169 results on '"Siyuan Hao"'
Search Results
2. Identification of SLC35A1 as an essential host factor for the transduction of multi-serotype recombinant adeno-associated virus (AAV) vectors
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Xiujuan Zhang, Siyuan Hao, Zehua Feng, Kang Ning, Cagla Aksu Kuz, Shane McFarlin, Donovan Richart, Fang Cheng, Ander Zhang-Chen, Richenda McFarlane, Ziying Yan, and Jianming Qiu
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rAAV ,SLC35A1 ,transduction ,intracellular trafficking ,nuclear import ,Microbiology ,QR1-502 - Abstract
ABSTRACT We conducted a genome-wide CRISPR/Cas9 screen in suspension 293 F cells transduced with rAAV5. The highly selected genes revealed after two rounds of screening included the previously reported KIAA0319L, TM9SF2, and RNF121, along with a cluster of genes involved in glycan biogenesis, Golgi apparatus localization, and endoplasmic reticulum penetration. In this report, we focused on solute carrier family 35 member A1 (SLC35A1), a Golgi apparatus-localized cytidine 5’-monophosphate-sialic acid (CMP-SIA) transporter. We confirmed that SLC35A1 knockout (KO) significantly decreased rAAV5 transduction to a level lower than that observed in KIAA0319L or TM9SF2 KO cells. Although SLC35A1 KO drastically reduced the expression of α2,6-linked SIA on the cell surface, the expression of α2,3-linked SIA, as well as the cell binding and internalization of rAAV5, was only moderately affected. Moreover, SLC35A1 KO significantly diminished the transduction of AAV multi-serotypes, including rAAV2 and rAAV3, which do not utilize SIAs for primary attachment. Notably, the SLC35A1 KO markedly increased transduction of rAAV9 and rAAV11, which primarily attach to cells via binding to galactose. Further analyses revealed that SLC35A1 KO significantly decreased vector nuclear import. More importantly, although the C-terminal cytoplasmic tail deletion (∆C Tail) mutant of SLC35A1 did not drastically decrease SIA expression, it significantly decreased rAAV transduction, as well as vector nuclear import, suggesting that the C-tail is critical in these processes. Furthermore, the T128A mutant significantly decreased SIA expression but still supported rAAV transduction and nuclear import. These findings highlight the involvement of the CMP-SIA transporter in the intracellular trafficking of rAAV vectors post-internalization.IMPORTANCErAAV is an essential tool for gene delivery in the treatment of genetic disorders; however, the mechanisms of rAAV transduction remain partially understood. GPR108 is vital for the transduction of most rAAV vectors, but not for rAAV5. We aimed to identify host factors that impact AAV5 transduction akin to GPR108. Using a genome-wide CRISPR/Cas9 screen in 293 F cells, we identified SLC35A1, a Golgi apparatus-localized CMP-sialic acid transporter that transports CMP-sialic acid from the cytoplasm into the Golgi apparatus for sialylation, is essential to rAAV transduction. Further studies across various AAV serotypes showed SLC35A1 significantly affects vector nuclear import post-internalization. These results underscore the crucial role of SLC35A1 in intracellular trafficking beyond the initial cell attachment of rAAV. more...
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- 2025
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3. Calibration and development of safety performance functions for two-way stop-control intersections on rural two-lane highways in Louisiana
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Ming Sun, Xiaoduan Sun, Ruiche Liu, Siyuan Hao, and Jiahui Li
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Safety performance function ,Intersections ,Two-way stop-controlled ,Rural two-lane highway ,Transportation and communications ,HE1-9990 - Abstract
The first edition of the Highway Safety Manual (HSM) contains a simplistic version of the crash prediction model for two-way stop-controlled intersections (TWSC) on rural two-lane highways. This model considers AADT on major and minor roads, with the base conditions defined as no intersection skewness, no turning lanes, and no lighting. A crash modification factor (CMF) will be applied if an intersection has conditions different from the base condition. However, the HSM model does not take account of curvature. It is well known that curved TWSC intersections are less safe than non-curved ones, particularly on rural two-lane roadways. This paper presents the development of crash prediction models incorporating intersection geometrics for TWSC intersections on rural two-lane highways in Louisiana. Then, it compares the results from the developed model with the calibrated HSM model. The negative binomial model was used with 5126 TWSC intersections verified one by one, including both three- and four-leg intersections from all parishes (counties). The estimation results indicate that AADT, curve radius, and intersection skewness angle significantly impact expected crash frequency for both three- and four-leg intersections. This research utilizes cumulative residual plots, mean absolute error, and root mean square error for comparative analysis of HSM models, HSM models with calibration, and Louisiana-specific models. The results show that Louisiana-specific SPFs outperformed the calibrated SPFs with superior reliability. Calibration factors of 0.58 for three-leg intersections and 0.46 for four-leg intersections are estimated, suggesting that the original HSM model overpredicts crashes in Louisiana. more...
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- 2024
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4. Identification of the role of SNARE proteins in rAAV vector production through interaction with the viral MAAP
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Cagla Aksu Kuz, Kang Ning, Siyuan Hao, Shane McFarlin, Xiujuan Zhang, Fang Cheng, and Jianming Qiu
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rAAV ,SNARE ,MAAP ,vector secretion ,vector production ,Genetics ,QH426-470 ,Cytology ,QH573-671 - Abstract
Adeno-associated virus (AAV) expresses a membrane-associated accessory protein (MAAP), a small nonstructural protein, that facilitates AAV secretion out of the plasma membrane through an association with extracellular vesicles during AAV egress. Here, we investigated the host proteins that interact with AAV2 MAAP (MAAP2) using APEX2-mediated proximity labeling. We identified two SNARE proteins, Syntaxin 7 (STX7) and synaptosome-associated protein 23 (SNAP23), a vesicle (v-)SNARE and a target (t-)SNARE, respectively, that mediate intracellular trafficking of membrane vesicles aand exhibited associations with MAAP2 in HEK293 cells. We found that MAAP2 indirectly interacted with STX7 or SNAP23, and that the knockout of STX7 or SNAP23 not only enhanced rAAV secretion into the media but also increased total vector yield during rAAV vector production in HEK293 cells. Thus, our study revealed a practical approach for producing higher yields of rAAV vectors from the media, easing downstream processes in rAAV manufacturing. more...
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- 2025
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5. YAP condensates are highly organized hubs
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Siyuan Hao, Ye Jin Lee, Nadav Benhamou Goldfajn, Eduardo Flores, Jindayi Liang, Hannah Fuehrer, Justin Demmerle, Jennifer Lippincott-Schwartz, Zhe Liu, Shahar Sukenik, and Danfeng Cai
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protein ,properties of biomolecules ,molecular mechanism of gene regulation ,molecular interaction ,Biophysics ,Science - Abstract
Summary: YAP/TEAD signaling is essential for organismal development, cell proliferation, and cancer progression. As a transcriptional coactivator, how YAP activates its downstream target genes is incompletely understood. YAP forms biomolecular condensates in response to hyperosmotic stress, concentrating transcription-related factors to activate downstream target genes. However, whether YAP forms condensates under other signals, how YAP condensates organize and function, and how YAP condensates activate transcription in general are unknown. Here, we report that endogenous YAP forms sub-micron scale condensates in response to Hippo pathway regulation and actin cytoskeletal tension. YAP condensates are stabilized by the transcription factor TEAD1, and recruit BRD4, a coactivator that is enriched at active enhancers. Using single-particle tracking, we found that YAP condensates slowed YAP diffusion within condensate boundaries, a possible mechanism for promoting YAP target search. These results reveal that YAP condensate formation is a highly regulated process that is critical for YAP/TEAD target gene expression. more...
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- 2024
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6. Class-Aware Self-Distillation for Remote Sensing Image Scene Classification
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Bin Wu, Siyuan Hao, and Wei Wang
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Deep learning ,knowledge distillation (KD) ,remote sensing image ,scene classification ,vision transformer (ViT) ,Ocean engineering ,TC1501-1800 ,Geophysics. Cosmic physics ,QC801-809 - Abstract
Currently, convolutional neural networks (CNNs) and vision transformers (ViTs) are widely adopted as the predominant neural network architectures for remote sensing image scene classification. Although CNNs have lower computational complexity, ViTs have a higher performance ceiling, making both suitable as backbone networks for remote sensing scene classification tasks. However, remote sensing imagery has high intraclass variation and interclass similarity, which poses a challenge for existing methods. To address this issue, we propose the class-aware self-distillation (CASD) framework. This framework uses an end-to-end distillation mechanism to mine class-aware knowledge, effectively reducing the impact of significant intraclass variation and interclass similarity in remote sensing imagery. Specifically, our approach involves constructing pairs of images: similar pairs consisting of images belonging to the same class, and dissimilar pairs consisting of images from different classes. We then apply a distillation loss that we designed, which distills the corresponding probability distributions to ensure that the distributions of similar pairs become more consistent, and those of dissimilar pairs become more distinct. In addition, the enforced learnable $\alpha$ added to the distillation loss further amplifies the network's ability to comprehend class-aware knowledge. The experiment section demonstrates that our method CASD outperforms other methods on four publicly available datasets. And the ablation experiments demonstrate the effectiveness of the method. more...
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- 2024
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7. Human Activity Changed the Genetic Pattern of the Orchid Phaius flavus Population
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Cuiyi Liang, Jun Li, Shixing Li, Huayuan Zhang, Jiahao Zheng, Jianglin Miao, Siyuan Hao, Shasha Wu, Zhongjian Liu, and Junwen Zhai
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genetic differentiation ,habitat fragmentation ,human activity ,Phaius ,Biology (General) ,QH301-705.5 - Abstract
Human activity often has profound effects on plant growth and evolution. Orchids are the most diverse group of flowering plants and are threatened by habitat fragmentation, over-harvesting, and urbanization. A population of Phaius flavus from Beikengding Mount (BM) in the Fujian Province of China was divided into two patches by road construction. This study evaluated its genetic characteristics using restriction site-associated DNA sequencing (RAD-seq) data, more than seven years post-road construction. The purpose of this study was to explore the impact of road construction on the evolution of isolated patches within a population. The analysis revealed that the genetic diversity of patch B was slightly higher than that of patch A in the BM population of P. flavus. Principal component and phylogenetic analyses, genetic structure and genetic differentiation analysis, and bottleneck detection indicated relatively independent genetic differentiation between the two patches. Thus, the construction of the Y013 village road may have influenced different patches of this population on a genetic level. This study provides a case for understanding the impact of specific human activities on plant populations, and then biodiversity conservation. It is conducive to formulating more effective biological protection strategies to mitigate the damage inflicted by human activities on biodiversity. more...
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- 2024
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8. Transcriptional condensates and phase separation: condensing information across scales and mechanisms
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Justin Demmerle, Siyuan Hao, and Danfeng Cai
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Biomolecular condensates ,coactivators ,nuclear organization ,phase separation ,transcription ,Genetics ,QH426-470 ,Cytology ,QH573-671 - Abstract
ABSTRACTTranscription is the fundamental process of gene expression, which in eukaryotes occurs within the complex physicochemical environment of the nucleus. Decades of research have provided extreme detail in the molecular and functional mechanisms of transcription, but the spatial and genomic organization of transcription remains mysterious. Recent discoveries show that transcriptional components can undergo phase separation and create distinct compartments inside the nucleus, providing new models through which to view the transcription process in eukaryotes. In this review, we focus on transcriptional condensates and their phase separation-like behaviors. We suggest differentiation between physical descriptions of phase separation and the complex and dynamic biomolecular assemblies required for productive gene expression, and we discuss how transcriptional condensates are central to organizing the three-dimensional genome across spatial and temporal scales. Finally, we map approaches for therapeutic manipulation of transcriptional condensates and ask what technical advances are needed to understand transcriptional condensates more completely. more...
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- 2023
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9. Inductive Biased Swin-Transformer With Cyclic Regressor for Remote Sensing Scene Classification
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Siyuan Hao, Nan Li, and Yuanxin Ye
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Loss function ,remote sensing image ,scene classification ,self-supervised learning (SSL) ,swin transformer ,Ocean engineering ,TC1501-1800 ,Geophysics. Cosmic physics ,QC801-809 - Abstract
Convolutional neural networks (CNNs) have been widely used in remote sensing scene classification. However, the long-range dependencies of local features cannot be taken into account by CNNs. By contrast, a visual transformer (ViT) is good at capturing the long-range dependencies as it considers the global relationship of local features by introducing a self-attention mechanism. Although the ViT can obtain a good result when training on large-scale datasets, e.g., ImageNet, it is hard to be adapted to small-scale datasets (e.g., remote sensing image datasets). This is attributed to the fact that the ViT lacks the typical inductive bias capability. Therefore, we propose the inductive biased swin transformer with cyclic regressor used with random dense sampler (IBSwin-CR) to improve the training effect of the swin transformer on remote sensing image datasets, which builds upon three modules, i.e., inductive biased shifted window multihead self-attention (IBSW-MSA) module, random dense sampler, and a regressor with cyclic regression loss. We obtain the inductive bias information and the long-range dependencies of the attention map by the IBSW-MSA module. Moreover, the final feature map goes through a random dense sampler, in which the additional spatial information is learned. Finally, the network is normalized by a cross-entropy loss function and a cyclic regression loss function. The proposed IBSwin-CR model is evaluated on public datasets such as NWPU-RESISC45 dataset and Aerial Image Dataset, and the experimental results show that the proposed network can achieve better performance than other classification models, especially for the case with a small number of samples. more...
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- 2023
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10. African swine fever virus QP383R dampens type I interferon production by promoting cGAS palmitoylation
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Siyuan Hao, Xiaojie Zheng, Yingqi Zhu, Yao Yao, Sihan Li, Yangyang Xu, and Wen-hai Feng
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ASFV ,QP383R ,type I interferons ,cGAS ,palmitoylation ,Immunologic diseases. Allergy ,RC581-607 - Abstract
Cyclic GMP-AMP synthase (cGAS) recognizes viral DNA and synthesizes cyclic GMP-AMP (cGAMP), which activates stimulator of interferon genes (STING/MITA) and downstream mediators to elicit an innate immune response. African swine fever virus (ASFV) proteins can antagonize host immune responses to promote its infection. Here, we identified ASFV protein QP383R as an inhibitor of cGAS. Specifically, we found that overexpression of QP383R suppressed type I interferons (IFNs) activation stimulated by dsDNA and cGAS/STING, resulting in decreased transcription of IFNβ and downstream proinflammatory cytokines. In addition, we showed that QP383R interacted directly with cGAS and promoted cGAS palmitoylation. Moreover, we demonstrated that QP383R suppressed DNA binding and cGAS dimerization, thus inhibiting cGAS enzymatic functions and reducing cGAMP production. Finally, the truncation mutation analysis indicated that the 284-383aa of QP383R inhibited IFNβ production. Considering these results collectively, we conclude that QP383R can antagonize host innate immune response to ASFV by targeting the core component cGAS in cGAS-STING signaling pathways, an important viral strategy to evade this innate immune sensor. more...
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- 2023
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11. The prognostic and clinicopathological significance of SLC7A11 in human cancers: a systematic review and meta-analysis
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Jiantao Wang, Siyuan Hao, Guojiao Song, Yan Wang, and Qiukui Hao
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SLC7A11 ,Cancer ,Prognosis ,Systematic review ,Meta-analysis ,Medicine ,Biology (General) ,QH301-705.5 - Abstract
Objective It is of great importance to recognize bio-markers for cancer prognosis. However, the association between solute carrier family 7 member 11 (SLC7A11) and prognosis is still controversial. Therefore, we conducted this systematic review and meta-analysis to identify the prognostic and clinicopathological significance of SLC7A11 in human cancers. Methods PubMed, Web of Science, Scopus, the Cochrane Library and Embase database were searched from database inceptions to March 19th 2022. Hand searches were also conducted in references. Prognosis and clinicopathological data were extracted and analyzed. Results A total of 12 eligible studies with 1,955 patients were included. The results indicated that SLC7A11 expression is associated with unfavorable overall survival (OS), unfavorable recurrence-free survival (RFS) and unfavorable progression free survival (PFS). And SLC7A11 expression is also associated with more advanced tumor stage. Conclusions SLC7A11 expression is associated with more unfavorable prognosis and more advanced tumor stage. Therefore, SLC7A11 could be a potential biomarker for human cancer prognosis. more...
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- 2023
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12. Effect of different aspect ratios of rectangular hole on magnetic shielding property for cylindrical shield
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Jing Zhu, Lei Wang, Siyuan Hao, Xinzhe Shi, Shuai Wang, and Lianqing Zhu
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Physics ,QC1-999 - Abstract
In this paper, the influence of rectangular holes with different aspect ratios in a cylinder on shielding properties is investigated using the finite element method. The two indicators used to assess the shielding properties of the cylinder are its internal residual magnetic field and its outer-surface magnetic field map. The internal residual magnetic field (B) of a cylinder as a function of the aspect ratio of a rectangular hole and its area is simulated, and the conclusions are as follows: with increasing length of the hole, the value of B increases first and then decreases. A cylindrical shield with square holes (the hole aspect ratio is equal to 1) delivers the worst shielding performance. A cylinder with a smaller hole area has better shielding properties, resulting from a less flux leakage from the environmental magnetic field. The anisotropy of the shielding properties is evaluated, and the magnetic shielding in the radial direction is better than that in the axial direction. This research provides a theoretical guide for the application and optimization of magnetic shields. more...
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- 2023
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13. Robust Sparse Bayesian Two-Dimensional Direction-of-Arrival Estimation with Gain-Phase Errors
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Xu Jin, Xuhu Wang, Yujun Hou, Siyuan Hao, Xinjie Wang, Zhenhua Xu, and Qunfei Zhang
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two-dimensional direction-of-arrival (2D DOA) ,gain-phase errors ,sparse signal reconstruction ,sparse Bayesian learning ,L-shaped array ,Chemical technology ,TP1-1185 - Abstract
To reduce the influence of gain-phase errors and improve the performance of direction-of-arrival (DOA) estimation, a robust sparse Bayesian two-dimensional (2D) DOA estimation method with gain-phase errors is proposed for L-shaped sensor arrays. The proposed method introduces an auxiliary angle to transform the 2D DOA estimation problem into two 1D angle estimation problems. A sparse representation model with gain-phase errors is constructed using the diagonal element vector of the cross-correlation covariance matrix of two submatrices of the L-shaped sensor array. The expectation maximization algorithm derives unknown parameter expression, which is used for iterative operations to obtain off-grid and signal precision. Using these parameters, a new spatial spectral function is constructed to estimate the auxiliary angle. The obtained auxiliary angle is substituted into a sparse representation model with gain and phase errors, and then the sparse Bayesian learning method is used to estimate the elevation angle of the incident signal. Finally, according to the relationship of the three angles, the azimuth angle can be estimated. The simulation results show that the proposed method can effectively realize the automatic matching of the azimuth and elevation angles of the incident signal, and improves the accuracy of DOA estimation and angular resolution. more...
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- 2023
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14. The negative effect of antibiotics on RCC patients with immunotherapy: A systematic review and meta-analysis
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Zhiqiang Luo, Siyuan Hao, Yuxuan Li, Lei Cheng, Xuedong Zhou, Emine Gulsen Gunes, Shiyu Liu, and Jing Chen
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carcinoma ,renal cell ,antibiotics ,immunotherapy ,immune checkpoint inhibitors ,meta-analysis ,Immunologic diseases. Allergy ,RC581-607 - Abstract
BackgroundMicrobiome dysbiosis is considered a predictive biomarker of clinical response in renal cell carcinoma (RCC), which can be regulated by antibiotics (ATB). Multiple studies have shown that concomitant ATB administration has inhibitory effects on immunotherapy in RCC. This review aimed to assess the impact of ATB on patient survival and tumor response in RCC with immunotherapy.MethodsLiterature evaluating the effect of ATB on immunotherapy in RCC from Cochrane Library®, PubMed®, Embase®, Scopus®, and Web of Science® were systematically searched. Hazard ratios (HR) for progression-free survival (PFS) and overall survival (OS), odds ratio (OR) for objective response rate (ORR) and primary progressive disease (PD) were pooled as effect sizes for clinical outcomes. Subgroup analysis was conducted to reveal the determinants of the effect of ATB on immunotherapy, including time windows of ATB exposure to immunotherapy initiation, ICIs treatment and study location. The leave-one-out approach was adopted to analyze the heterogeneity formulated. Cumulative meta-analysis adding by time was used to observe dynamic changes of the results.ResultsTen studies were included in the systematic review and six studies (with n=1,104 patients) were included in the meta-analysis, four studies were excluded for overlapping patients with subsequent larger studies and lack of unique patient-level data. ATB administration was significantly correlated with shorter PFS (HR=2.10, 95%CI [1.54; 2.85], I2 = 2% after omitting study Derosa et al, 2021 detected by leave-one-out approach), shorter OS (HR=1.69, 95%CI [1.34; 2.12], I2 = 25%) and worse ORR (OR=0.58, 95%CI [0.41; 0.84]), but no difference was observed in risk of PD (OR=1.18, 95%CI [0.97; 1.44]). No significant differences existed among the subgroups for determining the determinants of ATB inhibition.ConclusionsConcomitant ATB with immunotherapy was associated with worse PFS, OS and ORR in RCC. No publication bias was observed in this study.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=349577, identifier CRD42022349577. more...
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- 2022
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15. Repurposing Niclosamide as a Novel Anti-SARS-CoV-2 Drug by Restricting Entry Protein CD147
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Zhe Yang, Qi Zhang, Xiaoqing Wu, Siyuan Hao, Xinbao Hao, Elizabeth Jones, Yuxia Zhang, Jianming Qiu, and Liang Xu
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CD147 ,RNA-binding protein ,HuR ,niclosamide ,SARS-CoV-2 ,Western blot ,Biology (General) ,QH301-705.5 - Abstract
The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to the global coronavirus disease 2019 (COVID-19) pandemic, and the search for effective treatments has been limited. Furthermore, the rapid mutations of SARS-CoV-2 have posed challenges to existing vaccines and neutralizing antibodies, as they struggle to keep up with the increased viral transmissibility and immune evasion. However, there is hope in targeting the CD147-spike protein, which serves as an alternative point for the entry of SARS-CoV-2 into host cells. This protein has emerged as a promising therapeutic target for the development of drugs against COVID-19. Here, we demonstrate that the RNA-binding protein Human-antigen R (HuR) plays a crucial role in the post-transcriptional regulation of CD147 by directly binding to its 3′-untranslated region (UTR). We observed a decrease in CD147 levels across multiple cell lines upon HuR depletion. Furthermore, we identified that niclosamide can reduce CD147 by lowering the cytoplasmic translocation of HuR and reducing CD147 glycosylation. Moreover, our investigation revealed that SARS-CoV-2 infection induces an upregulation of CD147 in ACE2-expressing A549 cells, which can be effectively neutralized by niclosamide in a dose-dependent manner. Overall, our study unveils a novel regulatory mechanism of regulating CD147 through HuR and suggests niclosamide as a promising therapeutic option against COVID-19. more...
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- 2023
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16. Roles of Toll-Like Receptors in Radiotherapy- and Chemotherapy-Induced Oral Mucositis: A Concise Review
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Ling Ji, Siyuan Hao, Jiantao Wang, Jing Zou, and Yan Wang
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toll-like receptor ,oral mucositis ,gastrointestinal mucositis ,chemotherapy ,radiotherapy ,microbiota dysbiosis ,Microbiology ,QR1-502 - Abstract
Radiotherapy and/or chemotherapy-induced oral mucositis (RIOM/CIOM) is a common complication in cancer patients, leading to negative clinical manifestations, reduced quality of life, and impacting compliance with anticancer treatment. The composition and metabolic function of the oral microbiome, as well as the innate immune response of the oral mucosa are severely altered during chemotherapy or radiotherapy, promoting the expression of inflammatory mediators by direct and indirect mechanisms. Commensal oral bacteria-mediated innate immune signaling via Toll-like receptors (TLRs) ambiguously shapes radiotherapy- and/or chemotherapy-induced oral damage. To date, there has been no comprehensive overview of the role of TLRs in RIOM/CIOM. This review aims to provide a narrative of the involvement of TLRs, including TLR2, TLR4, TLR5, and TLR9, in RIOM/CIOM, mainly by mediating the interaction between the host and microorganisms. As such, we suggest that these TLR signaling pathways are a novel mechanism of RIOM/CIOM with considerable potential for use in therapeutic interventions. More studies are needed in the future to investigate the role of different TLRs in RIOM/CIOM to provide a reference for the precise control of RIOM/CIOM. more...
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- 2022
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17. The prognostic and clinicopathological significance of desmoglein 2 in human cancers: a systematic review and meta-analysis
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Jiantao Wang, Siyuan Hao, Junjie Gu, Sean G. Rudd, and Yan Wang
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Desmoglein 2 ,Cancer ,Prognosis ,Systematic review ,Meta-analysis ,Medicine ,Biology (General) ,QH301-705.5 - Abstract
Objective The survival and clinicopathological significance of desmoglein 2 (DSG2) in various cancers is controversial. Thus, we performed this systematic review and meta-analysis to explore the preliminary prognostic value of DSG2. Methods Eligible studies were identified from databases including PubMed, the Cochrane Library, Embase, Web of Science and Scopus. Hand searches were also conducted in relevant bibliographies. We then extracted and pooled hazard ratio (HR) of overall survival (OS) and odds ratio (OR) of clinicopathological features. Results A total of 11 eligible studies containing 1,488 patients were included. Our results demonstrated that in non-small cell lung cancer (NSCLC), high DSG2 expression is associated with poor OS. However, in digestive system cancer and female reproductive system cancer, there were no statistically significant associations between OS and DSG2. Conclusions Based on the findings of this study, high DSG2 expression is associated with worse prognosis in patients with NSCLC, and thus DSG2 expression could be a biomarker for prognosis in NSCLC. more...
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- 2022
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18. Credible Remote Sensing Scene Classification Using Evidential Fusion on Aerial-Ground Dual-View Images
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Kun Zhao, Qian Gao, Siyuan Hao, Jie Sun, and Lijian Zhou
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multi-view data fusion ,remote sensing scene classification ,uncertainty estimation ,evidential learning ,Dirichlet distribution ,Science - Abstract
Due to their ability to offer more comprehensive information than data from a single view, multi-view (e.g., multi-source, multi-modal, multi-perspective) data are being used more frequently in remote sensing tasks. However, as the number of views grows, the issue of data quality is becoming more apparent, limiting the potential benefits of multi-view data. Although recent deep neural network (DNN)-based models can learn the weight of data adaptively, a lack of research on explicitly quantifying the data quality of each view when fusing them renders these models inexplicable, performing unsatisfactorily and inflexibly in downstream remote sensing tasks. To fill this gap, in this paper, evidential deep learning is introduced to the task of aerial-ground dual-view remote sensing scene classification to model the credibility of each view. Specifically, the theory of evidence is used to calculate an uncertainty value which describes the decision-making risk of each view. Based on this uncertainty, a novel decision-level fusion strategy is proposed to ensure that the view with lower risk obtains more weight, making the classification more credible. On two well-known, publicly available datasets of aerial-ground dual-view remote sensing images, the proposed approach achieves state-of-the-art results, demonstrating its effectiveness. more...
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- 2023
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19. Shallow-to-Deep Spatial–Spectral Feature Enhancement for Hyperspectral Image Classification
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Lijian Zhou, Xiaoyu Ma, Xiliang Wang, Siyuan Hao, Yuanxin Ye, and Kun Zhao
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hyperspectral image classification ,spatial–spectral features ,3D-CNN ,2D-CNN ,Vision-Transformer ,Science - Abstract
Since Hyperspectral Images (HSIs) contain plenty of ground object information, they are widely used in fine-grain classification of ground objects. However, some ground objects are similar and the number of spectral bands is far higher than the number of the ground object categories. Therefore, it is hard to deeply explore the spatial–spectral joint features with greater discrimination. To mine the spatial–spectral features of HSIs, a Shallow-to-Deep Feature Enhancement (SDFE) model with three modules based on Convolutional Neural Networks (CNNs) and Vision-Transformer (ViT) is proposed. Firstly, the bands containing important spectral information are selected using Principal Component Analysis (PCA). Secondly, a two-layer 3D-CNN-based Shallow Spatial–Spectral Feature Extraction (SSSFE) module is constructed to preserve the spatial and spectral correlations across spaces and bands at the same time. Thirdly, to enhance the nonlinear representation ability of the network and avoid the loss of spectral information, a channel attention residual module based on 2D-CNN is designed to capture the deeper spatial–spectral complementary information. Finally, a ViT-based module is used to extract the joint spatial–spectral features (SSFs) with greater robustness. Experiments are carried out on Indian Pines (IP), Pavia University (PU) and Salinas (SA) datasets. The experimental results show that better classification results can be achieved by using the proposed feature enhancement method as compared to other methods. more...
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- 2023
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20. Multi-Channel EEG Emotion Recognition Based on Parallel Transformer and 3D-Convolutional Neural Network
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Jie Sun, Xuan Wang, Kun Zhao, Siyuan Hao, and Tianyu Wang
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EEG ,transformer ,3D-CNN ,feature fusion ,Mathematics ,QA1-939 - Abstract
Due to its covert and real-time properties, electroencephalography (EEG) has long been the medium of choice for emotion identification research. Currently, EEG-based emotion recognition focuses on exploiting temporal, spatial, and spatiotemporal EEG data for emotion recognition. Due to the lack of consideration of both spatial and temporal aspects of EEG data, the accuracy of EEG emotion detection algorithms employing solely spatial or temporal variables is low. In addition, approaches that use spatiotemporal properties of EEG for emotion recognition take temporal and spatial characteristics of EEG into account; however, these methods extract temporal and spatial information directly from EEG data. Since there is no reconstruction of the EEG data format, the temporal and spatial properties of the EEG data cannot be extracted efficiently. To address the aforementioned issues, this research proposes a multi-channel EEG emotion identification model based on the parallel transformer and three-dimensional convolutional neural networks (3D-CNN). First, parallel channel EEG data and position reconstruction EEG sequence data are created separately. The temporal and spatial characteristics of EEG are then retrieved using transformer and 3D-CNN models. Finally, the features of the two parallel modules are combined to form the final features for emotion recognition. On the DEAP, Dreamer, and SEED databases, the technique achieved greater accuracy in emotion recognition than other methods. It demonstrates the efficiency of the strategy described in this paper. more...
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- 2022
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21. The SARS-CoV-2 Transcriptome and the Dynamics of the S Gene Furin Cleavage Site in Primary Human Airway Epithelia
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Wei Zou, Min Xiong, Siyuan Hao, Elizabeth Yan Zhang, Nathalie Baumlin, Michael D. Kim, Matthias Salathe, Ziying Yan, and Jianming Qiu
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Microbiology ,QR1-502 - Abstract
Polarized human airway epithelia at an air-liquid interface (HAE-ALI) are an in vitro
- Published
- 2021
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22. Long-Term Modeling of SARS-CoV-2 Infection of In Vitro Cultured Polarized Human Airway Epithelium
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Siyuan Hao, Kang Ning, Cagla Aksu Kuz, Kai Vorhies, Ziying Yan, and Jianming Qiu
- Subjects
SARS-CoV-2 ,human airway epithelium ,epithelial damage ,recurrent infection ,airway epithelial damage ,long-term infection ,Microbiology ,QR1-502 - Abstract
ABSTRACT Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replicates throughout human airways. The polarized human airway epithelium (HAE) cultured at an airway-liquid interface (HAE-ALI) is an in vitro model mimicking the in vivo human mucociliary airway epithelium and supports the replication of SARS-CoV-2. Prior studies characterized only short-period SARS-CoV-2 infection in HAE. In this study, continuously monitoring the SARS-CoV-2 infection in HAE-ALI cultures for a long period of up to 51 days revealed that SARS-CoV-2 infection was long lasting with recurrent replication peaks appearing between an interval of approximately 7 to 10 days, which was consistent in all the tested HAE-ALI cultures derived from 4 lung bronchi of independent donors. We also identified that SARS-CoV-2 does not infect HAE from the basolateral side, and the dominant SARS-CoV-2 permissive epithelial cells are ciliated cells and goblet cells, whereas virus replication in basal cells and club cells was not detected. Notably, virus infection immediately damaged the HAE, which is demonstrated by dispersed zonula occludens-1 (ZO-1) expression without clear tight junctions and partial loss of cilia. Importantly, we identified that SARS-CoV-2 productive infection of HAE requires a high viral load of >2.5 × 105 virions per cm2 of epithelium. Thus, our studies highlight the importance of a high viral load and that epithelial renewal initiates and maintains a recurrent infection of HAE with SARS-CoV-2. IMPORTANCE The pandemic of coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to >35 million confirmed cases and >1 million fatalities worldwide. SARS-CoV-2 mainly replicates in human airway epithelia in COVID-19 patients. In this study, we used in vitro cultures of polarized human bronchial airway epithelium to model SARS-CoV-2 replication for a period of 21 to 51 days. We discovered that in vitro airway epithelial cultures endure a long-lasting SARS-CoV-2 propagation with recurrent peaks of progeny virus release at an interval of approximately 7 to 10 days. Our study also revealed that SARS-CoV-2 infection causes airway epithelia damage with disruption of tight junction function and loss of cilia. Importantly, SARS-CoV-2 exhibits a polarity of infection in airway epithelium only from the apical membrane; it infects ciliated and goblet cells but not basal and club cells. Furthermore, the productive infection of SARS-CoV-2 requires a high viral load of over 2.5 × 105 virions per cm2 of epithelium. Our study highlights that the proliferation of airway basal cells and regeneration of airway epithelium may contribute to the recurrent infections. more...
- Published
- 2020
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23. Establishment of a Replicon Reporter of the Emerging Tick-Borne Bourbon Virus and Use It for Evaluation of Antivirals
- Author
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Siyuan Hao, Kang Ning, Xiaomei Wang, Jianke Wang, Fang Cheng, Safder S. Ganaie, John E. Tavis, and Jianming Qiu
- Subjects
tick-borne virus ,thogotovirus ,Bourbon virus ,RNA-dependent RNA polymerase ,replicon reporter ,antivirals ,Microbiology ,QR1-502 - Abstract
Bourbon virus (BRBV) was first isolated from a patient hospitalized at the University of Kansas Hospital in 2014. Since then, several deaths have been reported to be caused by BRBV infection in the Midwest and Southern United States. BRBV is a tick-borne virus that is widely carried by lone star ticks. It belongs to genus Thogotovirus of the Orthomyxoviridae family. Currently, there are no treatments or vaccines available for BRBV or thogotovirus infection caused diseases. In this study, we reconstituted a replicon reporter system, composed of plasmids expressing the RNA-dependent RNA polymerase (RdRP) complex (PA, PB1, and PB2), nucleocapsid (NP) protein, and a reporter gene flanked by the 3′ and 5′ untranslated region (UTR) of the envelope glycoprotein (GP) genome segment. By using the luciferase reporter, we screened a few small molecule compounds of anti-endonuclease that inhibited the nicking activity by parvovirus B19 (B19V) NS1, as well as FDA-approved drugs targeting the RdRP of influenza virus. Our results demonstrated that myricetin, an anti-B19V NS1 nicking inhibitor, efficiently inhibited the RdRP activity of BRBV and virus replication. The IC50 and EC50 of myricetin are 2.22 and 4.6 μM, respectively, in cells. Myricetin had minimal cytotoxicity in cells, and therefore the therapeutic index of the compound is high. In conclusion, the BRBV replicon system is a useful tool to study viral RNA replication and to develop antivirals, and myricetin may hold promise in treatment of BRBV infected patients. more...
- Published
- 2020
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- View/download PDF
24. Temporal Spiking Recurrent Neural Network for Action Recognition
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Wei Wang, Siyuan Hao, Yunchao Wei, Shengtao Xiao, Jiashi Feng, and Nicu Sebe
- Subjects
Action recognition ,temporal spiking ,recurrent neural network ,Electrical engineering. Electronics. Nuclear engineering ,TK1-9971 - Abstract
In this paper, we propose a novel temporal spiking recurrent neural network (TSRNN) to perform robust action recognition in videos. The proposed TSRNN employs a novel spiking architecture which utilizes the local discriminative features from high-confidence reliable frames as spiking signals. The conventional CNN-RNNs typically used for this problem treat all the frames equally important such that they are error-prone to noisy frames. The TSRNN solves this problem by employing a temporal pooling architecture which can help RNN select sparse and reliable frames and enhances its capability in modelling long-range temporal information. Besides, a message passing bridge is added between the spiking signals and the recurrent unit. In this way, the spiking signals can guide RNN to correct its long-term memory across multiple frames from contamination caused by noisy frames with distracting factors (e.g., occlusion, rapid scene transition). With these two novel components, TSRNN achieves competitive performance compared with the state-of-the-art CNN-RNN architectures on two large scale public benchmarks, UCF101 and HMDB51. more...
- Published
- 2019
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- View/download PDF
25. Data-Wise Spatial Regional Consistency Re-Enhancement for Hyperspectral Image Classification
- Author
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Lijian Zhou, Erya Xu, Siyuan Hao, Yuanxin Ye, and Kun Zhao
- Subjects
hyperspectral image classification ,spatial regional consistency ,SGWT ,Gaussian filtering ,Science - Abstract
Effectively using rich spatial and spectral information is the core issue of hyperspectral image (HSI) classification. The recently proposed Diverse Region-based Convolutional Neural Network (DRCNN) achieves good results by weighted averaging the features extracted from several predefined regions, thus exploring the use of spatial consistency to some extent. However, such feature-wise spatial regional consistency enhancement does not effectively address the issue of wrong classifications at the edge of regions, especially when the edge is winding and rough. To improve the feature-wise approach, Data-wise spAtial regioNal Consistency re-Enhancement (“DANCE”) is proposed. Firstly, the HSIs are decomposed once using the Spectral Graph Wavelet (SGW) to enhance the intra-class correlation. Then, the image components in different frequency domains obtained from the weight map are filtered using a Gaussian filter to “debur” the non-smooth region edge. Next, the reconstructed image is obtained based on all filtered frequency domain components using inverse SGW transform. Finally, a DRCNN is used for further feature extraction and classification. Experimental results show that the proposed method achieves the goal of pixel level re-enhancement with image spatial consistency, and can effectively improve not only the performance of the DRCNN, but also that of other feature-wise approaches. more...
- Published
- 2022
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26. Eight Years of Research Advances in Bourbon Virus, a Tick-borne Thogotovirus of the Orthomyxovirus Family
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Siyuan Hao, Kang Ning, Çağla Aksu Küz, Shane McFarlin, Fang Cheng, and Jianming Qiu
- Subjects
Infectious and parasitic diseases ,RC109-216 ,Veterinary medicine ,SF600-1100 - Abstract
Bourbon virus (BRBV) was first isolated from a blood sample collected from a male patient living in Bourbon County, Kansas, during the spring of 2014. The patient later died because of complications associated with multiorgan failure. Several deaths due to BRBV infection have since been reported in the United States, and misdiagnosed cases are often undercounted. BRBV is a member of the genus Thogotovirus of the Orthomyxoviridae family, and is transmitted through the Lone Star tick, Amblyomma americanum , in North America. Currently, no specific antiviral agents or vaccines are available to treat or prevent BRBV infection. Several small-molecular compounds have been identified to effectively inhibit BRBV infection of in vitro cell cultures at the single- or sub-micromolar level. Favipiravir, an RNA-dependent RNA polymerase inhibitor, has been found to prevent death in type I interferon receptor knockout mice with BRBV infection. more...
- Published
- 2022
- Full Text
- View/download PDF
27. Two-Stream Swin Transformer with Differentiable Sobel Operator for Remote Sensing Image Classification
- Author
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Siyuan Hao, Bin Wu, Kun Zhao, Yuanxin Ye, and Wei Wang
- Subjects
remote sensing ,scene classification ,deep learning ,swin transformer ,feature fusion ,edge detection ,Science - Abstract
Remote sensing (RS) image classification has attracted much attention recently and is widely used in various fields. Different to natural images, the RS image scenes consist of complex backgrounds and various stochastically arranged objects, thus making it difficult for networks to focus on the target objects in the scene. However, conventional classification methods do not have any special treatment for remote sensing images. In this paper, we propose a two-stream swin transformer network (TSTNet) to address these issues. TSTNet consists of two streams (i.e., original stream and edge stream) which use both the deep features of the original images and the ones from the edges to make predictions. The swin transformer is used as the backbone of each stream given its good performance. In addition, a differentiable edge Sobel operator module (DESOM) is included in the edge stream which can learn the parameters of Sobel operator adaptively and provide more robust edge information that can suppress background noise. Experimental results on three publicly available remote sensing datasets show that our TSTNet achieves superior performance over the state-of-the-art (SOTA) methods. more...
- Published
- 2022
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- View/download PDF
28. Hyperspectral Image Classification Based on Fusion of Guided Filter and Domain Transform Interpolated Convolution Filter
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Jianshang Liao, Liguo Wang, Siyuan Hao, and Genping Zhao
- Subjects
Environmental sciences ,GE1-350 ,Technology - Abstract
In recent years, the spatial texture features obtained by filtering have become a hot research topic to improve hyperspectral image classification, but spatial correlation information is often lost in spatial texture information extraction. To solve this problem, a spectral-spatial classification method based on guided filtering and by the algorithm Large Margin Distribution Machine (LDM) is proposed. More specifically, the spatial texture features can be extracted by a Guided filter (GDF) from hyperspectral images whose dimensionality is reduced by a Principal Component Analysis (PCA). Spatial correlation features of the hyperspectral image are then obtained using a Domain Transform Interpolated Convolution Filter. The last step is to fuse spatial texture features and correlation features for classification by LDM. The experimental results using the actual hyperspectral image indicate that the proposed GDFDTICF-LDM method is superior to other classification methods, such as the original Support Vector Machine (SVM) with raw spectral features, dimensionality reduction features and spatial-spectral information, methods of edge-preserving filter and recursive filter, and LDM-based methods. more...
- Published
- 2018
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29. Experimental Study of Oblique Pedestrian Streams
- Author
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Lishan Sun, Qingsheng Gong, Siyuan Hao, Chao Wang, and Yanyan Chen
- Subjects
rail transit ,intersecting pedestrian streams ,intersecting angle ,pedestrian experiment ,Transportation engineering ,TA1001-1280 - Abstract
The intersecting of pedestrian streams is a common phenomenon which would lead to the pedestrian deceleration, stopping, and even threat to the safety of walking. The organization of pedestrian flow is a critical factor which influences the intersection traffic. The aim of this paper is to study the characteristics of oblique pedestrian streams by a set of pedestrian experiments. Two groups of experiment participants, three volume levels and five intersecting angles were tested. The qualitative analysis and quantitative analysis methods were applied to find out the relationship between the pedestrian streams angle and pedestrian characteristics. The results indicated that the mean and median speed, exit traffic efficiency decreased initially and increased afterwards with the increase of intersecting angles when the volume was 1,000 p/h/m and 3,000 p/h/m, while the speed standard deviation changing inversely. However, these four factors show the opposite variation tendency in volume 5,000 p/h/m. Meanwhile, the quadratic function was selected to fit them. It is found that the worst speeds of pedestrian streams were 131° and 122° in volume 1,000 p/h/m and 3,000 p/h/m, respectively, and the greatest influence on pedestrian streams was 125° in volume 5,000 p/h/m. The results of this research can help establish the foundation for the organization and optimization of intersecting pedestrian streams. more...
- Published
- 2018
- Full Text
- View/download PDF
30. Improving Remote Sensing Image Super-Resolution Mapping Based on the Spatial Attraction Model by Utilizing the Pansharpening Technique
- Author
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Peng Wang, Gong Zhang, Siyuan Hao, and Liguo Wang
- Subjects
remote sensing image ,super-resolution mapping ,spatial attraction model ,pansharpening technique ,Science - Abstract
The spatial distribution information of remote sensing images can be derived by the super-resolution mapping (SRM) technique. Super-resolution mapping, based on the spatial attraction model (SRMSAM), has been an important SRM method, due to its simplicity and explicit physical meanings. However, the resolution of the original remote sensing image is coarse, and the existing SRMSAM cannot take full advantage of the spatial⁻spectral information from the original image. To utilize more spatial⁻spectral information, improving remote sensing image super-resolution mapping based on the spatial attraction model by utilizing the pansharpening technique (SRMSAM-PAN) is proposed. In SRMSAM-PAN, a novel processing path, named the pansharpening path, is added to the existing SRMSAM. The original coarse remote sensing image is first fused with the high-resolution panchromatic image from the same area by the pansharpening technique in the novel pansharpening path, and the improved image is unmixed to obtain the novel fine-fraction images. The novel fine-fraction images from the pansharpening path and the existing fine-fraction images from the existing path are then integrated to produce finer-fraction images with more spatial⁻spectral information. Finally, the values predicted from the finer-fraction images are utilized to allocate class labels to all subpixels, to achieve the final mapping result. Experimental results show that the proposed SRMSAM-PAN can obtain a higher mapping accuracy than the existing SRMSAM methods. more...
- Published
- 2019
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31. Semi-Supervised Classification of Hyperspectral Images Based on Extended Label Propagation and Rolling Guidance Filtering
- Author
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Binge Cui, Xiaoyun Xie, Siyuan Hao, Jiandi Cui, and Yan Lu
- Subjects
spectral-spatial classification ,label propagation ,superpixel ,semi-supervised learning ,rolling guidance filtering (RGF) ,graph ,hyperspectral image ,Science - Abstract
Semi-supervised classification methods result in higher performance for hyperspectral images, because they can utilize the relationship between unlabeled samples and labeled samples to obtain pseudo-labeled samples. However, how generating an effective training sample set is a major challenge for semi-supervised methods, In this paper, we propose a novel semi-supervised classification method based on extended label propagation (ELP) and a rolling guidance filter (RGF) called ELP-RGF, in which ELP is a new two-step process to make full use of unlabeled samples. The first step is to implement the graph-based label propagation algorithm to propagate the label information from labeled samples to the neighboring unlabeled samples. This is then followed by the second step, which uses superpixel propagation to assign the same labels to all pixels within the superpixels that are generated by the image segmentation method, so that some labels wrongly labeled by the above step can be modified. As a result, so obtained pseudo-labeled samples could be used to improve the performance of the classifier. Subsequently, an effective feature extraction method, i.e., RGF is further used to remove the noise and the small texture structures to optimize the features of the initial hyperspectral image. Finally, these produced initial labeled samples and high-confidence pseudo-labeled samples are used as a training set for support vector machine (SVM). The experimental results show that the proposed method can produce better classification performance for three widely-used real hyperspectral datasets, particularly when the number of training samples is relatively small. more...
- Published
- 2018
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- View/download PDF
32. Prime Label Learning From Multilabel Aerial Image: A Novel Weakly Supervised Task.
- Author
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Kun Zhao, Shiwen Zeng, Lijian Zhou, Tingyuan Nie, and Siyuan Hao
- Published
- 2024
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- View/download PDF
33. Intelligent Guidance Method and System for Driving Safety in Curves Under Slippery and Low Visibility Conditions.
- Author
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Siyuan Hao, Nale Zhao, Ni Zhou, Jiahui Li, Ruiche Liu, and Chengwu Jiao
- Published
- 2023
- Full Text
- View/download PDF
34. Research on Road Surface Slippery State Dynamic Evaluation Model of Long Highway Tunnels.
- Author
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Ruiche Liu, Chengwu Jiao, Nale Zhao, Ming Sun, Jiahui Li, and Siyuan Hao
- Published
- 2023
- Full Text
- View/download PDF
35. Hybrid Heterogeneous Graph Neural Networks for Fund Performance Prediction.
- Author
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Siyuan Hao, Le Dai, Le Zhang 0010, Shengming Zhang, Chao Wang 0086, Chuan Qin 0002, and Hui Xiong 0001
- Published
- 2023
- Full Text
- View/download PDF
36. Generative Adversarial Network With Transformer for Hyperspectral Image Classification.
- Author
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Siyuan Hao, Yufeng Xia, and Yuanxin Ye
- Published
- 2023
- Full Text
- View/download PDF
37. Spectral and Spatial Feature Fusion for Hyperspectral Image Classification.
- Author
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Siyuan Hao, Yufeng Xia, Lijian Zhou, Yuanxin Ye, and Wei Wang 0108
- Published
- 2022
- Full Text
- View/download PDF
38. A Multiscale Framework With Unsupervised Learning for Remote Sensing Image Registration.
- Author
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Yuanxin Ye, Tengfeng Tang, Bai Zhu, Chao Yang 0028, Bo Li 0090, and Siyuan Hao
- Published
- 2022
- Full Text
- View/download PDF
39. Bounding Boxes Are All We Need: Street View Image Classification via Context Encoding of Detected Buildings.
- Author
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Kun Zhao, Yongkun Liu, Siyuan Hao, Shaoxing Lu, Hongbin Liu, and Lijian Zhou
- Published
- 2022
- Full Text
- View/download PDF
40. Security and Reliability Analysis of Relay Selection in Cognitive Relay Networks.
- Author
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Enyu Li, Long Ma 0010, Siyuan Hao, and Xinjie Wang
- Published
- 2022
- Full Text
- View/download PDF
41. A Novel Keypoint Detector Combining Corners and Blobs for Remote Sensing Image Registration.
- Author
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Yuanxin Ye, Mengmeng Wang, Siyuan Hao, and Qing Zhu
- Published
- 2021
- Full Text
- View/download PDF
42. Geometry-Aware Deep Recurrent Neural Networks for Hyperspectral Image Classification.
- Author
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Siyuan Hao, Wei Wang 0108, and Mathieu Salzmann
- Published
- 2021
- Full Text
- View/download PDF
43. Face recognition based on local binary pattern and improved Pairwise-constrained Multiple Metric Learning.
- Author
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Lijian Zhou, Hui Wang, Shanshan Lin, Siyuan Hao, and Zhe-Ming Lu 0001
- Published
- 2020
- Full Text
- View/download PDF
44. Outage Analysis of Decode-and-Forward Two-Way Relay Selection With Different Coding and Decoding Schemes.
- Author
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Enyu Li, Xuhu Wang, Zeju Wu, Siyuan Hao, and Yunquan Dong
- Published
- 2019
- Full Text
- View/download PDF
45. Combining multi-wavelet and CNN for palmprint recognition against noise and misalignment.
- Author
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Lijian Zhou, Han Guo, Shanshan Lin, Siyuan Hao, and Kun Zhao
- Published
- 2019
- Full Text
- View/download PDF
46. pH-responsive nanocatalyst for enhancing cancer therapy via H2O2 homeostasis disruption and disulfiram sensitization
- Author
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Jingjie Zuo, Siyuan Hao, Wenqiu Li, Haowu Huang, Mingxing Liu, and Huiling Guo
- Subjects
Biomedical Engineering ,General Materials Science ,General Chemistry ,General Medicine - Abstract
Due to the powerful redox homeostasis and inefficiency of monotherapy, chemodynamic therapy (CDT) is clinically limited.
- Published
- 2023
- Full Text
- View/download PDF
47. Tumor microenvironment (TME)-modulating nanoreactor for multiply enhanced chemodynamic therapy synergized with chemotherapy, starvation, and photothermal therapy
- Author
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Siyuan Hao, Jingjie Zuo, Haowu Huang, Wenqiu Li, Huiling Guo, Mingxing Liu, Hongda Zhu, and Hongmei Sun
- Subjects
Biomedical Engineering ,General Materials Science ,General Chemistry ,General Medicine - Abstract
The combination of chemotherapy (CT) and chemodynamic therapy (CDT) via nanoscale drug delivery systems has great potential for tumor therapy.
- Published
- 2023
- Full Text
- View/download PDF
48. A Deep Network Architecture for Super-Resolution-Aided Hyperspectral Image Classification With Classwise Loss.
- Author
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Siyuan Hao, Wei Wang 0108, Yuanxin Ye, Enyu Li, and Lorenzo Bruzzone
- Published
- 2018
- Full Text
- View/download PDF
49. Two-Stream Deep Architecture for Hyperspectral Image Classification.
- Author
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Siyuan Hao, Wei Wang 0108, Yuanxin Ye, Tingyuan Nie, and Lorenzo Bruzzone
- Published
- 2018
- Full Text
- View/download PDF
50. Palm-print Recognition based on CNN against Rotation and Noise.
- Author
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Lijian Zhou, Zuowei Wang, Han Guo, Siyuan Hao, and Zhao Zhuo
- Published
- 2018
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