandem targeted and killed CD123‐ and CLL‐1‐positive leukaemia cell lines and released a large number of cytokines. Conclusions: CD123/CLL‐1 CAR‐T cells in tandem can simultaneously target CD123 and CLL‐1 on AML cells, demonstrating a significant ability to kill single antigens and multi‐target tumour cells. This suggests that CD123/CLL‐1 CAR‐T cells exhibit significant advantages in the expression of multiple antigens in a wide range of target cells, which may help overcome the challenges posed by tumour heterogeneity and evasion mechanisms. [ABSTRACT FROM AUTHOR]

Recognition of handwritten mathematical expressions (MEs) is an important problem that has wide applications in practice. Handwritten ME recognition is challenging due to the variety of writing styles and ME formats. As a result, recognizers trained by optimizing the traditional supervision loss do not perform satisfactorily. To improve the robustness of the recognizer with respect to writing styles, in this work, we propose a novel paired adversarial learning method to learn semantic-invariant features. Specifically, our proposed model, named PAL-v2, consists of an attention-based recognizer and a discriminator. During training, handwritten MEs and their printed templates are fed into PAL-v2 simultaneously. The attention-based recognizer is trained to learn semantic-invariant features with the guide of the discriminator. Moreover, we adopt a convolutional decoder to alleviate the vanishing and exploding gradient problems of RNN-based decoder, and further, improve the coverage of decoding with a novel attention method. We conducted extensive experiments on the CROHME dataset to demonstrate the effectiveness of each part of the method and achieved state-of-the-art performance. [ABSTRACT FROM AUTHOR]

Background: Protein phosphatase 2A (PP2A) is one of the major protein phosphatases in eukaryotic cells and is essential for cellular homeostasis. PP2A is a heterotrimer comprising the dimeric AC core enzyme and a highly variable regulatory B subunit. Distinct B subunits help the core enzyme gain full activity toward specific substrates and contribute to diverse cellular roles of PP2A. PP2A has been thought to play a tumor suppressor and the B56γ3 regulatory subunit was shown to play a key tumor suppressor regulatory subunit of PP2A. Nevertheless, we uncovered a molecular mechanism of how B56γ3 may act as an oncogene in colorectal cancer (CRC). Methods: Polyclonal pools of CRC cells with stable B56γ3 overexpression or knockdown were generated by retroviral or lentiviral infection and subsequent drug selection. Co-immunoprecipitation(co-IP) and in vitro pull-down analysis were applied to analyze the protein–protein interaction. Transwell migration and invasion assays were applied to investigate the role of B56γ3 in affecting motility and invasive capability of CRC cells. The sensitivity of CRC cells to 5-fluorouracil (5-FU) was analyzed using the PrestoBlue reagent assay for cell viability. Immunohistochemistry (IHC) was applied to investigate the expression levels of phospho-AKT and B56γ3 in paired tumor and normal tissue specimens of CRC. DataSets of TCGA and GEO were analyzed to investigate the correlation of B56γ3 expression with overall survival rates of CRC patients. Results: We showed that B56γ3 promoted epithelial-mesenchymal transition (EMT) and reduced the sensitivity of CRC cells to 5-FU through upregulating AKT activity. Mechanistically, B56γ3 upregulates AKT activity by targeting PP2A to attenuate the p70S6K-mediated negative feedback loop regulation on PI3K/AKT activation. B56γ3 was highly expressed and positively correlated with the level of phospho-AKT in tumor tissues of CRC. Moreover, high B56γ3 expression is associated with poor prognosis of a subset of patients with CRC. Conclusions: Our finding reveals that the B56γ3 regulatory subunit-containing PP2A plays an oncogenic role in CRC cells by sustaining AKT activation through suppressing p70S6K activity and suggests that the interaction between B56γ3 and p70S6K may serve as a therapeutic target for CRC. CUkGCcvqWD-y5KjYaB3kRR Video Abstract [ABSTRACT FROM AUTHOR]

Recent deep learning based approaches have achieved great success on handwriting recognition. Chinese characters are among the most widely adopted writing systems in the world. Previous research has mainly focused on recognizing handwritten Chinese characters. However, recognition is only one aspect for understanding a language, another challenging and interesting task is to teach a machine to automatically write (pictographic) Chinese characters. In this paper, we propose a framework by using the recurrent neural network (RNN) as both a discriminative model for recognizing Chinese characters and a generative model for drawing (generating) Chinese characters. To recognize Chinese characters, previous methods usually adopt the convolutional neural network (CNN) models which require transforming the online handwriting trajectory into image-like representations. Instead, our RNN based approach is an end-to-end system which directly deals with the sequential structure and does not require any domain-specific knowledge. With the RNN system (combining an LSTM and GRU), state-of-the-art performance can be achieved on the ICDAR-2013 competition database. Furthermore, under the RNN framework, a conditional generative model with character embedding is proposed for automatically drawing recognizable Chinese characters. The generated characters (in vector format) are human-readable and also can be recognized by the discriminative RNN model with high accuracy. Experimental results verify the effectiveness of using RNNs as both generative and discriminative models for the tasks of drawing and recognizing Chinese characters. [ABSTRACT FROM PUBLISHER]

Abstract: Classical swine fever virus (CSFV) causes significant losses in the pig industry in many countries. Erns is an envelope glycoprotein of CSFV which is known to induce virus-neutralizing antibodies and protective immunity in the natural host. In this study, one recombinant baculoviruses BacSC-Erns expressing histidine-tagged Erns with the transmembrane domain (TM) and cytoplasmic domain (CTD) derived from baculovirus envelope protein gp64 was constructed and its immunizing efficacy was evaluated in a mouse model. After infection, Erns was expressed and anchored on the plasma membrane of Sf-9 cells, as demonstrated by Western-blot and confocal microscopy. Immunogold electron microscopy demonstrated that the Erns glycoprotein was successfully displayed on the baculoviral envelope. Vaccine tests in animals showed that BacSC-Erns elicited significantly higher Erns antibody titers in the immunized mouse models than the control group. This demonstrates that the BacSC-Erns vaccine can be used potentially against CSFV infections. This is the first report demonstrating the potential of Erns-pseudotyped baculovirus as a CSFV vaccine. [Copyright &y& Elsevier]

Background: The schizothoracine fishes, an excellent model for several studies, is a dominant fish group of the Qinghai-Tibet Plateau (QTP). However, species populations have rapidly declined due to various factors, and infection with Echinorhynchus gymnocyprii is cited as a possible factor. In the present study, the molecular characteristics of E. gymnocyprii in four species of schizothoracine fishes from the QTP were explored. Methods: We investigated the infection status of E. gymnocyprii in 156 schizothoracine fishes from the upper Yangtze River, upper Yellow River, and Qinghai Lake in Qinghai Province, China. The complete internal transcribed spacer (ITS) of the ribosomal RNA (rRNA) gene and part of the mitochondrial cytochrome c oxidase subunit 1 (cox1) gene of 35 E. gymnocyprii isolates from these fishes were sequenced and their characteristics analyzed. In addition, we inferred phylogenetic relationships of the E. gymnocyprii populations based on the rRNA-ITS and cox1 sequences. Results: The total prevalence of E. gymnocyprii in schizothoracine fishes was 57.69% (90/156). However, the prevalence among different species as well as that across the geographical locations of the schizothoracine fishes was significantly different. The results of sequence analysis showed that the four E. gymnocyprii populations from different hosts and regions of Qinghai Province were conspecific, exhibiting rich genetic diversity. Phylogenetic analysis based on rRNA-ITS and cox1 sequences supported the coalescence of branches within E. gymnocyprii; the cox1 gene of E. gymnocyprii populations inferred some geographical associations with water systems. In addition, three species of schizothoracine fishes were recorded as new definitive hosts for E. gymnocyprii. Conclusions: To the best of our knowledge, this is the first molecular description of E. gymnocyprii populations in schizothoracine fishes from the Qinghai-Tibet Plateau that provides basic data for epidemiological surveillance and control of acanthocephaliasis to protect endemic fish stocks. [ABSTRACT FROM AUTHOR]

The conversion of monoculture rubber (Hevea brasiliensis) plantations into rubber-based agroforestry systems has become a common trend in forestry management in the past few decades. Rubber-Flemingia macrophylla (a leguminous shrub) systems are popular in southwestern China’s Xishuangbanna region. The biogeochemical cycles of soil carbon and nitrogen in forests are mainly affected by their fractions. This study investigated the effect of introducing Flemingia macrophylla to rubber plantations of different ages on soil carbon and nitrogen fractions. The experimental treatments included R1 (young rubber plantation), RF1 (young rubber-Flemingia macrophylla system), R2 (mature rubber plantation) and RF2 (mature rubber-Flemingia macrophylla system). The results showed that the introduction of Flemingia macrophylla to rubber plantations of different ages significantly changed soil carbon and nitrogen fractions, improved soil labile organic carbon and nitrogen contents, and ameliorated soil environments. The average soil microbial biomass organic carbon, nitrogen and nitrate-nitrogen in the 0-10 cm soil layer during the experimental period was 38.9%, 55.5%, and 214.7% higher in RF1 than R1, respectively, and 22.1%, 22.2%, and 652.2% higher in RF2 than R2, respectively. Therefore, Flemingia macrophylla can be used as an alternative interplanted tree species within rubber plantations in similar environments of southeastern Asia. [ABSTRACT FROM AUTHOR]

Blastocystis is one of the most common parasites inhabiting in small intestines of human and animals. Although its pathogenicity has been remaining controversial, the possibility of zoonotic transmission between human and animals was recognized. The goat was one of the most important economic animals supplying people with cashmere, meat, and dairy products. However, few studies were to investigate Blastocystis infection in goats. A total of 789 faecal specimens of goats (including 362 of dairy, 193 of meat and 234 of cashmere goats) were collected from multiple regions of Shaanxi province in northwestern China to investigate the colonization frequency and subtypes of Blastocystis , and to assess the zoonotic potential of these goats. The respective colonization frequencies of Blastocystis in dairy, meat and cashmere goats were 54.1% (196/362), 40.4% (78/193) and 78.6% (184/234). The prevalence of Blastocystis in pre-weaned (0–2-month) goats was significantly lower than that in goats of other age groups, and the highest colonization was observed in goats of 7–11-month age group. Sequence analysis of Blastocystis positive samples indicated the presence of seven subtypes in these goats, including six known subtypes (STs1, 3, 4, 5, 10, 14) and one possible novel subtype (isolate Sd26), with the subtype 10 as the predominant one. Additionally, zoonotic subtypes were found in dairy (ST1, ST3 and ST5) and cashmere (ST4 and ST5) goats, but not detected in meat goats. These results showed that Blastocystis is highly prevalent, widely distributed and genetically diverse in goats in Shaanxi province, northwestern China, and zoonotic potential of dairy and cashmere goats to transmit Blastocystis . [ABSTRACT FROM AUTHOR]

It is difficult to differentiate pigs that have been injected attenuated vaccines from those that are infected by a virulent virus. In this study, a duplex reverse transcription polymerase chain reaction (RT-PCR) was developed for simultaneous detection and identification of the pathogenic strain (Shimen-strain) and attenuated vaccine strain (C-strain) of classical swine fever virus (CSFV). A fragment of 438 bp or 265 bp was amplified from the genomic RNA of the Shimen-strain or the C-strain, respectively. Both types of viruses were simultaneously identified from the mixed samples of Shimen-strain and C-strain, while no PCR bands were obtained from the templates of some other porcine original viruses with the designed primers. The lowest limit of detection was 0.0616 pg for the C-strain RNA and 0.0844 pg for the Shimen-strain RNA. The developed RT-PCR was adopted to test CSFV from 65 collected samples. Compared with quantitative real-time PCR, the results indicated that the developed RT-PCR can not only be used to distinguish the virulent and attenuated CSFV, but also possesses high sensitivity for detecting CSFV. This is a convenient method to detect and differentiate pigs infected with virulent CSFV from the pigs immunized with the C-strain. [ABSTRACT FROM AUTHOR]

Abstract: Classical swine fever virus (CSFV) causes significant losses in the pig industry in many countries. NS3 proteins of CSFV, which include serine protease and RNA helicase/nucleotide triphosphatase (NTPase) activities, are multifunctional proteins involved in polyprotein processing and viral replication. Previous reports showed that NS3 protein can induce apoptosis in host cells that present cytopathic effects (CPE). Baculovirus/insect cell systems are used widely for recombinant protein production. In this study, one recombinant baculovirus BacSC-NS3 expressing histidine-tagged NS3 with the transmembrane domain (TM) and cytoplasmic domain (CTD) derived from baculovirus envelope protein gp64 of baculovirus was constructed. After infection, NS3 was expressed and anchored to the plasma membrane of Sf-9 cells, as demonstrated by Western blot assay and confocal microscopy. Immunogold electron microscopy demonstrated that the NS3 glycoprotein successfully displayed on the baculoviral envelope. Animal vaccine tests showed that recombinant baculovirus BacSC-NS3 elicited significantly higher NS3 antibody titers in the treated mouse models than the control group. This report demonstrated the potential of NS3-pseudotyped baculovirus expression of NS3 protein successfully. [Copyright &y& Elsevier]

A letter to the editor is presented in response to an article regarding the intraoral fixation method in fixing endotracheal tube (ETT) during craniomaxillofacial surgery.