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Mumps virus (MuV) is highly neurotropic and neurovirulent, hence, the neurovirulence of virus seeds used in the production of mumps vaccines must be tested. The previous neurovirulence evaluation method involves measuring the area of the cavity in the Lewis neonatal rat brain caused by MuV through paraffin sectioning and hematoxylin-eosin (HE) staining. However, the processes of paraffin sectioning and HE staining are time consuming and complicated. To solve this problem, in this study, a vibratome sectioning system was first deployed to evaluate MuV neurovirulence in the rat brain instead of paraffin sectioning and HE staining. The results showed that the vibratome sectioning method could assess the neurovirulence potential of MuV more objectively and efficiently. In addition, the effects of different MuV doses and the ages of the rats in days on this evaluation method were explored. The results indicate that MuV at no less than 10 50 % cell culture infective dose (CCID

This paper presents an improved teaching learning-based whale optimization algorithm (TSWOA) used the simplex method. First of all, the combination of WOA algorithm and teaching learning-based algorithm not only achieves a better balance between exploration and exploitation of WOA, but also makes whales have self-learning ability from the biological background, and greatly enriches the theory of the original WOA algorithm. Secondly, the WOA algorithm adds the simplex method to optimize the current worst unit, averting the agents to search at the boundary, and increasing the convergence accuracy and speed of the algorithm. To evaluate the performance of the improved algorithm, the TSWOA algorithm is employed to train the multi-layer perceptron (MLP) neural network. It is a difficult thing to propose a well-pleasing and valid algorithm to optimize the multi-layer perceptron neural network. Fifteen different data sets were selected from the UCI machine learning knowledge and the statistical results were compared with GOA, GSO, SSO, FPA, GA and WOA, severally. The statistical results display that better performance of TSWOA compared to WOA and several well-established algorithms for training multi-layer perceptron neural networks.

The coronavirus disease 2019 (COVID-19) broke out in early December 2019 in Wuhan, China and escalated into a global pandemic. There is an urgent need to understand the biology of SARS-CoV-2. In this letter, we report the isolation and characterization of seven isolates of SARS-CoV-2. Results show that our viruses have 99% sequence identity with published virus sequences. In addition, all viruses grew well in Vero cells, and one of the viruses had a deletion mutation after short passage. These results shall facilitate the understanding of the characteristics of SARS-CoV-2 in vitro.

Carbone KM, Wolinsky JS (2001) Mumps Virus. In: Fields BN, Howley PM, Griffin DE, Lamb RA, Martin MA, Roizman B, Straus SE, Knipe DM (eds) Fields-virology, vol 4. pp 1381–1400 Carr MJ, Moss E, Waters A, Dean J, Jin L, Coughlan S, Connell J, Hall WW, Hassan J (2010) Molecular epidemiological evaluation of the recent resurgence in mumps virus infections in Ireland. J Clin Microbiol 48:3288–3294 Article Google Scholar Cui A, Zhu Z, Chen M, Zheng H, Liu L, Wang Y, Ma Y, Wang C, Fang X, Li P, Guan R, Wang S, Zhou J, Zheng L, Gao H, Ding Z, Li L, Bo F, Sun Z, Zhang Z, Feng D, He J, Chen H, Jin L, Rota PA, Xu W (2014) Epidemiologic and genetic characteristics of mumps viruses isolated in China from 1995 to 2010. Infect Genet Evol 21:384–390 Article Google Scholar Cui A, Zhu Z, Hu Y, Deng X, Sun Z, Zhang Y, Mao N, Xu S, Fang X, Gao H, Si Y, Lei Y, Zheng H, He J, Wu H, Xu W (2017) Mumps epidemiology and mumps virus genotypes circulating in mainland China during 2013–2015. PLoS ONE 12:e0169561 Article Google Scholar Cui A, Zhu Z, Zhang Y, Qiu Q, Mao N, XU S, Ji Y, Wang H, Xu W (2018) Viral surveillance and genetic characteristics of mumps viruses in China during 2001–2017. Chin J Vacc Immun 24:249–255 Google Scholar Dayan GH, Rubin S (2008) Mumps outbreaks in vaccinated populations: are available mumps vaccines effective enough to prevent outbreaks? Clin Infect Dis 47:1458–1467 Article Google Scholar Iabs (2006) IABs scientific workshop on neurovirulence tests for live virus vaccines, January 31-February 1, 2005, Geneva. Biologicals 34:233–236 Article Google Scholar Park SH (2015) Resurgence of mumps in Korea. Infect Chemother 47:1–11 Article Google Scholar Rubin SA, Afzal MA (2011) Neurovirulence safety testing of mumps vaccines–historical perspective and current status. Vaccine 29:2850–2855 CAS Article Google Scholar Rubin SA, Pletnikov M, Carbone KM (1998) Comparison of the neurovirulence of a vaccine and a wild-type mumps virus strain in the developing rat brain. J Virol 72:8037–8042 CAS Article Google Scholar Rubin SA, Pletnikov M, Taffs R, Snoy PJ, Kobasa D, Brown EG, Wright KE, Carbone KM (2000) Evaluation of a neonatal rat model for prediction of mumps virus neurovirulence in humans. J Virol 74:5382–5384 CAS Article Google Scholar Sauder CJ, Vandenburgh KM, Iskow RC, Malik T, Carbone KM, Rubin SA (2006) Changes in mumps virus neurovirulence phenotype associated with quasispecies heterogeneity. Virology 350:48–57 CAS Article Google Scholar Turner PC, Forsey T, Minor PD (1991) Comparison of the nucleotide sequence of the SH gene and flanking regions of mumps vaccine virus (Urabe strain) grown on different substrates and isolated from vaccinees. J Gen Virol 72(Pt 2):435–437 CAS Article Google Scholar WHO (2012) Weekly epidemiological record releve epidemiologique hebdomadaire 29:241–248 Google Scholar Xu P, Luthra P, Li Z, Fuentes S, D’Andrea JA, Wu J, Rubin S, Rota PA, He B (2012) The V protein of mumps virus plays a critical role in pathogenesis. J Virol 86:1768–1776 CAS Article Google Scholar Zengel J, Phan SI, Pickar A, Xu P, He B (2017) Immunogenicity of mumps virus vaccine candidates matching circulating genotypes in the United States and China. Vaccine 35:3988–3994 CAS Article Google Scholar Download references This work was partially supported by the National Natural Science Foundation of China (31702248), the Beijing Innovation Fund for Small Technology-based Firms (Z16010101394), We gratefully acknowledge the mumps throat swab samples support from Center for Zhejiang Provincial center For Disease Control and Prevention, Jiangsu Provincial Center For Disease Control And Prevention, Shanxi Provincial Center For Disease Control And Prevention, Beijing Center For Diseases Prevention And Control and Hubei Provincial Center For Disease Control And Prevention. Yajing Zhang and Lixia Xie contributed equally to the study. R&D Department, Shanghai King-cell biotechnology Co., Ltd., Shanghai, 201506, China Yajing Zhang, Lixia Xie, Juncheng Ruan, Yulin Gu, Biao Niu, Yachun Zhang, Qi An & Dayong Tian State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, 430070, China Benjie Chai, Zhenfang Fu & Dayong Tian You can also search for this author in PubMed Google Scholar You can also search for this author in PubMed Google Scholar You can also search for this author in PubMed Google Scholar You can also search for this author in PubMed Google Scholar You can also search for this author in PubMed Google Scholar You can also search for this author in PubMed Google Scholar You can also search for this author in PubMed Google Scholar You can also search for this author in PubMed Google Scholar You can also search for this author in PubMed Google Scholar You can also search for this author in PubMed Google Scholar Correspondence to Zhenfang Fu or Qi An or Dayong Tian. The authors declare that they have no conflict of interest. Animal experiments in this study were approved by the Ethics Committees of Huazhong Agriculture University (Approval Number: HZAUMO-2019-020). Below is the link to the electronic supplementary material. Reprints and Permissions Zhang, Y., Xie, L., Chai, B. et al. A Highly Attenuated Mumps Virus Strain of Genotype F Generated by Passaging in Vero Cells. Virol. Sin. (2020). https://doi.org/10.1007/s12250-020-00292-5 Download citation Received: 24 February 2020 Accepted: 28 June 2020 Published: 29 September 2020 DOI: https://doi.org/10.1007/s12250-020-00292-5

This study was conducted to determine the optimal dose of the oral solution of the ultrasonic extract of Radix dichroae (UERD) and to provide experimental support for a safe clinical dose for anticoccidial treatment of broiler chickens. Radix dichroae root extracts were prepared using the ultrasonic extraction method. The anticoccidial activity of the oral solution prepared from the ultrasonic extract of Radix dichroae roots was tested in broiler chickens following oral infection with a field isolate of E. tenella. Ninety Lingnan yellow broiler chickens (14 days old) were randomly divided into nine groups (n = 10), including six UERD oral solution treatments (0.25, 0.50, 1.50, 2.50, 3.50, and 5.00%), a toltrazuril group (0.10%), an E. tenella-infected control group, and a healthy control group. All groups were inoculated orally with 7 × 104 sporulated E. tenella oocysts (Guangdong strain) except for the healthy control group. The chickens in the seven drug-treated groups were administered a UERD oral solution or toltrazuril in drinking water for 7 days. The anticoccidial efficacy of the UERD oral solution was evaluated by the bloody diarrhoea severity level, relative body weight gain (rBWG), lesion score, oocyst per gram (OPG), and anticoccidial index (ACI). Compared with the infected control group, there were no significant differences in the groups treated with UERD oral solution or toltrazuril with regard to the lesion changes in the caecal regions (P > 0.05); however, the blood contents, OPG, and oocyst score in three UERD oral solution treatment groups (0.50, 1.50, and 2.50%) were significantly reduced, and the bloody diarrhoea was also alleviated. The ACI in three UERD oral solution treatment groups (0.50%, ACI = 143.7; 1.50%, ACI = 151.0; and 2.50%, ACI = 144.3) was higher than that in the toltrazuril group (ACI = 127.0), and the rBWG in the 1.50% UERD oral solution treatment group (95.0%) was similar to that in the healthy control group (100%), which was also 12.5% higher than that in the toltrazuril group (82.5%). The findings of this study demonstrated that the UERD oral solution (0.50% ～ 2.50% dose range) showed better prevention, anticoccidial efficacy, and growth promotion effects than toltrazuril (0.10%), and the 1.50% dose level of UERD oral solution in water is the clinically recommended dose according to the present study conditions.

This study was conducted to determine the optimal dose of the oral solution of the ultrasonic extract of Radix dichroae (UERD) and to provide experimental support for a safe clinical dose for anticoccidial treatment of broiler chickens. Radix dichroae root extracts were prepared using the ultrasonic extraction method. The anticoccidial activity of the oral solution prepared from the ultrasonic extract of Radix dichroae roots was tested in broiler chickens following oral infection with a field isolate of E. tenella. Ninety Lingnan yellow broiler chickens (14 days old) were randomly divided into nine groups (n = 10), including six UERD oral solution treatments (0.25, 0.50, 1.50, 2.50, 3.50, and 5.00%), a toltrazuril group (0.10%), an E. tenella-infected control group, and a healthy control group. All groups were inoculated orally with 7 × 104 sporulated E. tenella oocysts (Guangdong strain) except for the healthy control group. The chickens in the seven drug-treated groups were administered a UERD oral solution or toltrazuril in drinking water for 7 days. The anticoccidial efficacy of the UERD oral solution was evaluated by the bloody diarrhoea severity level, relative body weight gain (rBWG), lesion score, oocyst per gram (OPG), and anticoccidial index (ACI). Compared with the infected control group, there were no significant differences in the groups treated with UERD oral solution or toltrazuril with regard to the lesion changes in the caecal regions (P>0.05); however, the blood contents, OPG, and oocyst score in three UERD oral solution treatment groups (0.50, 1.50, and 2.50%) were significantly reduced, and the bloody diarrhoea was also alleviated. The ACI in three UERD oral solution treatment groups (0.50%, ACI = 143.7; 1.50%, ACI = 151.0; and 2.50%, ACI = 144.3) was higher than that in the toltrazuril group (ACI = 127.0), and the rBWG in the 1.50% UERD oral solution treatment group (95.0%) was similar to that in the healthy control group (100%), which was also 12.5% higher than that in the toltrazuril group (82.5%). The findings of this study demonstrated that the UERD oral solution (0.50% ～ 2.50% dose range) showed better prevention, anticoccidial efficacy, and growth promotion effects than toltrazuril (0.10%), and the 1.50% dose level of UERD oral solution in water is the clinically recommended dose according to the present study conditions.

Based on the equipment problems of capacitor voltage transformer (CVT) caused by capacitor element breakdown and the analyzed situation towards these equipments, this research made tests on the CVT and calculated the tested data, capacitor element numbers, and capacitance theoretically, and finally put up with the fluctuation value range for detecting the secondary voltage of CVT and the strategies for operation and maintenance, which will improve the problem-finding probability of CVT by detecting secondary voltage.

Pleuromutilin derivatives 4a-h, 5a-g, and 6a-d were synthesized and characterized by IR, 1 H NMR, and 13 C NMR. All synthetic compounds were screened for their in vitro antibacterial activity against Staphylococcus aureus (ATCC 25923), methicillin-resistant S. aureus (MRSA, ATCC 43300), Pasteurella multocida (CVCC 408), Escherichia coli (ATCC 25922), and Salmonella typhimurium (ATCC 14028). Most compounds with quaternary amine showed higher antibacterial activities against both Gram-positive and Gram-negative bacteria strains. Among the screened compounds, compound 5a bearing an N,N,N-trimethyl group at the C-14 side chain of pleuromutilin was found to be the most active agent. Furthermore, preliminary molecular docking was performed to predict the binding interaction of the compounds in the binding pocket.

Seven new cucurbitane glucosides, 11-oxomogrosides III E and IV (1 and 2), 11-oxoisomogroside V (3), 7-oxomogrosides III E and IV (4 and 5), and mogrosides VI A and VI B (6 and 7), were separated from the crude extract of Siraitia grosvenorii. The new structures were defined by analysis of their 1H and 13C NMR, 2D NMR, and HRESIMS data. Especially, the band-selective constant time HSQC and band-selective constant time HMBC techniques were recuited to elucidate the structures of the complex glucoside moieties. Using the PGC-1α promoter driven luciferase reporter assay, the isolated compounds were examined for PGC-1α promoter activity.

Semantic attributes have been proved to be an effective representation approach for image classification in recent years. However, most of the existing semantic attributes are explicitly pre-defined and the attribute number is also very limited in practice. Therefore, we often encounter difficulties by using a fixed incomplete semantic attribute set for different classification tasks. One possible solution is to expand the semantic attribute representation with some non-semantic mid-level features. However, how to make the expanded features more effective and discriminative is still seldom exploited. In this paper, we propose a Sequential augmented Attributes learning (SAL) method to implement semantic attribute augmentation. In our SAL method, the non-semantic mid-level features are learned one by one under a sequential error-correcting scheme so that we can obtain more discriminating power with very compact expanded features. Extensive experiments are conducted on two public datasets and the results show that our approach achieves encouraging performance.

This paper presents a lifecycle model (LCM) to simulate bacterial evolution from a finite population of Escherichia coli (E. coli) bacteria. The potential of this approach is in relating the microscopic behaviors of single bacterial cell to the macroscopic effects of bacterial colonies. This can be accomplished via use of an individual-based modeling method under the framework of agent-environment-rule (AER). Here, our study focuses on investigating the behaviors at different developmental stages in E. coli lifecycle and developing a new biologically inspired methodology for static or dynamic systems. The experimental results through a varying environment demonstrates that our model can be used to study under which circumstances a certain bacterial behaviors emerges, and also give an inspiration to design a new biological optimization algorithm being used for optimization problems.

The goal of relevance feedback is to improve the performance of image retrieval by leveraging the labeling of human. It is helpful to introduce active learning method in relevance feedback to alleviate the human burden. In the traditional active learning the samples which can improve the classifier the most if they were labeled are selected for the user's labeling. However, the change of the geometrical structure of the data distribution caused by such expensive labeled samples is not fully exploited. By mining user's labeling information, we can reduce the original feature space dimension to ease the classifier's instability brought by the small sample size. In this paper, we propose a novel batch mode active learning method for informative data selection. The labeled samples are not only used to retrain the classifier, but to learn a subspace which efficiently encodes user's intention as well. Especially, a scheme of certainty propagation on the subspace effectively integrates uncertainty sampling and subspace learning into the proposed Subspace learning based batch mode Active Learning method (SubAL) in relevance feedback. Extensive experiments on publicly available dataset shows that the proposed method is promising.

Traditionally, Collaborative Filtering assumes that similar users have similar responses to similar items. However, human activities exhibit heterogenous features across multiple domains such that users own similar tastes in one domain may behave quite differently in other domains. Moreover, highly sparse data presents crucial challenge in preference prediction. Intuitively, if users' interested domains are captured first, the recommender system is more likely to provide the enjoyed items while filter out those uninterested ones. Therefore, it is necessary to learn preference profiles from the correlated domains instead of the entire user-item matrix. In this paper, we propose a unified framework, TopRec, which detects topical communities to construct interpretable domains for domain-specific collaborative filtering. In order to mine communities as well as the corresponding topics, a semi-supervised probabilistic topic model is utilized by integrating user guidance with social network. Experimental results on real-world data from Epinions and Ciao demonstrate the effectiveness of the proposed framework.

The cysteine and glycine-rich protein 1 and 2 genes (CSRP1 and CSRP2) are an effective growth factor in promoting skeletal muscle growth in vitro and vivo. However, in cattle, the information on the CSRP1 and CSRP2 genes is very limited. The aim of this study was to examine the association of the CSRP1 and CSRP2 variants with growth and carcass traits in cattle breeds. Three single nucleotide variants (SNVs) were identified within the bovine CSRP1 gene, whereas CSRP2 gene has not detected any SNVs, using DNA pooled sequencing, PCR-RFLP, and forced PCR-RFLP methods. These SNVs include g. 801TC (Intron 2), g. 46TC (Exon 3) and g. 99CG (Intron 3). Besides, we also investigated haplotype frequencies and linkage disequilibrium (LD) coefficients for three SNVs in all study populations. LD and haplotype structure of CSRP1 were different between breeds. The result of haplotype analysis demonstrated eight haplotype present in QC (Qinchuan) and one haplotype in CH (Chinese Holstein). Only haplotype 1 (TTC), shared by all two populations, comprised 10.74% and 100.00%, of all haplotypes observed in QC and CH, respectively. Haplotype 5 (CTC) had the highest haplotype frequencies in QC (30.98%) and haplotype 1 had the highest haplotype frequencies in CH (100.00%). The statistical analyses indicated that one single SNV and 19 combined haplotypes were significantly or highly significantly associated with growth and carcass traits in the QC cattle population (P0.05 or P0.01). Quantitative real-time PCR (qRT-PCR) analyses showed that the bovine CSRP1 and CSRP2 genes were widely expressed in many tissues. The results of this study suggest that the CSRP1 gene possibly is a strong candidate gene that affects growth and carcass traits in the Chinese beef cattle breeding.

Recommendation for cold users is fairly challenging because no prior rating can be used in preference prediction. To tackle this cold-start scenario, rating elicitation is usually employed through an initial interview in which users are queried by some carefully selected items. In this paper, we propose a novel framework to mine the most valuable items to construct query set using a semi-supervised discriminative selection (SSDS) model. To learn a low dimensional representation for users in item space which can reflect their tastes to a large extent, the model incorporates category labels as discriminative information. To ensure the used labels reliable as well as all users considered, the model utilizes a semi-supervised scheme leveraging expert guidance with graph regularization. Experimental results on real-world dataset MovieLens demonstrate that the proposed SSDS model outperforms traditional preference elicitation methods on top-N measures for cold-start recommendation.

Relevance feedback is a quite effective approach to improve performance for image retrieval. Recently, active learning method has attracted much attention due to its capability of alleviating the burden of labeling in relevance feedback. However, most of the traditional studies focus on single sample selection in each feedback which needs heavy computational cost in practice. In this paper, we presents a novel batch mode active learning method for informative sample selection. Inspired by graph propagation, we consider the certainty of labels as asymmetric propagation information on graph, and formulate the correlation between labeled samples and unlabeled samples in an united scheme. Extensive experiments on publicly available data sets show that the proposed method is promising.

Selective sampling has been widely used in relevance feedback of image retrieval to alleviate the burden of labeling by selecting the most informative instances for user to label. Traditional sample selection scheme often selects a batch of instances each time and label them simultaneously, which ignores the correlation among instances and results in redundant labeling. In this paper, we propose an improved representative sampling method with certainty propagation to improve the performance of sampling. In our method, two kinds of correlations among instances are explored to reduce the redundancy in sampling. One is the correlation between labeled instances and unlabeled instances. The other is the correlation among unlabeled instances. Extensive experiments show that the proposed method achieve encouraging results.