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6,026 results on '"Wei, Zhen"'

1. Seed-TTS: A Family of High-Quality Versatile Speech Generation Models

Author

Anastassiou, Philip, Chen, Jiawei, Chen, Jitong, Chen, Yuanzhe, Chen, Zhuo, Chen, Ziyi, Cong, Jian, Deng, Lelai, Ding, Chuang, Gao, Lu, Gong, Mingqing, Huang, Peisong, Huang, Qingqing, Huang, Zhiying, Huo, Yuanyuan, Jia, Dongya, Li, Chumin, Li, Feiya, Li, Hui, Li, Jiaxin, Li, Xiaoyang, Li, Xingxing, Liu, Lin, Liu, Shouda, Liu, Sichao, Liu, Xudong, Liu, Yuchen, Liu, Zhengxi, Lu, Lu, Pan, Junjie, Wang, Xin, Wang, Yuping, Wang, Yuxuan, Wei, Zhen, Wu, Jian, Yao, Chao, Yang, Yifeng, Yi, Yuanhao, Zhang, Junteng, Zhang, Qidi, Zhang, Shuo, Zhang, Wenjie, Zhang, Yang, Zhao, Zilin, Zhong, Dejian, and Zhuang, Xiaobin

Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Sound
Abstract

We introduce Seed-TTS, a family of large-scale autoregressive text-to-speech (TTS) models capable of generating speech that is virtually indistinguishable from human speech. Seed-TTS serves as a foundation model for speech generation and excels in speech in-context learning, achieving performance in speaker similarity and naturalness that matches ground truth human speech in both objective and subjective evaluations. With fine-tuning, we achieve even higher subjective scores across these metrics. Seed-TTS offers superior controllability over various speech attributes such as emotion and is capable of generating highly expressive and diverse speech for speakers in the wild. Furthermore, we propose a self-distillation method for speech factorization, as well as a reinforcement learning approach to enhance model robustness, speaker similarity, and controllability. We additionally present a non-autoregressive (NAR) variant of the Seed-TTS model, named $\text{Seed-TTS}_\text{DiT}$, which utilizes a fully diffusion-based architecture. Unlike previous NAR-based TTS systems, $\text{Seed-TTS}_\text{DiT}$ does not depend on pre-estimated phoneme durations and performs speech generation through end-to-end processing. We demonstrate that this variant achieves comparable performance to the language model-based variant and showcase its effectiveness in speech editing. We encourage readers to listen to demos at \url{https://bytedancespeech.github.io/seedtts_tech_report}.

Published
2024

2. Heavy baryons in the relativized quark model with chromodynamics

Author

Weng, Xin-Zhen, Deng, Wei-Zhen, and Zhu, Shi-Lin

Subjects
High Energy Physics - Phenomenology, High Energy Physics - Experiment, High Energy Physics - Lattice
Abstract

Following the work of Capstick and Isgur [\href{https://doi.org/10.1103/PhysRevD.34.2809}{Phys.~Rev.~D~34,~2809~(1986)}], we systematically study the mass spectrum of the heavy baryons in the relativized quark potential model with chromodynamics. Besides the original Godfrey-Isgur (GI) model, we also adopt a modified GI model which replaces the linear confinement by a screened one. The two models give similar results in our work. All heavy baryons observed so far can be explained as three-quark states. In particular, we identify the $\Omega_{c}(3000)$/$\Omega_{b}(6316)$, $\Omega_{c}(3050)$/$\Omega_{b}(6330)$, $\Omega_{c}(3065)$/$\Omega_{b}(6340)$ and $\Omega_{c}(3090)$/$\Omega_{b}(6350)$ states as the $p_{\lambda}$ excitations with quantum numbers $1/2^{-}$, $3/2^{-}$, $3/2^{-}$ and $5/2^{-}$. The $\Omega_{c}(3120)$ is a $3/2^{-}$ state with the $p_{\rho}$ excitation, whose bottom partner is predicted to be $\Omega_{b}(6446/6457,3/2^{-})$. The higher state $\Omega_{c}(3188)$ is the $2s_{\lambda}$ excitation with quantum numbers $1/2^{+}$, and $\Omega_{c}(3327)$ is a $d_{\lambda}$ excitation with quantum numbers $3/2^{+}$ or $5/2^{+}$. In addition, the $\Lambda_{c}(2940)$ with quantum numbers $J^{P}=3/2^{-}$ could be explained as the $p_{\rho}$ excitation., Comment: 20 pages, 10 figures

Published
2024

3. High-resolution power equipment recognition based on improved self-attention

Author

Zhang, Siyi, Liu, Cheng, Li, Xiang, Zhai, Xin, Wei, Zhen, Li, Sizhe, and Ma, Xun

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

The current trend of automating inspections at substations has sparked a surge in interest in the field of transformer image recognition. However, due to restrictions in the number of parameters in existing models, high-resolution images can't be directly applied, leaving significant room for enhancing recognition accuracy. Addressing this challenge, the paper introduces a novel improvement on deep self-attention networks tailored for this issue. The proposed model comprises four key components: a foundational network, a region proposal network, a module for extracting and segmenting target areas, and a final prediction network. The innovative approach of this paper differentiates itself by decoupling the processes of part localization and recognition, initially using low-resolution images for localization followed by high-resolution images for recognition. Moreover, the deep self-attention network's prediction mechanism uniquely incorporates the semantic context of images, resulting in substantially improved recognition performance. Comparative experiments validate that this method outperforms the two other prevalent target recognition models, offering a groundbreaking perspective for automating electrical equipment inspections.

Published
2023

4. Image Recognition of Oil Leakage Area Based on Logical Semantic Discrimination

Author

Lin, Weiying, Liu, Che, Zhang, Xin, Wei, Zhen, Li, Sizhe, and Ma, Xun

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Implementing precise detection of oil leaks in peak load equipment through image analysis can significantly enhance inspection quality and ensure the system's safety and reliability. However, challenges such as varying shapes of oil-stained regions, background noise, and fluctuating lighting conditions complicate the detection process. To address this, the integration of logical rule-based discrimination into image recognition has been proposed. This approach involves recognizing the spatial relationships among objects to semantically segment images of oil spills using a Mask RCNN network. The process begins with histogram equalization to enhance the original image, followed by the use of Mask RCNN to identify the preliminary positions and outlines of oil tanks, the ground, and areas of potential oil contamination. Subsequent to this identification, the spatial relationships between these objects are analyzed. Logical rules are then applied to ascertain whether the suspected areas are indeed oil spills. This method's effectiveness has been confirmed by testing on images captured from peak power equipment in the field. The results indicate that this approach can adeptly tackle the challenges in identifying oil-contaminated areas, showing a substantial improvement in accuracy compared to existing methods.

Published
2023

6. Dissection of a rapidly evolving wheat resistance gene cluster by long-read genome sequencing accelerated the cloning of Pm69

Author

Li, Yinghui, Wei, Zhen-Zhen, Sela, Hanan, Govta, Liubov, Klymiuk, Valentyna, Roychowdhury, Rajib, Chawla, Harmeet Singh, Ens, Jennifer, Wiebe, Krystalee, Bocharova, Valeria, Ben-David, Roi, Pawar, Prerna B, Zhang, Yuqi, Jaiwar, Samidha, Molnár, István, Doležel, Jaroslav, Coaker, Gitta, Pozniak, Curtis J, and Fahima, Tzion

Subjects
Plant Biology, Biological Sciences, Bioinformatics and Computational Biology, Genetics, Biotechnology, Human Genome, Triticum, Genes, Plant, Chromosome Mapping, Cloning, Molecular, Multigene Family, Plant biology
Abstract

Gene cloning in repeat-rich polyploid genomes remains challenging. Here, we describe a strategy for overcoming major bottlenecks in cloning of the powdery mildew resistance gene (R-gene) Pm69 derived from tetraploid wild emmer wheat. A conventional positional cloning approach was not effective owing to suppressed recombination. Chromosome sorting was compromised by insufficient purity. A Pm69 physical map, constructed by assembling Oxford Nanopore Technology (ONT) long-read genome sequences, revealed a rapidly evolving nucleotide-binding leucine-rich repeat (NLR) R-gene cluster with structural variations. A single candidate NLR was identified by anchoring RNA sequencing reads from susceptible mutants to ONT contigs and was validated by virus-induced gene silencing. Pm69 is likely a newly evolved NLR and was discovered in only one location across the wild emmer wheat distribution range in Israel. Pm69 was successfully introgressed into cultivated wheat, and a diagnostic molecular marker was used to accelerate its deployment and pyramiding with other R-genes.

Published
2024

8. Automatic Parameterization for Aerodynamic Shape Optimization via Deep Geometric Learning

Author

Wei, Zhen, Fua, Pascal, and Bauerheim, Michaël

Subjects
Computer Science - Computer Vision and Pattern Recognition, Physics - Fluid Dynamics
Abstract

We propose two deep learning models that fully automate shape parameterization for aerodynamic shape optimization. Both models are optimized to parameterize via deep geometric learning to embed human prior knowledge into learned geometric patterns, eliminating the need for further handcrafting. The Latent Space Model (LSM) learns a low-dimensional latent representation of an object from a dataset of various geometries, while the Direct Mapping Model (DMM) builds parameterization on the fly using only one geometry of interest. We also devise a novel regularization loss that efficiently integrates volumetric mesh deformation into the parameterization model. The models directly manipulate the high-dimensional mesh data by moving vertices. LSM and DMM are fully differentiable, enabling gradient-based, end-to-end pipeline design and plug-and-play deployment of surrogate models or adjoint solvers. We perform shape optimization experiments on 2D airfoils and discuss the applicable scenarios for the two models., Comment: 15 pages, to be appeared at AIAA Aviation Forum 2023

Published
2023

9. Research Progress on Fucoidan-Degrading Enzymes

Author

WEI Zhen, CHEN Jinling, YANG Jie

Subjects
fucoidan-degrading enzymes, fucoidan, fucosidase, structure and function, application, Food processing and manufacture, TP368-456
Abstract

Fucoidan-degrading enzymes are glycoside hydrolases that hydrolyze fucoidan into low molecular mass fucosan with biological activity or other products. The enzymes have great application value in the preparation of active fucoidan oligosaccharides, biopharmaceutics and disease diagnosis. In this article, the sources, properties, modes of action, structures and applications of fucoidan-degrading enzymes are reviewed, revealing that fucoidan-degrading enzymes are mainly derived from marine microorganisms and marine invertebrates and that the enzymatic properties, substrate specificity, molecular structures and catalytic mechanisms of fucoidan-degrading enzymes vary significantly depending on the species source. Different types of fucoidan-degrading enzymes catalyze different sites of complex fucoidans producing fucoidan oligosaccharides with antioxidant, anti-tumor, anti-thrombotic or other special activities. Therefore, the utilization of fucoidan-degrading enzymes in the preparation of drugs and functional foods has gradually become a research focus in the application field of polysaccharides. This article provides theoretical support for further research on fucoidan-degrading enzymes, and also provides references for the effective development of fucoidan oligosaccharides with special biological functions.

Published
2024
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10. Robust Outlier Rejection for 3D Registration with Variational Bayes

Author

Jiang, Haobo, Dang, Zheng, Wei, Zhen, Xie, Jin, Yang, Jian, and Salzmann, Mathieu

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Learning-based outlier (mismatched correspondence) rejection for robust 3D registration generally formulates the outlier removal as an inlier/outlier classification problem. The core for this to be successful is to learn the discriminative inlier/outlier feature representations. In this paper, we develop a novel variational non-local network-based outlier rejection framework for robust alignment. By reformulating the non-local feature learning with variational Bayesian inference, the Bayesian-driven long-range dependencies can be modeled to aggregate discriminative geometric context information for inlier/outlier distinction. Specifically, to achieve such Bayesian-driven contextual dependencies, each query/key/value component in our non-local network predicts a prior feature distribution and a posterior one. Embedded with the inlier/outlier label, the posterior feature distribution is label-dependent and discriminative. Thus, pushing the prior to be close to the discriminative posterior in the training step enables the features sampled from this prior at test time to model high-quality long-range dependencies. Notably, to achieve effective posterior feature guidance, a specific probabilistic graphical model is designed over our non-local model, which lets us derive a variational low bound as our optimization objective for model training. Finally, we propose a voting-based inlier searching strategy to cluster the high-quality hypothetical inliers for transformation estimation. Extensive experiments on 3DMatch, 3DLoMatch, and KITTI datasets verify the effectiveness of our method., Comment: Accepted by CVPR2023

Published
2023

11. Null and missense mutations of ERI1 cause a recessive phenotypic dichotomy in humans.

Author

Guo, Long, Salian, Smrithi, Xue, Jing-Yi, Rath, Nicola, Rousseau, Justine, Kim, Hyunyun, Ehresmann, Sophie, Moosa, Shahida, Nakagawa, Norio, Kuroda, Hiroshi, Clayton-Smith, Jill, Wang, Juan, Wang, Zheng, Banka, Siddharth, Jackson, Adam, Zhang, Yan-Min, Wei, Zhen-Jie, Hüning, Irina, Brunet, Theresa, Ohashi, Hirofumi, Thomas, Molly, Bupp, Caleb, Miyake, Noriko, Matsumoto, Naomichi, Mendoza-Londono, Roberto, Costain, Gregory, Hahn, Gabriele, Di Donato, Nataliya, Yigit, Gökhan, Yamada, Takahiro, Nishimura, Gen, Ansel, Karl, Wollnik, Bernd, Hrabě de Angelis, Martin, Mégarbané, André, Rosenfeld, Jill, Heissmeyer, Vigo, Ikegawa, Shiro, and Campeau, Philippe

Subjects
ERI1, exoribonuclease, ribosomopathy, short stature, skeletal dysplasia, spondyloepimetaphyseal dysplasia, Humans, Exoribonucleases, Histones, Mutation, Missense, RNA, Ribosomal, 5.8S, RNA, RNA, Messenger
Abstract

ERI1 is a 3-to-5 exoribonuclease involved in RNA metabolic pathways including 5.8S rRNA processing and turnover of histone mRNAs. Its biological and medical significance remain unclear. Here, we uncover a phenotypic dichotomy associated with bi-allelic ERI1 variants by reporting eight affected individuals from seven unrelated families. A severe spondyloepimetaphyseal dysplasia (SEMD) was identified in five affected individuals with missense variants but not in those with bi-allelic null variants, who showed mild intellectual disability and digital anomalies. The ERI1 missense variants cause a loss of the exoribonuclease activity, leading to defective trimming of the 5.8S rRNA 3 end and a decreased degradation of replication-dependent histone mRNAs. Affected-individual-derived induced pluripotent stem cells (iPSCs) showed impaired in vitro chondrogenesis with downregulation of genes regulating skeletal patterning. Our study establishes an entity previously unreported in OMIM and provides a model showing a more severe effect of missense alleles than null alleles within recessive genotypes, suggesting a key role of ERI1-mediated RNA metabolism in human skeletal patterning and chondrogenesis.

Published
2023

14. Joint Optimization of PAoI and Queue Backlog with Energy Constraints in LoRa Gateway Systems

Author

Shi, Lei, Ji, Rui, Wei, Zhen, Feng, Shilong, Li, Zhehao, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin, Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Gao, Honghao, editor, Wang, Xinheng, editor, and Voros, Nikolaos, editor

Published
2024
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15. Study on Mixing Characteristics of the Heavy Oil and the Light Oil Based on Experiment and Numerical Simulation

Author

Wang, Yijie, Xie, Yan, Xu, Zhenkang, Wei, Zhen, Zhang, Yu, Qi, Jingwei, Huang, Qiyu, Ceccarelli, Marco, Series Editor, Agrawal, Sunil K., Advisory Editor, Corves, Burkhard, Advisory Editor, Glazunov, Victor, Advisory Editor, Hernández, Alfonso, Advisory Editor, Huang, Tian, Advisory Editor, Jauregui Correa, Juan Carlos, Advisory Editor, Takeda, Yukio, Advisory Editor, and Li, Shaofan, editor

Published
2024
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16. Study on the Adhesion of UV Ink in Tinplate Printing

Author

Wu, Zhenxing, Wei, Zhen, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Song, Huihui, editor, Xu, Min, editor, Yang, Li, editor, Zhang, Linghao, editor, and Yan, Shu, editor

Published
2024
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17. Experience and Inspiration in the Construction of Advanced Enterprise Technology Standard System at Domestic and International

Author

Zhang, Shenzhi, Huang, Xinpei, Cong, Pengwei, Wei, Zhen, Xue, Jingwei, Sun, Nuoling, Appolloni, Andrea, Series Editor, Caracciolo, Francesco, Series Editor, Ding, Zhuoqi, Series Editor, Gogas, Periklis, Series Editor, Huang, Gordon, Series Editor, Nartea, Gilbert, Series Editor, Ngo, Thanh, Series Editor, Striełkowski, Wadim, Series Editor, Tehseen, Shehnaz, editor, Ahmad, Mohd Naseem Niaz, editor, and Afroz, Rafia, editor

Published
2024
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18. Research on the Background of Effectiveness Evaluation of New Power System Technical Standards System

Author

Lv, Chao, Cong, Pengwei, Zhang, Pengyue, Zhao, Shuning, Zhang, Jing, Wei, Zhen, Sun, Nuoling, Wei, Xin, Appolloni, Andrea, Series Editor, Caracciolo, Francesco, Series Editor, Ding, Zhuoqi, Series Editor, Gogas, Periklis, Series Editor, Huang, Gordon, Series Editor, Nartea, Gilbert, Series Editor, Ngo, Thanh, Series Editor, Striełkowski, Wadim, Series Editor, Tehseen, Shehnaz, editor, Ahmad, Mohd Naseem Niaz, editor, and Afroz, Rafia, editor

Published
2024
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19. Research on the Benefit Evaluation Method for the Implementation of the New Power System Technical Standards System

Author

Lv, Chao, Cong, Pengwei, Zhang, Pengyue, Zhao, Shuning, Zhang, Jing, Wei, Zhen, Sun, Nuoling, Wei, Xin, Appolloni, Andrea, Series Editor, Caracciolo, Francesco, Series Editor, Ding, Zhuoqi, Series Editor, Gogas, Periklis, Series Editor, Huang, Gordon, Series Editor, Nartea, Gilbert, Series Editor, Ngo, Thanh, Series Editor, Striełkowski, Wadim, Series Editor, Tehseen, Shehnaz, editor, Ahmad, Mohd Naseem Niaz, editor, and Afroz, Rafia, editor

Published
2024
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24. The implications of single-cell RNA-seq analysis in prostate cancer: unraveling tumor heterogeneity, therapeutic implications and pathways towards personalized therapy

Author

De-Chao Feng, Wei-Zhen Zhu, Jie Wang, Deng-Xiong Li, Xu Shi, Qiao Xiong, Jia You, Ping Han, Shi Qiu, Qiang Wei, and Lu Yang

Subjects
Prostate cancer, Single-cell RNA sequencing (scRNA-seq), Tumor microenvironment, Tumor heterogeneity, Treatment resistance, Precision medicine, Medicine (General), R5-920, Military Science
Abstract

Abstract In recent years, advancements in single-cell and spatial transcriptomics, which are highly regarded developments in the current era, particularly the emerging integration of single-cell and spatiotemporal transcriptomics, have enabled a detailed molecular comprehension of the complex regulation of cell fate. The insights obtained from these methodologies are anticipated to significantly contribute to the development of personalized medicine. Currently, single-cell technology is less frequently utilized for prostate cancer compared with other types of tumors. Starting from the perspective of RNA sequencing technology, this review outlined the significance of single-cell RNA sequencing (scRNA-seq) in prostate cancer research, encompassing preclinical medicine and clinical applications. We summarize the differences between mouse and human prostate cancer as revealed by scRNA-seq studies, as well as a combination of multi-omics methods involving scRNA-seq to highlight the key molecular targets for the diagnosis, treatment, and drug resistance characteristics of prostate cancer. These studies are expected to provide novel insights for the development of immunotherapy and other innovative treatment strategies for castration-resistant prostate cancer. Furthermore, we explore the potential clinical applications stemming from other single-cell technologies in this review, paving the way for future research in precision medicine.

Published
2024
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25. IR2Net: Information Restriction and Information Recovery for Accurate Binary Neural Networks

Author

Xue, Ping, Lu, Yang, Chang, Jingfei, Wei, Xing, and Wei, Zhen

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Weight and activation binarization can efficiently compress deep neural networks and accelerate model inference, but cause severe accuracy degradation. Existing optimization methods for binary neural networks (BNNs) focus on fitting full-precision networks to reduce quantization errors, and suffer from the trade-off between accuracy and computational complexity. In contrast, considering the limited learning ability and information loss caused by the limited representational capability of BNNs, we propose IR$^2$Net to stimulate the potential of BNNs and improve the network accuracy by restricting the input information and recovering the feature information, including: 1) information restriction: for a BNN, by evaluating the learning ability on the input information, discarding some of the information it cannot focus on, and limiting the amount of input information to match its learning ability; 2) information recovery: due to the information loss in forward propagation, the output feature information of the network is not enough to support accurate classification. By selecting some shallow feature maps with richer information, and fusing them with the final feature maps to recover the feature information. In addition, the computational cost is reduced by streamlining the information recovery method to strike a better trade-off between accuracy and efficiency. Experimental results demonstrate that our approach still achieves comparable accuracy even with $ \sim $10x floating-point operations (FLOPs) reduction for ResNet-18. The models and code are available at https://github.com/pingxue-hfut/IR2Net., Comment: 11 pages, 8 figures

Published
2022

26. Distribution and dynamic changes of Huanglongbing pathogen in its insect vector Diaphorina citri

Author

Chang-Fei Guo, Wei-Zhen Kong, Marguerite Mukangango, Yu-Wei Hu, Yu-Tao Liu, Wen Sang, and Bao-Li Qiu

Subjects
Huanglongbing, CLAS, Diaphorina citri, infection, distribution, dynamic, Microbiology, QR1-502
Abstract

The Asian citrus psyllid (ACP) Diaphorina citri Kuwayama is the leading vector of Candidatus Liberibacter asiaticus (CLas), the causative agent of citrus Huanglongbing (HLB) disease. The distribution and dynamics of CLas within ACP are critical to understanding how the transmission, spread and infection of CLas occurs within its host vector in nature. In this study, the distribution and titer changes of CLas in various tissues of ACP 5th instar nymphs and adults were examined by fluorescence in situ hybridization (FISH) and real-time quantitative PCR (qPCR) techniques. Results demonstrated that 100% of ACP 5th instar nymphs and adults were infected with CLas following feeding on infected plants, and that CLas had widespread distribution in most of the tissues of ACP. The titers of CLas within the midgut, salivary glands and hemolymph tissues were the highest in both 5th instar nymphs and adults. When compared with adults, the titers of CLas in these three tissues of 5th instar nymphs were significantly higher, while in the mycetome, ovary and testes they were significantly lower than those of adults. FISH visualization further confirmed these findings. Dynamic analysis of CLas demonstrated that it was present across all the developmental ages of ACP adults. There was a discernible upward trend in the presence of CLas with advancing age in most tissues of ACP adults, including the midgut, hemolymph, salivary glands, foot, head, cuticula and muscle. Our findings have significant implications for the comprehensive understanding of the transmission, dissemination and infestation of CLas, which is of much importance for developing novel strategies to halt the spread of CLas, and therefore contribute to the efficient prevention and control of HLB.

Published
2024
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27. Real-world efficacy, roll-out and uptake of intramuscular tixagevimab/cilgavimab as COVID-19 pre-exposure prophylaxis in people with multiple sclerosis and neuroimmunological conditions during the COVID-19 pandemic

Author

Helmut Butzkueven, Wei Zhen Yeh, Mastura Monif, Robb Wesselingh, Louise Rath, Olga Skibina, Cassie Nesbitt, Nabil Seery, Anneke van der Walt, Francesca Bridge, Michael Zhong, Tracie Tan, Angie Roldan, and YiChao Foong

Subjects
Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Background In Australia, tixagevimab/cilgavimab 150 mg/150 mg was a government-funded pre-exposure prophylaxis for COVID-19 people with multiple sclerosis (pwMS) and other neuroimmunological conditions (pwNIc) treated with anti-CD20 antibodies or sphingosine-1-phosphate receptor modulators were eligible.Objective To analyse the roll-out, uptake and real-world efficacy of tixagevimab/cilgavimab in the prevention and severity of COVID-19. To assess compliance with uptake depending on the location of delivery.Methods We undertook a single-centre study. 440 pwMS and pwNIc were eligible. Logistic regression was used to assess predictors of COVID-19 during follow-up and to assess predictors of uptake among those who consented.Results Of the eligible pwMS and pwNIc in our service, 52.7% (233/440) requested a consultation and were included in this study. Consultation resulted in 71.7% of people (167/233) receiving the treatment. Of these, 94.0% (157/167) had received three or more COVID-19 vaccines. Among those who received a single dose of tixagevimab/cilgavimab, 19.16% (32/167) tested positive for COVID-19 during the observational window. The majority of these were on ocrelizumab (68.8% (22/32)). None of those with COVID-19 required hospitalisation or supplemental oxygen. There was no difference in odds of COVID-19 during the observation period between those who received and did not receive tixagevimab/cilgavimab (adjusted OR, aOR 2.16 (95% CI 0.82 to 6.85), p=0.43). Uptake of tixagevimab/cilgavimab was highest when offered at the hospital infusion centre (aOR 3.09 (95% CI 1.08 to 9.94) relative to referral to the local pharmacy, p=0.04).Conclusion Tixagevimab/cilgavimab administration did not protect against subsequent COVID-19 in our cohort. Compliance with uptake was influenced by administration location.

Published
2024
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31. The antennal transcriptome analysis and characterizations of odorant-binding proteins in Megachile saussurei (Hymenoptera, Megachilidae)

Author

Wei-Zhen Li, Wen-Juan Kang, Jing-Jiang Zhou, Su-Qin Shang, and Shang-Li Shi

Subjects
Megachile saussurei, Medicago sativa, Odorant-binding proteins, Transcriptome, Antennae, Biotechnology, TP248.13-248.65, Genetics, QH426-470
Abstract

Abstract Background Odorant-binding proteins (OBPs) are essential in insect’s daily behaviors mediated by olfactory perception. Megachile saussurei Radoszkowski (Hymenoptera, Megachilidae) is a principal insect pollinating alfalfa (Medicago sativa) in Northwestern China. The olfactory function have been less conducted, which provides a lot of possibilities for our research. Results Our results showed that 20 OBPs were identified in total. Multiple sequence alignment analysis indicated MsauOBPs were highly conserved with a 6-cysteine motif pattern and all belonged to the classic subfamily, coding 113-196 amino acids and sharing 41.32%-99.12% amino acid identity with known OBPs of other bees. Phylogenetic analysis indicated there were certain homologies existed among MsauOBPs and most sequences were clustered with that of Osmia cornuta (Hymenoptera, Megachilidae). Expression analysis showed the identified OBPs were mostly enriched in antennae instead of other four body parts, especially the MsauOBP2, MsauOBP3, MsauOBP4, MsauOBP8, MsauOBP11 and MsauOBP17, in which the MsauOBP2, MsauOBP4 and MsauOBP8 presented obvious tissue-biased expression pattern. Molecular docking results indicated MsauOBP4 might be the most significant protein in recognizing alfalfa flower volatile 3-Octanone, while MsauOBP13 might be the most crucial protein identifying (Z)-3-hexenyl acetate. It was also found the lysine was a momentous hydrophilic amino acid in docking simulations. Conclusion In this study, we identified and analyzed 20 OBPs of M. saussurei. The certain homology existed among these OBPs, while some degree of divergence could also be noticed, indicating the complex functions that different MsauOBPs performed. Besides, the M. saussurei and Osmia cornuta were very likely to share similar physiological functions as most of their OBPs were clustered together. MsauOBP4 might be the key protein in recognizing 3-Octanone, while MsauOBP13 might be the key protein in binding (Z)-3-hexenyl acetate. These two proteins might contribute to the alfalfa-locating during the pollination process. The relevant results may help determine the highly specific and effective attractants for M. saussurei in alfalfa pollination and reveal the molecular mechanism of odor-evoked pollinating behavior between these two species.

Published
2023
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32. Single-nucleus transcriptome sequencing reveals hepatic cell atlas in pigs

Author

Jun-Hong Zhu, Xuan-Cheng Guan, Lan-Lan Yi, Hong Xu, Qiu-Yan Li, Wen-Jie Cheng, Yu-Xiao Xie, Wei-Zhen Li, Hong-Ye Zhao, Hong-Jiang Wei, and Su-Mei Zhao

Subjects
Hepatic tissue, Single-nucleus RNA sequencing, Cell atlas, Dahe pigs, Dahe black pigs, Biotechnology, TP248.13-248.65, Genetics, QH426-470
Abstract

Abstract Background As the largest substantive organ of animals, the liver plays an essential role in the physiological processes of digestive metabolism and immune defense. However, the cellular composition of the pig liver remains poorly understood. This investigation used single-nucleus RNA sequencing technology to identify cell types from liver tissues of pigs, providing a theoretical basis for further investigating liver cell types in pigs. Results The analysis revealed 13 cells clusters which were further identified 7 cell types including endothelial cells, T cells, hepatocytes, Kupffer cells, stellate cells, B cells, and cholangiocytes. The dominant cell types were endothelial cells, T cells and hepatocytes in the liver tissue of Dahe pigs and Dahe black pigs, which accounts for about 85.76% and 82.74%, respectively. The number of endothelial cells was higher in the liver tissue of Dahe pigs compared to Dahe black pigs, while the opposite tendency was observed for T cells. Moreover, functional enrichment analysis demonstrated that the differentially expressed genes in pig hepatic endothelial cells were significantly enriched in the protein processing in endoplasmic reticulum, MAPK signaling pathway, and FoxO signaling pathway. Functional enrichment analysis demonstrated that the differentially expressed genes in pig hepatic T cells were significantly enriched in the thyroid hormone signaling pathway, B cell receptor signaling pathway, and focal adhesion. Functional enrichment analysis demonstrated that the differentially expressed genes in pig hepatic hepatocytes were significantly enriched in the metabolic pathways. Conclusions In summary, this study provides a comprehensive cell atlas of porcine hepatic tissue. The number, gene expression level and functional characteristics of each cell type in pig liver tissue varied between breeds.

Published
2023
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46. Assessing caregiver burden in advanced kidney disease: protocol for a systematic review of the measurement properties of instruments and tools

Author

Yee Wei Lim, Nan Luo, Amartya Mukhopadhyay, Jason Phua, Priyanka Khatri, Ravi Shankar, Leanne Leong, Geraldine Yu-Xuan Teo, Jason Choo, Horng Ruey Chua, Gim-Gee Teng, and Wei Zhen Hong

Subjects
Medicine
Abstract

Introduction Caregiver burden is a significant issue in the care of patients with advanced kidney disease. Its assessment is crucial for evaluating the needs of caregivers and for the development of interventions to support them. Several instruments have been developed to measure caregiver burden in these patients. However, the measurement properties of these instruments have not been systematically reviewed.Methods and analysis This systematic review will include a comprehensive search of databases including PubMed, CINAHL, Embase, Cochrane Library, SCOPUS and Web of Science by using keywords and MeSH terms to identify relevant studies starting from each database inception to 1 January 2024 and covering papers in English. The search strategy will combine relevant keywords and database-specific subject headings related to the following concepts: (1) caregivers, (2) burden, stress, distress, (3) chronic kidney disease, end-stage kidney disease, dialysis. Reference lists of eligible articles will also be hand searched. We will include quantitative and qualitative studies evaluating measurement properties of instruments assessing caregiver burden in caregivers of adult patients (aged ≥18 years). Data will be extracted from the selected studies and analysed using the COnsensus-based Standards for the selection of health Measurement INstruments checklist as the study quality assessment tool. Subsequently, the van der Vleuten utility index will be used to critique and categorise the instruments. A narrative that synthesises the utility of all instruments will be presented along with recommendations for the selection of instruments depending on specific clinical contexts. This systematic review will provide an overview of the measurement properties of available instruments, including discussion on reliability, validity and responsiveness. Results from the review may give rise to the subsequent development of most appropriate instrument that could be applied to the assessment of caregiver burden in advanced kidney disease.Ethics and dissemination Ethics approval is not required as this study will merely synthesise data from published studies. The results will be disseminated through peer-reviewed publications as well as conference presentations.PROSPERO registration number CRD42023433906.

Published
2024
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