Fast Learning of Temporal Action Proposal via Dense Boundary Generator

Generating temporal action proposals remains a very challenging problem, where the main issue lies in predicting precise temporal proposal boundaries and reliable action confidence in long and untrimmed real-world videos. In this paper, we propose an efficient and unified framework to generate temporal action proposals named Dense Boundary Generator (DBG), which draws inspiration from boundary-sensitive methods and implements boundary classification and action completeness regression for densely distributed proposals. In particular, the DBG consists of two modules: Temporal boundary classification (TBC) and Action-aware completeness regression (ACR). The TBC aims to provide two temporal boundary confidence maps by low-level two-stream features, while the ACR is designed to generate an action completeness score map by high-level action-aware features. Moreover, we introduce a dual stream BaseNet (DSB) to encode RGB and optical flow information, which helps to capture discriminative boundary and actionness features. Extensive experiments on popular benchmarks ActivityNet-1.3 and THUMOS14 demonstrate the superiority of DBG over the state-of-the-art proposal generator (e.g., MGG and BMN). Our code will be made available upon publication.Comment: Accepted by AAAI 2020. Ranked No. 1 on ActivityNet Challenge 2019 on Temporal Action Proposals (http://activity-net.org/challenges/2019/evaluation.html

High-Resolution GAN Inversion for Degraded Images in Large Diverse Datasets

The last decades are marked by massive and diverse image data, which shows increasingly high resolution and quality. However, some images we obtained may be corrupted, affecting the perception and the application of downstream tasks. A generic method for generating a high-quality image from the degraded one is in demand. In this paper, we present a novel GAN inversion framework that utilizes the powerful generative ability of StyleGAN-XL for this problem. To ease the inversion challenge with StyleGAN-XL, Clustering \& Regularize Inversion (CRI) is proposed. Specifically, the latent space is firstly divided into finer-grained sub-spaces by clustering. Instead of initializing the inversion with the average latent vector, we approximate a centroid latent vector from the clusters, which generates an image close to the input image. Then, an offset with a regularization term is introduced to keep the inverted latent vector within a certain range. We validate our CRI scheme on multiple restoration tasks (i.e., inpainting, colorization, and super-resolution) of complex natural images, and show preferable quantitative and qualitative results. We further demonstrate our technique is robust in terms of data and different GAN models. To our best knowledge, we are the first to adopt StyleGAN-XL for generating high-quality natural images from diverse degraded inputs. Code is available at https://github.com/Booooooooooo/CRI

The truncated IFITM3 facilitates the humoral immune response in inactivated influenza vaccine-vaccinated mice via interaction with CD81

A single-nucleotide polymorphism (SNP) rs12252-C of interferon-induced transmembrane protein 3 (IFITM3), resulting in a truncated IFITM3 protein lacking 21 N-terminus amino acids, is associated with severe influenza infection in the Chinese population. However, the effect of IFITM3 rs12252-C on influenza vaccination and the underlying mechanism is poorly understood. Here, we constructed a mouse model with a deletion of 21 amino acids at the N-terminus (NΔ21) of IFITM3 and then compared the antibody response between Quadrivalent influenza vaccine (QIV) immunized wild-type (WT) mice and NΔ21 mice. Significantly higher levels of HI titer, neutralizing antibodies (NAb), and immunoglobulin G (IgG) to H1N1, H3N2, B/Victory, and B/Yamagata viruses were observed in NΔ21 mice compared to WT mice. Correspondingly, the numbers of splenic germinal center (GC) B cells, plasma cells, memory B cells, QIV-specific IgG+ antibody-secreting cells (ASC), and T follicular helper cells (TFH) in NΔ21 mice were higher compared with WT mice. Moreover, the 21-amino-acid deletion caused IFITM3 translocation from the endocytosis compartment to the periphery of cells, which also prevented the degradation of a co-stimulatory molecule of B cell receptor (BCR) CD81 on the cell surface. More importantly, a more interaction was observed between NΔ21 protein and CD81 compared to the interaction between IFITM3 and CD81. Overall, our study revealed a potential mechanism of NΔ21 protein enhancing humoral immune response by relocation to prevent the degradation of CD81, providing insight into SNP affecting influenza vaccination

A mosaic influenza virus-like particles vaccine provides broad humoral and cellular immune responses against influenza A viruses

Abstract The development of a universal influenza vaccine to elicit broad immune responses is essential in reducing disease burden and pandemic impact. In this study, the mosaic vaccine design strategy and genetic algorithms were utilized to optimize the seasonal influenza A virus (H1N1, H3N2) hemagglutinin (HA) and neuraminidase (NA) antigens, which also contain most potential T-cell epitopes. These mosaic immunogens were then expressed as virus-like particles (VLPs) using the baculovirus expression system. The immunogenicity and protection effectiveness of the mosaic VLPs were compared to the commercial quadrivalent inactivated influenza vaccine (QIV) in the mice model. Strong cross-reactive antibody responses were observed in mice following two doses of vaccination with the mosaic VLPs, with HI titers higher than 40 in 15 of 16 tested strains as opposed to limited cross HI antibody levels with QIV vaccination. After a single vaccination, mice also show a stronger level of cross-reactive antibody responses than the QIV. The QIV vaccinations only elicited NI antibodies to a small number of vaccine strains, and not even strong NI antibodies to its corresponding vaccine components. In contrast, the mosaic VLPs caused robust NI antibodies to all tested seasonal influenza virus vaccine strains. Here, we demonstrated the mosaic vaccines induces stronger cross-reactive antibodies and robust more T-cell responses compared to the QIV. The mosaic VLPs also provided protection against challenges with ancestral influenza A viruses of both H1 and H3 subtypes. These findings indicated that the mosaic VLPs were a promising strategy for developing a broad influenza vaccine in future

Cryo-EM structure of infectious bronchitis coronavirus spike protein reveals structural and functional evolution of coronavirus spike proteins.

As cell-invading molecular machinery, coronavirus spike proteins pose an evolutionary conundrum due to their high divergence. In this study, we determined the cryo-EM structure of avian infectious bronchitis coronavirus (IBV) spike protein from the γ-genus. The trimeric IBV spike ectodomain contains three receptor-binding S1 heads and a trimeric membrane-fusion S2 stalk. While IBV S2 is structurally similar to those from the other genera, IBV S1 possesses structural features that are unique to different other genera, thereby bridging these diverse spikes into an evolutionary spectrum. Specifically, among different genera, the two domains of S1, the N-terminal domain (S1-NTD) and C-terminal domain (S1-CTD), diverge from simpler tertiary structures and quaternary packing to more complex ones, leading to different functions of the spikes in receptor usage and membrane fusion. Based on the above structural and functional comparisons, we propose that the evolutionary spectrum of coronavirus spikes follows the order of α-, δ-, γ-, and β-genus. This study has provided insight into the evolutionary relationships among coronavirus spikes and deepened our understanding of their structural and functional diversity

Detailed structure of IBV spike ectodomain.

<p>(A) Schematic drawing of IBV S1. SD1: subdomain 1. SD2: subdomain 2. SD1’ and SD1”: two parts of SD1. SD2’ and SD2”: two parts of SD2. (B) Structure of monomeric S1. S1-NTD is colored in cyan. S1-CTD is colored in green. SD1 is colored in magenta. SD2 is colored in orange. * indicates putative sugar-binding site. Partial ceiling on top of the S1-NTD core is labeled. Putative receptor-binding motif loops (RBMs) in S1-CTD are also labeled. (C) Structure of trimeric S1. Three S1 subunits are colored differently. (D) Structure of monomeric S2. The structural elements are colored in the same way as in <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1007009#ppat.1007009.g001" target="_blank">Fig 1A</a>. (E) Structure of trimeric S2. Dotted line indicates residues 702–710 that are missing in the structural model. The structural elements of subunit A are colored in the same way as in <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1007009#ppat.1007009.g001" target="_blank">Fig 1D</a>. Subunits B and C are colored in light purple and light pink, respectively. All structures are viewed from the side.</p

Characterization of a New Member of Alphacoronavirus with Unique Genomic Features in Rhinolophus Bats

Bats have been identified as a natural reservoir of a variety of coronaviruses (CoVs). Several of them have caused diseases in humans and domestic animals by interspecies transmission. Considering the diversity of bat coronaviruses, bat species and populations, we expect to discover more bat CoVs through virus surveillance. In this study, we described a new member of alphaCoV (BtCoV/Rh/YN2012) in bats with unique genome features. Unique accessory genes, ORF4a and ORF4b were found between the spike gene and the envelope gene, while ORF8 gene was found downstream of the nucleocapsid gene. All the putative genes were further confirmed by reverse-transcription analyses. One unique gene at the 3&#8217; end of the BtCoV/Rh/YN2012 genome, ORF9, exhibits ~30% amino acid identity to ORF7a of the SARS-related coronavirus. Functional analysis showed ORF4a protein can activate IFN-&#946; production, whereas ORF3a can regulate NF-&#954;B production. We also screened the spike-mediated virus entry using the spike-pseudotyped retroviruses system, although failed to find any fully permissive cells. Our results expand the knowledge on the genetic diversity of bat coronaviruses. Continuous screening of bat viruses will help us further understand the important role played by bats in coronavirus evolution and transmission

Structural comparisons of S1-NTDs from four coronavirus genera.

<p>(A) Structure of S1-NTD from α-genus human coronavirus NL63 (PDB ID: 5SZS). Although each subunit of NL63 S1 contains two copies of S1-NTDs (i.e., S1-NTD1 and S1-NTD2), S1-NTD2 was used in structural comparisons with the S1-NTDs from the other genera because it occupies the same location as the S1-NTDs from the other genera in quaternary structures of the spikes (see <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1007009#ppat.1007009.g005" target="_blank">Fig 5A</a>). (B) Structure of S1-NTD from δ-genus porcine delta coronavirus (PdCoV) (PDB ID: 6B7N). (C) Structure of S1-NTD from γ-genus IBV. (D) Structure of S1-NTD from β-genus SARS coronavirus (PDB ID: 5X58). * indicates sugar-binding site or putative sugar-binding site in sugar-binding S1-NTDs from each genus. Core structure, partial ceiling, and extensive ceiling are labeled. Arrows from panels (A) to (D) indicate evolutionary direction. (E) Quantitative structural comparisons among S1-NTDs from different genera using software Dali [<a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1007009#ppat.1007009.ref058" target="_blank">58</a>]. Both Z-score and r.m.s.d. were calculated for each pair of the proteins. PDB IDs for NL63, PdCoV and SARS S1-NTDs are the same as in panels (A)-(D). PDB IDs for mouse hepatitis coronavirus (MHV) and MERS coronavirus are 3JCL and 5X5F, respectively. CEACAM1b (PDB ID: 5VST), whose β-sandwich fold is topologically different from that of coronavirus S1-NTDs [<a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1007009#ppat.1007009.ref059" target="_blank">59</a>], was used as a negative control. N.D.: no detectable structural similarity.</p

Structural comparisons of S1-CTDs from four coronavirus genera.

<p>(A)-(D): Structures of S1-CTDs from different genera. Core structures and RBMs are labeled. (E) Quantitative structural comparisons among S1-CTDs from different genera. The PDB IDs are the same as those in <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1007009#ppat.1007009.g003" target="_blank">Fig 3</a>. Left right arrows from panels (A) to (D) indicate that evolution could go either way.</p