Immune Efficacy of a Genetically Engineered Vaccine against Lymphocystis Disease Virus: Analysis of Different Immunization Strategies

Here, we report the construction of a vaccine against lymphocystis disease virus (LCDV) using nucleic acid vaccination technology. A fragment of the major capsid protein encoding gene from an LCDV isolated from China (LCDV-cn) was cloned into an eukaryotic expression vector pEGFP-N2, yielding a recombinant plasmid pEGFP-N2-LCDV-cn0.6 kb. This plasmid was immediately expressed after liposomal transfer into the Japanese flounder embryo cell line. The recombinant plasmid was inoculated into Japanese flounder via two routes (intramuscular injection and hypodermic injection) at three doses (0.1, 5, and 15 μg), and then T-lymphopoiesis in different tissues and antibodies raised against LCDV were evaluated. The results indicated that this recombinant plasmid induced unique humoral or cell-mediated immune responses depending on the inoculation route and conferred immune protection. Furthermore, the humoral immune responses and protective effects were significantly increased at higher vaccine doses via the two injection routes. Plasmid pEGFP-N2-LCDV0.6 kb is therefore a promising vaccine candidate against LCDV in Japanese flounder

Zero-Shot Rumor Detection with Propagation Structure via Prompt Learning

The spread of rumors along with breaking events seriously hinders the truth in the era of social media. Previous studies reveal that due to the lack of annotated resources, rumors presented in minority languages are hard to be detected. Furthermore, the unforeseen breaking events not involved in yesterday's news exacerbate the scarcity of data resources. In this work, we propose a novel zero-shot framework based on prompt learning to detect rumors falling in different domains or presented in different languages. More specifically, we firstly represent rumor circulated on social media as diverse propagation threads, then design a hierarchical prompt encoding mechanism to learn language-agnostic contextual representations for both prompts and rumor data. To further enhance domain adaptation, we model the domain-invariant structural features from the propagation threads, to incorporate structural position representations of influential community response. In addition, a new virtual response augmentation method is used to improve model training. Extensive experiments conducted on three real-world datasets demonstrate that our proposed model achieves much better performance than state-of-the-art methods and exhibits a superior capacity for detecting rumors at early stages.Comment: AAAI 202

On the validity of the local Fourier analysis

Local Fourier analysis (LFA) is a useful tool in predicting the convergence factors of geometric multigrid methods (GMG). As is well known, on rectangular domains with periodic boundary conditions this analysis gives the exact convergence factors of such methods. In this work, using the Fourier method, we extend these results by proving that such analysis yields the exact convergence factors for a wider class of problems

Pressure Destabilizes Oxygen Vacancies in Bridgmanite

Bridgmanite may contain a large proportion of ferric iron in its crystal structure in the forms of FeFeO3 and MgFeO2.5 components. We investigated the pressure dependence of FeFeO3 and MgFeO2.5 contents in bridgmanite coexisting with MgFe2O4-phase and with or without ferropericlase in the MgO-SiO2-Fe2O3 ternary system at 2,300 K, 33 and 40 GPa. Together with the experiments at 27 GPa reported in Fei et al. (2020, https://doi.org/10.1029/2019GL086296), our results show that the FeFeO3 and MgFeO2.5 contents in bridgmanite decrease from 7.6 to 5.3 mol % and from 2 to 3 mol % to nearly zero, respectively, with increasing pressure from 27 to 40 GPa. Accordingly, the total Fe3+ decreases from 0.18 to 0.11 pfu. The formation of oxygen vacancies (MgFeO2.5 component) in bridgmanite is therefore dramatically suppressed by pressure. Oxygen vacancies can be produced by ferric iron in Fe3+-rich bridgmanite under the topmost lower mantle conditions, but the concentration should decrease rapidly with increasing pressure. The variation of oxygen-vacancy content with depth may potentially affect the physical properties of bridgmanite and thus affect mantle dynamics

Genome-wide identification of cystathionine beta synthase genes in wheat and its relationship with anther male sterility under heat stress

Cystathionine beta synthase (CBS) domains containing proteins (CDCPs) plays an important role in plant development through regulation of the thioredoxin system, as well as its ability to respond to biotic and abiotic stress conditions. Despite this, no systematic study has examined the wheat CBS gene family and its relation to high temperature-induced male sterility. In this study, 66 CBS family members were identified in the wheat genome, and their gene or protein sequences were used for subsequent analysis. The TaCBS gene family was found to be unevenly distributed on 21 chromosomes, and they were classified into four subgroups according to their gene structure and phylogeny. The results of collinearity analysis showed that there were 25 shared orthologous genes between wheat, rice and Brachypodium distachyon, and one shared orthologous gene between wheat, millet and barley. The cis-regulatory elements of the TaCBS were related to JA, IAA, MYB, etc. GO and KEGG pathway analysis identified these TaCBS genes to be associated with pollination, reproduction, and signaling and cellular processes, respectively. A heatmap of wheat plants based on transcriptome data showed that TaCBS genes were expressed to a higher extent in spikelets relative to other tissues. In addition, 29 putative tae-miRNAs were identified, targeting 41 TaCBS genes. Moreover, qRT-PCR validation of six TaCBS genes indicated their critical role in anther development, as five of them were expressed at lower levels in heat-stressed male sterile anthers than in Normal anthers. Together with anther phenotypes, paraffin sections, starch potassium iodide staining, and qRT-PCR data, we hypothesized that the TaCBS gene has a very important connection with the heat-stressed sterility process in wheat, and these data provide a basis for further insight into their relationship

Proteomic Analysis of Pathways Involved in Estrogen-Induced Growth and Apoptosis of Breast Cancer Cells

Estrogen is a known growth promoter for estrogen receptor (ER)-positive breast cancer cells. Paradoxically, in breast cancer cells that have been chronically deprived of estrogen stimulation, re-introduction of the hormone can induce apoptosis.Here, we sought to identify signaling networks that are triggered by estradiol (E2) in isogenic MCF-7 breast cancer cells that undergo apoptosis (MCF-7:5C) versus cells that proliferate upon exposure to E2 (MCF-7). The nuclear receptor co-activator AIB1 (Amplified in Breast Cancer-1) is known to be rate-limiting for E2-induced cell survival responses in MCF-7 cells and was found here to also be required for the induction of apoptosis by E2 in the MCF-7:5C cells. Proteins that interact with AIB1 as well as complexes that contain tyrosine phosphorylated proteins were isolated by immunoprecipitation and identified by mass spectrometry (MS) at baseline and after a brief exposure to E2 for two hours. Bioinformatic network analyses of the identified protein interactions were then used to analyze E2 signaling pathways that trigger apoptosis versus survival. Comparison of MS data with a computationally-predicted AIB1 interaction network showed that 26 proteins identified in this study are within this network, and are involved in signal transduction, transcription, cell cycle regulation and protein degradation.G-protein-coupled receptors, PI3 kinase, Wnt and Notch signaling pathways were most strongly associated with E2-induced proliferation or apoptosis and are integrated here into a global AIB1 signaling network that controls qualitatively distinct responses to estrogen

Multifunctional Optical Vortex Beam Generator via Cross-Phase Based on Metasurface

We propose a multifunctional optical vortex beam (OVB) generator via cross-phase based on a metasurface. Accordingly, we separately investigate the two different propagation characteristics of OVB modulated by the low-order cross-phase (LOCP) and the high-order cross-phase (HOCP) in a self-selected area. When LOCP modulation is added to OVB, topological charges can be measured for any order of OVB. Moreover, we achieve the rotation tunable performance successfully by adding the rotation component. Then, we realize the function of polygonal beam generation and singularities regulation with the HOCP. The order of the HOCP is exactly equal to the number of a polygon OVB’s sides. The waist radius and usable width of the beam lengthens as the distance of the self-selected area increases. When the conversion rate is doubled, the distance between singularities widens by about 0.5 μm. The proposed OVB generator provides a simple strategy for detecting the value of topological charges and achieving OVB shaping and singularity manipulation simultaneously. We hope this can open new horizons for promoting the development of photon manipulation, optical communication, and vortex beam modulation

Oxygen Vacancy Substitution Linked to Ferric Iron in Bridgmanite at 27 GPa

Ferric iron can be incorporated into the crystal structure of bridgmanite by either oxygen vacancy substitution (MgFeO2.5 component) or charge-coupled substitution (FeFeO3 component) mechanisms. We investigated the concentrations of MgFeO2.5 and FeFeO3 in bridgmanite in the MgO-SiO2-Fe2O3 system at 27 GPa and 1700–2300 K using a multianvil apparatus. The FeFeO3 content increases from 1.6 to 7.6 mol.% and from 5.7 to 17.9 mol.% with and without coexistence of (Mg,Fe)O, respectively, with increasing temperature from 1700 to 2300 K. In contrast, the MgFeO2.5 content does not show clear temperature dependence, that is, ~2–3 and  0.025 pfu

Optimized Design of Plasma Metamaterial Absorber Based on Machine Learning

Metamaterial absorbers have become a popular research direction due to their broad application prospects, such as in radar, infrared imaging, and solar cell fields. Usually, nanostructured metamaterials are associated with a large number of geometric parameters, and traditional simulation designs are time consuming. In this paper, we propose a framework for designing plasma metamaterial absorbers in both a forward prediction and inverse design composed of a primary prediction network (PPN) and an auxiliary prediction network (APN). The framework can build the relationship between the geometric parameters of metamaterials and their optical response (reflection spectra, absorption spectra) from a large number of training samples, thus solving the problem of time-consuming and case-by-case numerical simulations in traditional metamaterial design. This framework can not only improve forward prediction more accurately and efficiently but also inverse design metamaterial absorbers from a given required optical response. It was verified that it is also applicable to absorbers of different structures and materials. Our results show that it can be used in metamaterial absorbers, chiral metamaterials, metamaterial filters, and other fields