Dynamic Semiparametric Factor Model with a Common Break

For change-point analysis of high dimensional time series, we consider a semiparametric model with dynamic structural break factors. The observations are described by a few low dimensional factors with time-invariate loading functions of covariates. The unknown structural break in time models the regime switching e ects introduced by exogenous shocks. In particular, the factors are assumed to be nonstationary and follow a Vector Autoregression (VAR) process with a structural break. In addition, to account for the known spatial discrepancies, we introduce discrete loading functions. We study the theoretical properties of the estimates of the loading functions and the factors. Moreover, we provide both the consistency and the asymptotic convergence results for making inference on the common breakpoint in time. The estimation precision is evaluated via a simulation study. Finally we present two empirical illustrations on modeling the dynamics of the minimum wage policy in China and analyzing a limit order book dataset

Sialic Acid Binding Sites in VP2 of Bluetongue Virus and Their Use during Virus Entry.

Bluetongue virus (BTV), a member of the Orbivirus genus, is transmitted by biting midges (gnats, Culicoides sp.) and is one of the most widespread animal pathogens, causing serious outbreaks in domestic animals, particularly in sheep, with high economic impact. The non-enveloped BTV particle is a double-capsid structure of seven proteins and a genome of 10 double-stranded RNA segments. Although the outermost spike-like VP2 acts as the attachment protein during BTV entry, no specific host receptor has been identified for BTV. Recent high-resolution cryo-electron (cryoEM) structures and biological data have suggested that VP2 may interact with sialic acids (SAs). To confirm this, we have generated protein-based nanoparticles displaying multivalent VP2 and used them to probe glycan arrays. The data show that VP2 binds α2,3-linked SA with high affinity but also binds α2,6-linked SA. Further, Maackia amurensis lectin II (MAL II) and Sambucus nigra lectin (SNA), which specifically bind α2,3-linked and α2,6-linked SAs, respectively, inhibited BTV infection and virus growth in susceptible sheep cells while SNA alone inhibited virus growth in Culicoides-derived cells. A combination of hydrogen deuterium exchange mass spectrometry and site-directed mutagenesis allowed the identification of the specific SA binding residues of VP2. This study provides direct evidence that sialic acids act as key receptor for BTV and that the outer capsid protein VP2 specifically binds SA during BTV entry in both mammalian and insect cells. IMPORTANCE To date no receptor has been assigned for non-enveloped bluetongue virus. To determine if the outermost spike-like VP2 protein is responsible for host cell attachment via interaction with sialic acids, we first generated a protein-based VP2-nanoparticle, for the multivalent presentation of recombinant VP2 protein. Using nanoparticles displaying VP2 to probe a glycan array, we identified that VP2 binds both α2,3-linked and α2,6-linked sialic acids. Lectin inhibitors targeting both linkages of sialic acids showed strong inhibition to BTV infection and progeny virus production in mammalian cells; however the inhibition was only seen with the lectin targeting α2,6-linked sialic acid in insect vector cells. In addition, we identified the VP2 sialic acid binding sites in the exposed tip domain. Our data provides direct evidence that sialic acids act as key receptors for BTV attachment and entry in to both mammalian and insect cells

ℓ2\ell^2 Inference for Change Points in High-Dimensional Time Series via a Two-Way MOSUM

We propose an inference method for detecting multiple change points in high-dimensional time series, targeting dense or spatially clustered signals. Our method aggregates moving sum (MOSUM) statistics cross-sectionally by an $\ell^2$-norm and maximizes them over time. We further introduce a novel Two-Way MOSUM, which utilizes spatial-temporal moving regions to search for breaks, with the added advantage of enhancing testing power when breaks occur in only a few groups. The limiting distribution of an $\ell^2$-aggregated statistic is established for testing break existence by extending a high-dimensional Gaussian approximation theorem to spatial-temporal non-stationary processes. Simulation studies exhibit promising performance of our test in detecting non-sparse weak signals. Two applications, analyzing equity returns and COVID-19 cases in the United States, showcase the real-world relevance of our proposed algorithms.Comment: 111 pages, 10 figure

Dynamic Semiparametric Factor Model with Structural Breaks

For the change-point analysis of a high-dimensional time series, we consider a semiparametric model with dynamic structural break factors. With our model, the observations are described by a few low-dimensional factors with time-invariant loading functions of the covariates. Regarding the structural break, the factors are assumed to be nonstationary and follow a vector autoregression (VAR) process with a change in the parameter values. In addition, to account for the known spatial discrepancies, we introduce discrete loading functions. We study the theoretical properties of the estimates of the loading functions and the factors. Moreover, we provide both the consistency and the asymptotic normality for making an inference on the estimated breakpoint. {Importantly, our results hold for both large and small breaks in the factor dependency structure.} The estimation precision is further illustrated via a simulation study. Finally, we present two empirical applications in modeling the dynamics of the minimum wage policy in China and analyzing a limit order book dataset

DualToken-ViT: Position-aware Efficient Vision Transformer with Dual Token Fusion

Self-attention-based vision transformers (ViTs) have emerged as a highly competitive architecture in computer vision. Unlike convolutional neural networks (CNNs), ViTs are capable of global information sharing. With the development of various structures of ViTs, ViTs are increasingly advantageous for many vision tasks. However, the quadratic complexity of self-attention renders ViTs computationally intensive, and their lack of inductive biases of locality and translation equivariance demands larger model sizes compared to CNNs to effectively learn visual features. In this paper, we propose a light-weight and efficient vision transformer model called DualToken-ViT that leverages the advantages of CNNs and ViTs. DualToken-ViT effectively fuses the token with local information obtained by convolution-based structure and the token with global information obtained by self-attention-based structure to achieve an efficient attention structure. In addition, we use position-aware global tokens throughout all stages to enrich the global information, which further strengthening the effect of DualToken-ViT. Position-aware global tokens also contain the position information of the image, which makes our model better for vision tasks. We conducted extensive experiments on image classification, object detection and semantic segmentation tasks to demonstrate the effectiveness of DualToken-ViT. On the ImageNet-1K dataset, our models of different scales achieve accuracies of 75.4% and 79.4% with only 0.5G and 1.0G FLOPs, respectively, and our model with 1.0G FLOPs outperforms LightViT-T using global tokens by 0.7%

Mapping the pH Sensors Critical for Host Cell Entry by a Complex Nonenveloped Virus.

Bluetongue virus (BTV), in the family Reoviridae, is an insect-borne, double-capsid virus causing hemorrhagic disease in livestock around the world. Here, we elucidate how outer capsid proteins VP2 and VP5 coordinate cell entry of BTV. To identify key functional residues, we used atomic-level structural data to guide mutagenesis of VP2 and VP5 and a series of biological and biochemical approaches, including site-directed mutagenesis, reverse genetics-based virus recovery, expression and characterization of individual recombinant mutant proteins, and various in vitro and in vivo assays. We demonstrate the dynamic nature of the conformational change process, revealing that a unique zinc finger (CCCH) in VP2 acts as the major low pH sensor, coordinating VP2 detachment, subsequently allowing VP5 to sense low pH via specific histidine residues at key positions. We show that single substitution of only certain histidine residues has a lethal effect, indicating that the location of histidine in VP5 is critical to inducing changes in VP5 conformation that facilitates membrane penetration. Further, we show that the VP5 anchoring domain alone recapitulates sensing of low pH. Our data reveal a novel, multiconformational process that overcomes entry barriers faced by this multicapsid nonenveloped virus.IMPORTANCE Virus entry into a susceptible cell is the first step of infection and a significant point at which infection can be prevented. To enter effectively, viruses must sense the cellular environment and, when appropriate, initiate a series of changes that eventually jettison the protective shell and deposit virus genes into the cytoplasm. Many viruses sense pH, but how this happens and the events that follow are often poorly understood. Here, we address this question for a large multilayered bluetongue virus. We show key residues in outer capsid proteins, a pH-sensing histidine of a zinc finger within the receptor-binding VP2 protein, and certain histidine residues in the membrane-penetrating VP5 protein that detect cellular pH, leading to irreversible changes and propel the virus through the cell membrane. Our data reveal a novel mechanism of cell entry for a nonenveloped virus and highlight mechanisms which may also be used by other viruses

Bluetongue virus capsid protein VP5 perforates membranes at low endosomal pH during viral entry.

Bluetongue virus (BTV) is a non-enveloped virus and causes substantial morbidity and mortality in ruminants such as sheep. Fashioning a receptor-binding protein (VP2) and a membrane penetration protein (VP5) on the surface, BTV releases its genome-containing core (VP3 and VP7) into the host cell cytosol after perforation of the endosomal membrane. Unlike enveloped ones, the entry mechanisms of non-enveloped viruses into host cells remain poorly understood. Here we applied single-particle cryo-electron microscopy, cryo-electron tomography and structure-guided functional assays to characterize intermediate states of BTV cell entry in endosomes. Four structures of BTV at the resolution range of 3.4-3.9 Å show the different stages of structural rearrangement of capsid proteins on exposure to low pH, including conformational changes of VP5, stepwise detachment of VP2 and a small shift of VP7. In detail, sensing of the low-pH condition by the VP5 anchor domain triggers three major VP5 actions: projecting the hidden dagger domain, converting a surface loop to a protonated β-hairpin that anchors VP5 to the core and stepwise refolding of the unfurling domains into a six-helix stalk. Cryo-electron tomography structures of BTV interacting with liposomes show a length decrease of the VP5 stalk from 19.5 to 15.5 nm after its insertion into the membrane. Our structures, functional assays and structure-guided mutagenesis experiments combined indicate that this stalk, along with dagger domain and the WHXL motif, creates a single pore through the endosomal membrane that enables the viral core to enter the cytosol. Our study unveils the detailed mechanisms of BTV membrane penetration and showcases general methods to study cell entry of other non-enveloped viruses

Specific TLR-mediated HSP70 activation plays a potential role in host defense against the intestinal parasite Giardia duodenalis

Giardia duodenalis, an important flagellated noninvasive protozoan parasite, infects the upper small intestine and causes a disease termed giardiasis globally. Few members of the heat shock protein (HSP) family have been shown to function as potential defenders against microbial pathogens, while such information is lacking for Giardia. Here we initially screened and indicated that in vitro Giardia challenge induced a marked early upregulation of HSP70 in intestinal epithelial cells (IECs). As noted previously, apoptotic resistance, nitric oxide (NO)-dependent cytostatic effect and parasite clearance, and epithelial barrier integrity represent effective anti-Giardia host defense mechanisms. We then explored the function of HSP70 in modulating apoptosis, NO release, and tight junction (TJ) protein levels in Giardia-IEC interactions. HSP70 inhibition by quercetin promoted Giardia-induced IEC apoptosis, viability decrease, NO release reduction, and ZO-1 and occludin downregulation, while the agonist celastrol could reverse these Giardia-evoked effects. The results demonstrated that HSP70 played a previously unrecognized and important role in regulating anti-Giardia host defense via attenuating apoptosis, promoting cell survival, and maintaining NO and TJ levels. Owing to the significance of apoptotic resistance among those defense-related factors mentioned earlier, we then elucidated the anti-apoptotic mechanism of HSP70. It was evident that HSP70 could negatively regulate apoptosis in an intrinsic way via direct inhibition of Apaf-1 or ROS-Bax/Bcl-2-Apaf-1 axis, and in an extrinsic way via cIAP2-mediated inhibition of RIP1 activity. Most importantly, it was confirmed that HSP70 exerted its host defense function by downregulating apoptosis via Toll-like receptor 4 (TLR4) activation, upregulating NO release via TLR4/TLR2 activation, and upregulating TJ protein expression via TLR2 activation. HSP70 represented a checkpoint regulator providing the crucial link between specific TLR activation and anti-Giardia host defense responses. Strikingly, independent of the checkpoint role of HSP70, TLR4 activation was proven to downregulate TJ protein expression, and TLR2 activation to accelerate apoptosis. Altogether, this study identified HSP70 as a potentially vital defender against Giardia, and revealed its correlation with specific TLR activation. The clinical importance of HSP70 has been extensively demonstrated, while its role as an effective therapeutic target in human giardiasis remains elusive and thus needs to be further clarified

Fast Quantification of Phosphorus in Crude Soybean Oil by Near-Infrared Spectroscopy

The existing methods for the determination of phosphorus content are unable to regulate the addition of acid and base in the refining process of crude soybean oil through real-time monitoring. Therefore, a novel rapid method for determining the phosphorus content of crude soybean oil based on near-infrared spectroscopy was proposed in this study. It was found that standard normal variate transformation was more effective than two other spectral preprocessing methods evaluated for denoising the spectral data indicative of the phosphorus content in soybean crude oil. The characteristic absorption band of phosphorus was optimized by synergy interval partial least squares (SiPLS). A back propagation (BP) neural network prediction model of the phosphorus content in crude soybean oil was established with learning efficiency of 0.005 and 108 training cycles. The determination coefficient (R2), root mean square error (RMSE) and relative standard deviation (RSD) for the correction set were 0.979 7, 0.859 3 and 1.89%, respectively. The R2, RMSE and RSD for the validation set were 0.978 5, 0.963 8 and 2.15%, respectively. The above results showed that NIR spectroscopy can achieve rapid, accurate and non-destructive detection of the phosphorus content in, and provide a feasible method for the refining of crude soybean oil