Glycosphingolipid GM3 is Indispensable for Dengue Virus Genome Replication

Dengue virus (DENV) causes the most prevalent arthropod-borne viral disease of humans worldwide. Glycosphingolipids (GSLs) are involved in virus infection by regulating various steps of viral-host interaction. However, the distinct role of GSLs during DENV infection remains unclear. In this study, we used mouse melanoma B16 cells and their GSL-deficient mutant counterpart GM95 cells to study the influence of GSLs on DENV infection. Surprisingly, GM95 cells were highly resistant to DENV infection compared with B16 cells. Pretreatment of B16 cells with synthetase inhibitor of GM3, the most abundant GSLs in B16 cells, or silencing GM3 synthetase T3GAL5, significantly inhibited DENV infection. DENV attachment and endocytosis were not impaired in GM95 cells, but DENV genome replication was obviously inhibited in GM95 cells compared to B16 cells. Furthermore, GM3 was colocalized with DENV viral replication complex on endoplasmic reticulum (ER) inside the B16 cells. Finally, GM3 synthetase inhibitor significantly reduced the mortality rate of suckling mice that challenged with DENV by impairing the viral replication in mouse brain. Taken together, these data indicated that GM3 was not required for DENV attachment and endocytosis, however, essential for viral genome replication. Targeting GM3 could be a novel strategy to inhibit DENV infection

Exchanging-based Multimodal Fusion with Transformer

We study the problem of multimodal fusion in this paper. Recent exchanging-based methods have been proposed for vision-vision fusion, which aim to exchange embeddings learned from one modality to the other. However, most of them project inputs of multimodalities into different low-dimensional spaces and cannot be applied to the sequential input data. To solve these issues, in this paper, we propose a novel exchanging-based multimodal fusion model MuSE for text-vision fusion based on Transformer. We first use two encoders to separately map multimodal inputs into different low-dimensional spaces. Then we employ two decoders to regularize the embeddings and pull them into the same space. The two decoders capture the correlations between texts and images with the image captioning task and the text-to-image generation task, respectively. Further, based on the regularized embeddings, we present CrossTransformer, which uses two Transformer encoders with shared parameters as the backbone model to exchange knowledge between multimodalities. Specifically, CrossTransformer first learns the global contextual information of the inputs in the shallow layers. After that, it performs inter-modal exchange by selecting a proportion of tokens in one modality and replacing their embeddings with the average of embeddings in the other modality. We conduct extensive experiments to evaluate the performance of MuSE on the Multimodal Named Entity Recognition task and the Multimodal Sentiment Analysis task. Our results show the superiority of MuSE against other competitors. Our code and data are provided at https://github.com/RecklessRonan/MuSE

Large vestibular schwannomas presenting in the late state of pregnancy: a case report and literature review

Vestibular schwannomas in pregnancy have rarely been reported, and there is a lack of in-depth discussion on the experience of management of massive acoustic neuromas in pregnancy. Herein, we present a pregnant woman with a giant vestibular schwannoma and obstructive hydrocephalus who presented at 30 weeks of gestation. She was initially misdiagnosed as having a pregnancy-related reaction of headache, dizziness, and vomiting that had occurred 2 months earlier. After observation at home, her symptoms progressed at 30 weeks of gestation, and imaging findings revealed a brain tumor in the CPA region with secondary cerebella tonsil herniation and obstructive hydrocephalus, and she was transferred to our center for treatment. Consequently, we relieved her hydrocephalus with a ventriculoperitoneal shunt (V-P shunt) and used corticosteroids to simulate fetal maturation. After 10 days, her mental condition deteriorated, and her right limb muscle strength gradually decreased until grade 0 (MMT Grading). Finally, under a joint consultation with the Department of Neurosurgery, Obstetrics, and Anesthesiology, she underwent a cesarean section under general anesthesia and first-stage tumor removal at 31 weeks of gestation. Upon discharge, the previously observed neurological deficits, which were reversible and had manifested during her gestational period, had been successfully resolved, and the fetus had been conserved. The neuroimaging confirmed the complete tumor removal, while the neuropathologic examination revealed a vestibular schwannoma. Therefore, we recommend early diagnosis and treatment for these patients, especially people with headaches, vomiting, and sudden hearing loss during pregnancy. Herein, we concluded that our cases provide a valuable experience in the latest acceptable time frame for the operation to prevent irreversible neurological impairment and premature delivery in late pregnancy

Growth Inhibition and Apoptosis Induced by Osthole, A Natural Coumarin, in Hepatocellular Carcinoma

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most commonly diagnosed tumors worldwide and is known to be resistant to conventional chemotherapy. New therapeutic strategies are urgently needed for treating HCC. Osthole, a natural coumarin derivative, has been shown to have anti-tumor activity. However, the effects of osthole on HCC have not yet been reported. METHODS AND FINDINGS: HCC cell lines were treated with osthole at various concentrations for 24, 48 and 72 hours. The proliferations of the HCC cells were measured by MTT assays. Cell cycle distribution and apoptosis were determined by flow cytometry. HCC tumor models were established in mice by subcutaneously injection of SMMC-7721 or Hepa1-6 cells and the effect of osthole on tumor growths in vivo and the drug toxicity were studied. NF-κB activity after osthole treatment was determined by electrophoretic mobility shift assays and the expression of caspase-3 was measured by western blotting. The expression levels of other apoptosis-related genes were also determined by real-time PCR (PCR array) assays. Osthole displayed a dose- and time-dependent inhibition of the HCC cell proliferations in vitro. It also induced apoptosis and caused cell accumulation in G2 phase. Osthole could significantly suppress HCC tumor growth in vivo with no toxicity at the dose we used. NF-κB activity was significantly suppressed by osthole at the dose- and time-dependent manner. The cleaved caspase-3 was also increased by osthole treatment. The expression levels of some apoptosis-related genes that belong to TNF ligand family, TNF receptor family, Bcl-2 family, caspase family, TRAF family, death domain family, CIDE domain and death effector domain family and CARD family were all increased with osthole treatment. CONCLUSION: Osthole could significantly inhibit HCC growth in vitro and in vivo through cell cycle arrest and inducing apoptosis by suppressing NF-κB activity and promoting the expressions of apoptosis-related genes

Social Network and Its Applications in Finance: A Review of Recent Literature

Applications of social network in Finance is an emerging area. Based on the analysis of the types, channels and characteristics of social networks, we discuss the functions of the social networks from five aspects: information transmission, risk sharing, reputation effect, favouritism and collusion, and relationship asset specificity. The application of these theories in the recent finance literature is thoroughly reviewed. We think endogeneity problem solving, mechanism design (e.g. for firm employees) in the presence of social network, the formation of social network and social network research with the integration of Chinese Guanxi are also interesting and important areas for further exploration

Abberant Immunoglobulin G Glycosylation in Rheumatoid Arthritis by LTQ-ESI-MS

Aberrant glycosylation has been observed in many autoimmune diseases. For example, aberrant glycosylation of immunoglobulin G (IgG) has been implicated in rheumatoid arthritis (RA) pathogenesis. The aim of this study is to investigate IgG glycosylation and whether there is an association with rheumatoid factor levels in the serum of RA patients. We detected permethylated N-glycans of the IgG obtained in serum from 44 RA patients and 30 healthy controls using linear ion-trap electrospray ionization mass spectrometry (LTQ-ESI-MS), a highly sensitive and efficient approach in the detection and identification of N-glycans profiles. IgG N-glycosylation and rheumatoid factor levels were compared in healthy controls and RA patients. Our results suggested that total IgG purified from serum of RA patients shows significantly lower galactosylation (p = 0.0012), lower sialylation (p < 0.0001) and higher fucosylation (p = 0.0063) levels compared with healthy controls. We observed a positive correlation between aberrant N-glycosylation and rheumatoid factor level in the RA patients. In conclusion, we identified aberrant glycosylation of IgG in the serum of RA patients and its association with elevated levels of rheumatoid factor

AutoFAS: Automatic Feature and Architecture Selection for Pre-Ranking System

Industrial search and recommendation systems mostly follow the classic multi-stage information retrieval paradigm: matching, pre-ranking, ranking, and re-ranking stages. To account for system efficiency, simple vector-product based models are commonly deployed in the pre-ranking stage. Recent works consider distilling the high knowledge of large ranking models to small pre-ranking models for better effectiveness. However, two major challenges in pre-ranking system still exist: (i) without explicitly modeling the performance gain versus computation cost, the predefined latency constraint in the pre-ranking stage inevitably leads to suboptimal solutions; (ii) transferring the ranking teacher's knowledge to a pre-ranking student with a predetermined handcrafted architecture still suffers from the loss of model performance. In this work, a novel framework AutoFAS is proposed which jointly optimizes the efficiency and effectiveness of the pre-ranking model: (i) AutoFAS for the first time simultaneously selects the most valuable features and network architectures using Neural Architecture Search (NAS) technique; (ii) equipped with ranking model guided reward during NAS procedure, AutoFAS can select the best pre-ranking architecture for a given ranking teacher without any computation overhead. Experimental results in our real world search system show AutoFAS consistently outperforms the previous state-of-the-art (SOTA) approaches at a lower computing cost. Notably, our model has been adopted in the pre-ranking module in the search system of Meituan, bringing significant improvements

A Voltage-Modulated Nanostrip Spin-Wave Filter and Spin Logic Device Thereof

A nanostrip magnonic-crystal waveguide with spatially periodic width modulation can serve as a gigahertz-range spin-wave filter. Compared with the regular constant-width nanostrip, the periodic width modulation creates forbidden bands (band gaps) at the Brillouin zone boundaries due to the spin-wave reflection by the periodic potential owing to the long-range dipolar interactions. Previous works have shown that there is a critical challenge in tuning the band structures of the magnonic-crystal waveguide once it is fabricated. In this work, using micromagnetic simulations, we show that voltage-controlled magnetic anisotropy can effectively tune the band structures of a ferromagnetic–dielectric heterostructural magnonic-crystal waveguide. A uniformly applied voltage of 0.1 V/nm can lead to a significant frequency shift of ~9 GHz. A spin-wave transistor prototype employing such a kind of spin-wave filter is proposed to realize various logical operations. Our results could be significant for future magnonic computing applications