7,595 results on '"Shen, Ying"'
Search Results
52. Exosomal miR-9-5p derived from iPSC-MSCs ameliorates doxorubicin-induced cardiomyopathy by inhibiting cardiomyocyte senescence
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Zheng, Huifeng, Liang, Xiaoting, Liu, Baojuan, Huang, Xinran, Shen, Ying, Lin, Fang, Chen, Jiaqi, Gao, Xiaoyan, He, Haiwei, Li, Weifeng, Hu, Bei, Li, Xin, and Zhang, Yuelin
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- 2024
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53. Promoting collateral formation in type 2 diabetes mellitus using ultra-small nanodots with autophagy activation and ROS scavenging
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Wang, Yixuan, Li, Feifei, Mao, Linshuang, Liu, Yu, Chen, Shuai, Liu, Jingmeng, Huang, Ke, Chen, Qiujing, Wu, Jianrong, Lu, Lin, Zheng, Yuanyi, Shen, Weifeng, Ying, Tao, Dai, Yang, and Shen, Ying
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- 2024
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54. Circulating secretoneurin level reflects angiographic coronary collateralization in stable angina patients with chronic total occlusion
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Wu, Zhi Ming, Huang, Ke, Dai, Yang, Chen, Shuai, Wang, Xiao Qun, Yang, Chen Die, Li, Le Ying, Liu, Jing Meng, Lu, Lin, Zhang, Rui Yan, Shen, Wei Feng, Shen, Ying, and Ding, Feng Hua
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- 2024
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55. Correction: Rare predicted loss-of-function variants of type I IFN immunity genes are associated with life-threatening COVID-19
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Matuozzo, Daniela, Talouarn, Estelle, Marchal, Astrid, Zhang, Peng, Manry, Jeremy, Seeleuthner, Yoann, Zhang, Yu, Bolze, Alexandre, Chaldebas, Matthieu, Milisavljevic, Baptiste, Gervais, Adrian, Bastard, Paul, Asano, Takaki, Bizien, Lucy, Barzaghi, Federica, Abolhassani, Hassan, Tayoun, Ahmad Abou, Aiuti, Alessandro, Darazam, Ilad Alavi, Allende, Luis M., Alonso-Arias, Rebeca, Arias, Andrés Augusto, Aytekin, Gokhan, Bergman, Peter, Bondesan, Simone, Bryceson, Yenan T., Bustos, Ingrid G., Cabrera-Marante, Oscar, Carcel, Sheila, Carrera, Paola, Casari, Giorgio, Chaïbi, Khalil, Colobran, Roger, Condino-Neto, Antonio, Covill, Laura E., Delmonte, Ottavia M., Zein, Loubna El, Flores, Carlos, Gregersen, Peter K., Gut, Marta, Haerynck, Filomeen, Halwani, Rabih, Hancerli, Selda, Hammarström, Lennart, Hatipoğlu, Nevin, Karbuz, Adem, Keles, Sevgi, Kyheng, Christèle, Leon-Lopez, Rafael, Franco, Jose Luis, Mansouri, Davood, Martinez-Picado, Javier, Akcan, Ozge Metin, Migeotte, Isabelle, Morange, Pierre-Emmanuel, Morelle, Guillaume, Martin-Nalda, Andrea, Novelli, Giuseppe, Novelli, Antonio, Ozcelik, Tayfun, Palabiyik, Figen, Pan-Hammarström, Qiang, de Diego, Rebeca Pérez, Planas-Serra, Laura, Pleguezuelo, Daniel E., Prando, Carolina, Pujol, Aurora, Reyes, Luis Felipe, Rivière, Jacques G., Rodriguez-Gallego, Carlos, Rojas, Julian, Rovere-Querini, Patrizia, Schlüter, Agatha, Shahrooei, Mohammad, Sobh, Ali, Soler-Palacin, Pere, Tandjaoui-Lambiotte, Yacine, Tipu, Imran, Tresoldi, Cristina, Troya, Jesus, van de Beek, Diederik, Zatz, Mayana, Zawadzki, Pawel, Al-Muhsen, Saleh Zaid, Alosaimi, Mohammed Faraj, Alsohime, Fahad M., Baris-Feldman, Hagit, Butte, Manish J., Constantinescu, Stefan N., Cooper, Megan A., Dalgard, Clifton L., Fellay, Jacques, Heath, James R., Lau, Yu-Lung, Lifton, Richard P., Maniatis, Tom, Mogensen, Trine H., von Bernuth, Horst, Lermine, Alban, Vidaud, Michel, Boland, Anne, Deleuze, Jean-François, Nussbaum, Robert, Kahn-Kirby, Amanda, Mentre, France, Tubiana, Sarah, Gorochov, Guy, Tubach, Florence, Hausfater, Pierre, Meyts, Isabelle, Zhang, Shen-Ying, Puel, Anne, Notarangelo, Luigi D., Boisson-Dupuis, Stephanie, Su, Helen C., Boisson, Bertrand, Jouanguy, Emmanuelle, Casanova, Jean-Laurent, Zhang, Qian, Abel, Laurent, and Cobat, Aurélie
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- 2024
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56. Incidence and risk factors of perioperative deep vein thrombosis in patients undergoing primary hip arthroplasty via the direct anterior approach
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Zhuang, Zaikai, Li, Qiangqiang, Yao, Yao, Shen, Ying, Chen, Dongyang, and Jiang, Qing
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- 2024
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57. Circ_0027885 sponges miR-203-3p to regulate RUNX2 expression and alleviates osteoporosis progression
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Fang, Shuhua, Cao, Dingwen, Wu, Zhanpo, Chen, Jie, Huang, Yafei, Shen, Ying, and Gao, Zengxin
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- 2024
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58. Solution Treatment as Pretreatment for Corrosion Resistance and Cytocompatibility of Micro-Arc Oxidation Coating on Biodegradable Mg Alloy
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Shen, Ying, Wang, Guiyang, Tu, Hao, Kolawole, Sharafadeen Kunle, Su, Xuping, and Chen, Junxiu
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- 2024
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59. Association of Magnesium, Iron, Copper, and Zinc Levels with the Prevalence of Behavior Problems in Children and Adolescents
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Shen, Ying, Jin, Huyi, Guo, Fanjia, Zhang, Wanting, Fu, Hao, Jin, Mingjuan, and Chen, Guangdi
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- 2024
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60. Continuous age- and sex-specific reference ranges of liver enzymes in Chinese children and application in pediatric non-alcoholic fatty liver disease
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Wu, Zhao-Yuan, Chi, Si-Wei, Ouyang, Liu-Jian, Xu, Xiao-Qin, Chen, Jing-Nan, Jin, Bing-Han, Ullah, Rahim, Zhou, Xue-Lian, Huang, Ke, Dong, Guan-Ping, Li, Zhe-Ming, Shen, Ying, Shao, Jie, Ni, Yan, Fu, Jun-Fen, Shu, Qiang, and Wu, Wei
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- 2024
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61. Comparative Study of the Effects of Nano ZnO and CuO on the Biodegradation, Biocompatibility, and Antibacterial Properties of Micro-arc Oxidation Coating of Magnesium Alloy
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Shen, Ying, Shan, Xianfeng, Etim, Iniobong P., Siddiqui, Muhammad Ali, Yang, Yang, Shi, Zewen, Su, Xuping, and Chen, Junxiu
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- 2024
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62. Aerobic Glycolysis Induced by mTOR/HIF-1α Promotes Early Brain Injury After Subarachnoid Hemorrhage via Activating M1 Microglia
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Sun, Xin-Gang, Chu, Xue-Hong, Godje Godje, Ivan Steve, Liu, Shao-Yu, Hu, Hui-Yu, Zhang, Yi-Bo, Zhu, Li-Juan, Wang, Hai, Sui, Chen, Huang, Juan, and Shen, Ying-Jie
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- 2024
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63. Learning by Asking for Embodied Visual Navigation and Task Completion
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Shen, Ying and Lourentzou, Ismini
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Artificial Intelligence ,Computer Science - Computation and Language ,Computer Science - Machine Learning - Abstract
The research community has shown increasing interest in designing intelligent embodied agents that can assist humans in accomplishing tasks. Despite recent progress on related vision-language benchmarks, most prior work has focused on building agents that follow instructions rather than endowing agents the ability to ask questions to actively resolve ambiguities arising naturally in embodied environments. To empower embodied agents with the ability to interact with humans, in this work, we propose an Embodied Learning-By-Asking (ELBA) model that learns when and what questions to ask to dynamically acquire additional information for completing the task. We evaluate our model on the TEACH vision-dialog navigation and task completion dataset. Experimental results show that ELBA achieves improved task performance compared to baseline models without question-answering capabilities.
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- 2023
64. Visual effects of a forward-curled 3D map of the Forbidden City with eye-tracking
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Shen Ying, Junru Su, Yuan Zhuang, and Lina Huang
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Deformation visualization ,forward-curled 3D map ,eye tracking ,wayfinding ,the Forbidden City ,Mathematical geography. Cartography ,GA1-1776 ,Geodesy ,QB275-343 - Abstract
ABSTRACTIn urban environment visualization, including both traditional two-dimensional (2D) and three-dimensional (3D) visualization, the height of ground objects results in visual occlusions in ordinary 3D maps, which leads to challenges in displaying spatial relationships. We empirically studied the visual effects of a curled deformation method and assessed whether curled deformation visualization could help participants complete wayfinding tasks. The results revealed that a forward-curled map can include both ego-view and bird-view perspectives, ensure continuity from ego-view to bird-view perspectives, and address foreshortening effects. The remote, distant areas are pulled closer, thereby enhancing the sense of space and allowing participants to better understand the overall situation. A forward-curled map has a wider coverage range of fixation points and a wider scope of visual search and can improve a participant’s task completion efficiency. Moreover, the cognitive burden is not increased with this approach.
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- 2024
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65. The Role of a Ladderlike Communication Skill Course on Fostering Doctor-Patient Communication Competence of Students in Rural-oriented Free Tuition Medical Education Program
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CHEN Enran, SHEN Ying, WEI Yuning, WEI Siyu
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education, medical, undergraduate ,general practice ,rural-oriented free tuition medical education program students ,doctor-patient communication ,communication skill ,ladderlike course ,Medicine - Abstract
Background The phase of undergraduate medical education is the starting point for fostering communication competence of students in Rural-oriented Free Tuition Medical Education Program (RTME), which lays the foundation both for communication competence training in the postgraduate education phase and performing effective communications with patients and their relatives, colleagues, and other health personnel in the career life of general practitioners (GPs). It is of great practical significance to explore how to improve quality of doctor-patient communication education in the stage of undergraduate medical education and develop doctor-patient communication competence of the RTME students. Objective To explore the role of the ladderlike communication skill course on fostering doctor-patient communication competence of students in rural-oriented free tuition medical education program. Methods A total of 259 RTME students of Grade 2019 were selected from Guangxi Medical University in September 2019 to establish Cohort 1, and 262 undergraduate medical students of Grade 2019 were selected to establish Cohort 2. From September 2019 to January 2022, the students in Cohort 1 were trained in a ladderlike communication skill course lasting for five consecutive semesters; from September 2021 to January 2022, the students in both cohorts were trained in a doctor-patient communication course. The final exam scores and process assessment scores of the two cohorts on the doctor-patient communication course were compared and the evaluation of teaching effectiveness and satisfaction of ladderlike communication skill course were investigated in the students in Cohort 1. Results The RTME students achieved significantly greater total scores for the final exam of the doctor-patient communication course, in which the RTME students performed better on the sections of case analysis and small essay, but worse on the single-choice question section compared to the undergraduate medical students (P0.05). Over 80% of RTME students felt satisfied or absolutely satisfied with the content, pedagogical measures, faculty, schedule and effects of the ladderlike communication skill course, and more than 60% believed it helped or absolutely helped promote learning interest, increase confidence to encounter difficult patients, and raise multiple competence, including empathy, doctor-patient communication, language expression, problem resolution, and team work. Conclusion The ladderlike communication skill course significantly elevates the effects of doctor-patient communication education in the phase of undergraduate medical education for the RTME students, facilitates the development of doctor-patient communication competence and other comprehensive competence. The ladderlike course mode is an effective measure fostering doctor-patient communication competence of medical students in medical education, and makes a useful reference for communication competence training for postgraduate education and continuing education of general practice.
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- 2024
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66. KIF22 promotes multiple myeloma progression by regulating the CDC25C/CDK1/cyclinB1 pathway
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Zhai, Meng, Miao, Jiyu, Zhang, Ru, Liu, Rui, Li, Fangmei, Shen, Ying, Wang, Ting, Xu, Xuezhu, Gao, Gongzhizi, Hu, Jinsong, He, Aili, and Bai, Ju
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- 2024
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67. Toll-Like Receptor 3 Mediates Aortic Stenosis Through a Conserved Mechanism of Calcification.
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Gollmann-Tepeköylü, Can, Graber, Michael, Hirsch, Jakob, Mair, Sophia, Naschberger, Andreas, Pölzl, Leo, Nägele, Felix, Kirchmair, Elke, Degenhart, Gerald, Demetz, Egon, Hilbe, Richard, Chen, Hao-Yu, Engert, James, Böhm, Anna, Franz, Nadja, Lobenwein, Daniela, Lener, Daniela, Fuchs, Christiane, Weihs, Anna, Töchterle, Sonja, Vogel, Georg, Schweiger, Victor, Eder, Jonas, Pietschmann, Peter, Seifert, Markus, Kronenberg, Florian, Coassin, Stefan, Blumer, Michael, Hackl, Hubert, Meyer, Dirk, Feuchtner, Gudrun, Kirchmair, Rudolf, Troppmair, Jakob, Krane, Markus, Weiss, Günther, Thanassoulis, George, Grimm, Michael, Rupp, Bernhard, Huber, Lukas, Zhang, Shen-Ying, Casanova, Jean-Laurent, Tancevski, Ivan, Holfeld, Johannes, and Tsimikas, Sotirios
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Toll-like receptor 3 ,aortic valve disease ,biglycan ,extracellular matrix ,osteogenesis ,proteins ,Adult ,Animals ,Humans ,Mice ,Aortic Valve ,Aortic Valve Stenosis ,Biglycan ,Calcinosis ,Cells ,Cultured ,Toll-Like Receptor 3 ,Zebrafish - Abstract
BACKGROUND: Calcific aortic valve disease (CAVD) is characterized by a phenotypic switch of valvular interstitial cells to bone-forming cells. Toll-like receptors (TLRs) are evolutionarily conserved pattern recognition receptors at the interface between innate immunity and tissue repair. Type I interferons (IFNs) are not only crucial for an adequate antiviral response but also implicated in bone formation. We hypothesized that the accumulation of endogenous TLR3 ligands in the valvular leaflets may promote the generation of osteoblast-like cells through enhanced type I IFN signaling. METHODS: Human valvular interstitial cells isolated from aortic valves were challenged with mechanical strain or synthetic TLR3 agonists and analyzed for bone formation, gene expression profiles, and IFN signaling pathways. Different inhibitors were used to delineate the engaged signaling pathways. Moreover, we screened a variety of potential lipids and proteoglycans known to accumulate in CAVD lesions as potential TLR3 ligands. Ligand-receptor interactions were characterized by in silico modeling and verified through immunoprecipitation experiments. Biglycan (Bgn), Tlr3, and IFN-α/β receptor alpha chain (Ifnar1)-deficient mice and a specific zebrafish model were used to study the implication of the biglycan (BGN)-TLR3-IFN axis in both CAVD and bone formation in vivo. Two large-scale cohorts (GERA [Genetic Epidemiology Research on Adult Health and Aging], n=55 192 with 3469 aortic stenosis cases; UK Biobank, n=257 231 with 2213 aortic stenosis cases) were examined for genetic variation at genes implicated in BGN-TLR3-IFN signaling associating with CAVD in humans. RESULTS: Here, we identify TLR3 as a central molecular regulator of calcification in valvular interstitial cells and unravel BGN as a new endogenous agonist of TLR3. Posttranslational BGN maturation by xylosyltransferase 1 (XYLT1) is required for TLR3 activation. Moreover, BGN induces the transdifferentiation of valvular interstitial cells into bone-forming osteoblasts through the TLR3-dependent induction of type I IFNs. It is intriguing that Bgn-/-, Tlr3-/-, and Ifnar1-/- mice are protected against CAVD and display impaired bone formation. Meta-analysis of 2 large-scale cohorts with >300 000 individuals reveals that genetic variation at loci relevant to the XYLT1-BGN-TLR3-interferon-α/β receptor alpha chain (IFNAR) 1 pathway is associated with CAVD in humans. CONCLUSIONS: This study identifies the BGN-TLR3-IFNAR1 axis as an evolutionarily conserved pathway governing calcification of the aortic valve and reveals a potential therapeutic target to prevent CAVD.
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- 2023
68. Monogenic Susceptibility to Infections With Viruses, Mycobacteria, Bacteria and Candida
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Zhang, Shen-Ying, primary, Rosain, Jérémie, additional, Picard, Capucine, additional, and Bustamante, Jacinta, additional
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- 2024
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69. MultiInstruct: Improving Multi-Modal Zero-Shot Learning via Instruction Tuning
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Xu, Zhiyang, Shen, Ying, and Huang, Lifu
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Computer Science - Computation and Language - Abstract
Instruction tuning, a new learning paradigm that fine-tunes pre-trained language models on tasks specified through instructions, has shown promising zero-shot performance on various natural language processing tasks. However, it has yet to be explored for vision and multimodal tasks. In this work, we introduce MUL-TIINSTRUCT, the first multimodal instruction tuning benchmark dataset that consists of 62 diverse multimodal tasks in a unified seq-to-seq format covering 10 broad categories. The tasks are derived from 21 existing open-source datasets and each task is equipped with 5 expert-written instructions. We take OFA as the base pre-trained model for multimodal instruction tuning, and to further improve its zero-shot performance, we explore multiple transfer learning strategies to leverage the large-scale NATURAL INSTRUCTIONS dataset. Experimental results demonstrate strong zero-shot performance on various unseen multimodal tasks and the benefit of transfer learning from a text-only instruction dataset. We also design a new evaluation metric - Sensitivity, to evaluate how sensitive the model is to the variety of instructions. Our results indicate that fine-tuning the model on a diverse set of tasks and instructions leads to a reduced sensitivity to variations in instructions for each task., Comment: ACL 2023, dataset url: https://github.com/VT-NLP/MultiInstruct
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- 2022
70. Collaborating Heterogeneous Natural Language Processing Tasks via Federated Learning
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Dong, Chenhe, Xie, Yuexiang, Ding, Bolin, Shen, Ying, and Li, Yaliang
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Computer Science - Computation and Language - Abstract
The increasing privacy concerns on personal private text data promote the development of federated learning (FL) in recent years. However, the existing studies on applying FL in NLP are not suitable to coordinate participants with heterogeneous or private learning objectives. In this study, we further broaden the application scope of FL in NLP by proposing an Assign-Then-Contrast (denoted as ATC) framework, which enables clients with heterogeneous NLP tasks to construct an FL course and learn useful knowledge from each other. Specifically, the clients are suggested to first perform local training with the unified tasks assigned by the server rather than using their own learning objectives, which is called the Assign training stage. After that, in the Contrast training stage, clients train with different local learning objectives and exchange knowledge with other clients who contribute consistent and useful model updates. We conduct extensive experiments on six widely-used datasets covering both Natural Language Understanding (NLU) and Natural Language Generation (NLG) tasks, and the proposed ATC framework achieves significant improvements compared with various baseline methods. The source code is available at \url{https://github.com/alibaba/FederatedScope/tree/master/federatedscope/nlp/hetero_tasks}.
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- 2022
71. Active Relation Discovery: Towards General and Label-aware Open Relation Extraction
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Li, Yangning, Li, Yinghui, Chen, Xi, Zheng, Hai-Tao, Shen, Ying, and Kim, Hong-Gee
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Computer Science - Computation and Language ,Computer Science - Artificial Intelligence - Abstract
Open Relation Extraction (OpenRE) aims to discover novel relations from open domains. Previous OpenRE methods mainly suffer from two problems: (1) Insufficient capacity to discriminate between known and novel relations. When extending conventional test settings to a more general setting where test data might also come from seen classes, existing approaches have a significant performance decline. (2) Secondary labeling must be performed before practical application. Existing methods cannot label human-readable and meaningful types for novel relations, which is urgently required by the downstream tasks. To address these issues, we propose the Active Relation Discovery (ARD) framework, which utilizes relational outlier detection for discriminating known and novel relations and involves active learning for labeling novel relations. Extensive experiments on three real-world datasets show that ARD significantly outperforms previous state-of-the-art methods on both conventional and our proposed general OpenRE settings. The source code and datasets will be available for reproducibility.
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- 2022
72. Towards Attribute-Entangled Controllable Text Generation: A Pilot Study of Blessing Generation
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Huang, Shulin, Ma, Shirong, Li, Yinghui, Li, Yangning, Lin, Shiyang, Zheng, Hai-Tao, and Shen, Ying
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Computer Science - Computation and Language - Abstract
Controllable Text Generation (CTG) has obtained great success due to its fine-grained generation ability obtained by focusing on multiple attributes. However, most existing CTG researches overlook how to utilize the attribute entanglement to enhance the diversity of the controlled generated texts. Facing this dilemma, we focus on a novel CTG scenario, i.e., blessing generation which is challenging because high-quality blessing texts require CTG models to comprehensively consider the entanglement between multiple attributes (e.g., objects and occasions). To promote the research on blessing generation, we present EBleT, a large-scale Entangled Blessing Text dataset containing 293K English sentences annotated with multiple attributes. Furthermore, we propose novel evaluation metrics to measure the quality of the blessing texts generated by the baseline models we designed. Our study opens a new research direction for controllable text generation and enables the development of attribute-entangled CTG models. Our dataset and source codes are available at \url{https://github.com/huangshulin123/Blessing-Generation}., Comment: Accepted to EMNLP 2022 GEM Workshop
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- 2022
73. Linguistic Rules-Based Corpus Generation for Native Chinese Grammatical Error Correction
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Ma, Shirong, Li, Yinghui, Sun, Rongyi, Zhou, Qingyu, Huang, Shulin, Zhang, Ding, Yangning, Li, Liu, Ruiyang, Li, Zhongli, Cao, Yunbo, Zheng, Haitao, and Shen, Ying
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Computer Science - Computation and Language - Abstract
Chinese Grammatical Error Correction (CGEC) is both a challenging NLP task and a common application in human daily life. Recently, many data-driven approaches are proposed for the development of CGEC research. However, there are two major limitations in the CGEC field: First, the lack of high-quality annotated training corpora prevents the performance of existing CGEC models from being significantly improved. Second, the grammatical errors in widely used test sets are not made by native Chinese speakers, resulting in a significant gap between the CGEC models and the real application. In this paper, we propose a linguistic rules-based approach to construct large-scale CGEC training corpora with automatically generated grammatical errors. Additionally, we present a challenging CGEC benchmark derived entirely from errors made by native Chinese speakers in real-world scenarios. Extensive experiments and detailed analyses not only demonstrate that the training data constructed by our method effectively improves the performance of CGEC models, but also reflect that our benchmark is an excellent resource for further development of the CGEC field., Comment: Long paper, accepted at the Findings of EMNLP 2022
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- 2022
74. Efficiently Extracting Multi-Point Correlations of a Floquet Thermalized System
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Zheng, Yong-Guang, Zhang, Wei-Yong, Shen, Ying-Chao, Luo, An, Liu, Ying, He, Ming-Gen, Zhang, Hao-Ran, Lin, Wan, Wang, Han-Yi, Zhu, Zi-Hang, Chen, Ming-Cheng, Lu, Chao-Yang, Thanasilp, Supanut, Angelakis, Dimitris G., Yuan, Zhen-Sheng, and Pan, Jian-Wei
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Condensed Matter - Quantum Gases ,Quantum Physics - Abstract
Nonequilibrium dynamics of many-body systems is challenging for classical computing, providing opportunities for demonstrating practical quantum computational advantage with analogue quantum simulators. It is proposed to be classically intractable to sample driven thermalized many-body states of Bose-Hubbard systems, and further extract multi-point correlations for characterizing quantum phases. Here, leveraging dedicated precise manipulations and number-resolved detection through a quantum gas microscope, we implement and sample a 32-site driven Hubbard chain in the thermalized phase. Multi-point correlations of up to 14th-order extracted from experimental samples offer clear distinctions between the thermalized and many-body-localized phases. In terms of estimated computational powers, the quantum simulator is comparable to the fastest supercomputer with currently known best algorithms. Our work paves the way towards practical quantum advantage in simulating Floquet dynamics of many-body systems., Comment: 18 pages, 14 figures
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- 2022
75. Functional building blocks for scalable multipartite entanglement in optical lattices
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Zhang, Wei-Yong, He, Ming-Gen, Sun, Hui, Zheng, Yong-Guang, Liu, Ying, Luo, An, Wang, Han-Yi, Zhu, Zi-Hang, Qiu, Pei-Yue, Shen, Ying-Chao, Wang, Xuan-Kai, Lin, Wan, Yu, Song-Tao, Li, Bin-Chen, Xiao, Bo, Li, Meng-Da, Yang, Yu-Meng, Jiang, Xiao, Dai, Han-Ning, Zhou, You, Ma, Xiongfeng, Yuan, Zhen-Sheng, and Pan, Jian-Wei
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Condensed Matter - Quantum Gases ,Quantum Physics - Abstract
Featuring excellent coherence and operated parallelly, ultracold atoms in optical lattices form a competitive candidate for quantum computation. For this, a massive number of parallel entangled atom pairs have been realized in superlattices. However, the more formidable challenge is to scale-up and detect multipartite entanglement due to the lack of manipulations over local atomic spins in retro-reflected bichromatic superlattices. Here we developed a new architecture based on a cross-angle spin-dependent superlattice for implementing layers of quantum gates over moderately-separated atoms incorporated with a quantum gas microscope for single-atom manipulation. We created and verified functional building blocks for scalable multipartite entanglement by connecting Bell pairs to one-dimensional 10-atom chains and two-dimensional plaquettes of $2\times4$ atoms. This offers a new platform towards scalable quantum computation and simulation.
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- 2022
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76. Lack of association between classical HLA genes and asymptomatic SARS-CoV-2 infection
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Astrid Marchal, Elizabeth T. Cirulli, Iva Neveux, Evangelos Bellos, Ryan S. Thwaites, Kelly M. Schiabor Barrett, Yu Zhang, Ivana Nemes-Bokun, Mariya Kalinova, Andrew Catchpole, Stuart G. Tangye, András N. Spaan, Justin B. Lack, Jade Ghosn, Charles Burdet, Guy Gorochov, Florence Tubach, Pierre Hausfater, Clifton L. Dalgard, Shen-Ying Zhang, Qian Zhang, Christopher Chiu, Jacques Fellay, Joseph J. Grzymski, Vanessa Sancho-Shimizu, Laurent Abel, Jean-Laurent Casanova, Aurélie Cobat, Alexandre Bolze, Alessandro Aiuti, Saleh Al-Muhsen, Fahd Al-Mulla, Ali Amara, Mark S. Anderson, Evangelos Andreakos, Andrés A. Arias, Lisa M. Arkin, Hagit Baris Feldman, Paul Bastard, Alexandre Belot, Catherine M. Biggs, Dusan Bogunovic, Anastasiia Bondarenko, Alessandro Borghesi, Ahmed A. Bousfiha, Petter Brodin, Yenan Bryceson, Manish J. Butte, Giorgio Casari, John Christodoulou, Roger Colobran, Antonio Condino-Neto, Stefan N. Constantinescu, Megan A. Cooper, Murkesh Desai, Beth A. Drolet, Xavier Duval, Jamila El Baghdadi, Philippine Eloy, Sara Espinosa-Padilla, Carlos Flores, José Luis Franco, Antoine Froidure, Peter K. Gregersen, Bodo Grimbacher, Filomeen Haerynck, David Hagin, Rabih Halwani, Lennart Hammarström, James R. Heath, Elena W.Y. Hsieh, Eystein Husebye, Kohsuke Imai, Yuval Itan, Emmanuelle Jouanguy, Elżbieta Kaja, Timokratis Karamitros, Kai Kisand, Cheng-Lung Ku, Yu-Lung Lau, Yun Ling, Carrie L. Lucas, Tom Maniatis, Davood Mansouri, László Maródi, France Mentré, Isabelle Meyts, Joshua D. Milner, Kristina Mironska, Trine H. Mogensen, Tomohiro Morio, Lisa F.P. Ng, Luigi D. Notarangelo, Antonio Novelli, Giuseppe Novelli, Cliona O'Farrelly, Satoshi Okada, Keisuke Okamoto, Tayfun Ozcelik, Qiang Pan-Hammarström, Jean W. Pape, Rebeca Perez de Diego, Jordi Perez-Tur, David S. Perlin, Graziano Pesole, Anna M. Planas, Carolina Prando, Aurora Pujol, Anne Puel, Lluis Quintana-Murci, Sathishkumar Ramaswamy, Laurent Renia, Igor Resnick, Carlos Rodríguez-Gallego, Anna Sediva, Mikko R.J. Seppänen, Mohammad Shahrooei, Anna Shcherbina, Ondrej Slaby, Andrew L. Snow, Pere Soler-Palacín, Vassili Soumelis, Ivan Tancevski, Ahmad Abou Tayoun, Şehime Gülsün Temel, Christian Thorball, Pierre Tiberghien, Sophie Trouillet-Assant, Stuart E. Turvey, K. M. Furkan Uddin, Mohammed J. Uddin, Diederik van de Beek, Donald C. Vinh, Horst von Bernuth, Joost Wauters, Mayana Zatz, Pawel Zawadzki, Serge Bureau, Yannick Vacher, Anne Gysembergh-Houal, Lauren Demerville, Abla Benleulmi-Chaachoua, Sebastien Abad, Radhiya Abassi, Abdelrafie Abdellaoui, Abdelkrim Abdelmalek, Hendy Abdoul, Helene Abergel, Fariza Abeud, Sophie Abgrall, Noemie Abisror, Marylise Adechian, Nordine Aderdour, Hakeem Farid Admane, Frederic Adnet, Sara Afritt, Helene Agostini, Claire Aguilar, Sophie Agut, Tommaso Francesco Aiello, Marc Ait Kaci, Hafid Ait Oufella, Gokula Ajeenthiravasan, Virginie Alauzy, Fanny Alby-Laurent, Lucie Allard, Marie-Alexandra Alyanakian, Blanca Amador Borrero, Sabrina Amam, Lucile Amrouche, Marc Andronikof, Dany Anglicheau, Nadia Anguel, Djillali Annane, Mohammed Aounzou, Caroline Aparicio, Gladys Aratus, Jean-Benoit Arlet, Jeremy Arzoine, Elisabeth Aslangul, Mona Assefi, Adeline Aubry, Laetitia Audiffred, Etienne Audureau, Christelle Nathalie Auger, Jean-Charles Auregan, Celine Awotar, Sonia Ayllon Milla, Delphine Azan, Laurene Azemar, Billal Azzouguen, Marwa Bachir Elrufaai, Aïda Badsi, Prissile Bakouboula, Coline Balcerowiak, Fanta Balde, Elodie Baldivia, Eliane-Flore Bangamingo, Amandine Baptiste, Fanny Baran-Marszak, Caroline Barau, Nathalie Barget, Flore Baronnet, Romain Barthelemy, Jean-Luc Baudel, Camille Baudry, Elodie Baudry, Laurent Beaugerie, Adel Belamri, Nicolas Belaube, Rhida Belilita, Pierre Bellassen, Rawan Belmokhtar, Isabel Beltran, Ruben Benainous, Mourad Benallaoua, Robert Benamouzig, Amélie Benbara, Jaouad Benhida, Anis Benkhelouf, Jihene Benlagha, Chahinez Benmostafa, Skander Benothmane, Miassa Bentifraouine, Laurence Berard, Quentin Bernier, Enora Berti, Astrid Bertier, Laure Berton, Simon Bessis, Alexandra Beurton, Celine Bianco, Clara Bianquis, Frank Bidar, Philippe Blanche, Clarisse Blayau, Alexandre Bleibtreu, Emmanuelle Blin, Coralie Bloch-Queyrat, Marie-Christophe Boissier, Diane Bollens, Marion Bolzoni, Rudy pierre Bompard, Nicolas Bonnet, Justine Bonnouvrier, Shirmonecrystal Botha, Wissam Boucenna, Fatiha Bouchama, Olivier Bouchaud, Hanane Bouchghoul, Taoueslylia Boudjebla, Noel Boudjema, Catherine Bouffard, Adrien Bougle, Meriem Bouguerra, Leila Bouras, Agnes Bourcier, Anne Bourgarit Durand, Anne Bourrier, Fabrice Bouscarat, Diane Bouvry, Nesrine Bouziri, Ons Bouzrara, Sarah Bribier, Delphine Brugier, Melanie Brunel, Eida Bui, Anne Buisson, Iryna Bukreyeva, Côme Bureau, Jacques Cadranel, Johann Cailhol, Ruxandra Calin, Clara Campos Vega, Pauline Canavaggio, Marta Cancella, Delphine Cantin, Albert Cao, Lionel Carbillon, Nicolas Carlier, Clementine Cassard, Guylaine Castor, Marion Cauchy, Olivier Cha, Benjamin Chaigne, Salima Challal, Karine Champion, Patrick Chariot, Julie Chas, Simon Chauveau, Anthony Chauvin, Clement Chauvin, Nathalie Chavarot, Kamélia Chebbout, Mustapha Cherai, Ilaria Cherubini, Amelie Chevalier, Thibault Chiarabini, Thierry Chinet, Richard Chocron, Pascaline Choinier, Juliette Chommeloux, Christophe Choquet, Laure 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Rodero, Carlos Rodrigo, Luis Antonio Rodriguez, Carlos Rodriguez-Gallego, Agustí Rodriguez-Palmero, Carolina Soledad Romero, Anya Rothenbuhler, Damien Roux, Nikoletta Rovina, Flore Rozenberg, Yvon Ruch, Montse Ruiz, Maria Yolanda Ruiz del Prado, Juan Carlos Ruiz-Rodriguez, Joan Sabater-Riera, Kai Saks, Maria Salagianni, Oliver Sanchez, Adrián Sánchez-Montalvá, Silvia Sánchez-Ramón, Laire Schidlowski, Agatha Schluter, Julien Schmidt, Matthieu Schmidt, Catharina Schuetz, Cyril E. Schweitzer, Francesco Scolari, Luis Seijo, Analia Gisela Seminario, Piseth Seng, Sevtap Senoglu, Mikko Seppänen, Alex Serra Llovich, Virginie Siguret, Eleni Siouti, David M. Smadja, Nikaia Smith, Ali Sobh, Xavier Solanich, Jordi Solé-Violán, Catherine Soler, Betül Sözeri, Giulia Maria Stella, Yuriy Stepanovskiy, Annabelle Stoclin, Fabio Taccone, Jean-Luc Taupin, Simon J. Tavernier, Loreto Vidaur Tello, Benjamin Terrier, Guillaume Thiery, Karolina Thorn, Caroline Thumerelle, Imran Tipu, Martin Tolstrup, Gabriele Tomasoni, Julie Toubiana, Josep Trenado Alvarez, Vasiliki Triantafyllia, Jesús Troya, Owen T.Y. Tsang, Liina Tserel, Eugene Y.K. Tso, Alessandra Tucci, Şadiye Kübra Tüter Öz, Matilde Valeria Ursini, Takanori Utsumi, Pierre Vabres, Juan Valencia-Ramos, Ana Maria Van Den Rym, Isabelle Vandernoot, Valentina Velez-Santamaria, Silvia Patricia Zuniga Veliz, Mateus C. Vidigal, Sébastien Viel, Cédric Villain, Marie E. Vilaire-Meunier, Judit Villar-García, Audrey Vincent, Dimitri Van der Linden, Alla Volokha, Fanny Vuotto, Els Wauters, Alan K.L. Wu, Tak-Chiu Wu, Aysun Yahşi, Osman Yesilbas, Mehmet Yildiz, Barnaby E. Young, Ufuk Yükselmiş, Marco Zecca, Valentina Zuccaro, Jens Van Praet, Bart N. Lambrecht, Eva Van Braeckel, Cédric Bosteels, Levi Hoste, Eric Hoste, Fré Bauters, Jozefien De Clercq, Catherine Heijmans, Hans Slabbynck, Leslie Naesens, Benoit Florkin, Mary-Anne Young, Amanda Willis, Paloma Lapuente-Suanzes, Ana de Andrés-Martín, Matilda Berkell, Valerio Carelli, Alessia Fiorentino, Surbhi Malhotra, Alessandro Mattiaccio, Tommaso Pippucci, Marco Seri, Evelina Tacconelli, Michiel van Agtmael, Anne Geke Algera, Brent Appelman, Frank van Baarle, Diane Bax, Martijn Beudel, Harm Jan Bogaard, Marije Bomers, Peter Bonta, Lieuwe Bos, Michela Botta, Justin de Brabander, Godelieve de Bree, Sanne de Bruin, David T.P. Buis, Marianna Bugiani, Esther Bulle, Osoul Chouchane, Alex Cloherty, Mirjam Dijkstra, Dave A. Dongelmans, Romein W.G. Dujardin, Paul Elbers, Lucas Fleuren, Suzanne Geerlings, Theo Geijtenbeek, Armand Girbes, Bram Goorhuis, Martin P. Grobusch, Florianne Hafkamp, Laura Hagens, Jorg Hamann, Vanessa Harris, Robert Hemke, Sabine M. Hermans, Leo Heunks, Markus Hollmann, Janneke Horn, Joppe W. Hovius, Menno D. de Jong, Rutger Koning, Endry H.T. Lim, Niels van Mourik, Jeaninne Nellen, Esther J. Nossent, Frederique Paulus, Edgar Peters, Dan A.I. Pina-Fuentes, Tom van der Poll, Bennedikt Preckel, Jan M. Prins, Jorinde Raasveld, Tom Reijnders, Maurits C.F. J. de Rotte, Michiel Schinkel, Marcus J. Schultz, Femke A.P. Schrauwen, Alex Schuurmans, Jaap Schuurmans, Kim Sigaloff, Marleen A. Slim, Patrick Smeele, Marry Smit, Cornelis S. Stijnis, Willemke Stilma, Charlotte Teunissen, Patrick Thoral, Anissa M. Tsonas, Pieter R. Tuinman, Marc van der Valk, Denise P. Veelo, Carolien Volleman, Heder de Vries, Lonneke A. Vught, Michèle van Vugt, Dorien Wouters, A.H. Zwinderman, Matthijs C. Brouwer, W. Joost Wiersinga, Alexander P.J. Vlaar, Miranda F. Tompkins, Camille Alba, Daniel N. Hupalo, John Rosenberger, Gauthaman Sukumar, Matthew D. Wilkerson, Xijun Zhang, Justin Lack, Andrew J. Oler, Kerry Dobbs, Ottavia M. Delmonte, Jeffrey J. Danielson, Andrea Biondi, Laura Rachele Bettini, Mariella D’Angiò, Ilaria Beretta, Luisa Imberti, Alessandra Sottini, Virginia Quaresima, Eugenia Quiros-Roldan, Camillo Rossi, Riccardo Castagnoli, Daniela Montagna, Amelia Licari, and Gian Luigi Marseglia
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HLA ,association ,asymptomatic infection ,COVID-19 ,population stratification ,Genetics ,QH426-470 - Abstract
Summary: Human genetic studies of critical COVID-19 pneumonia have revealed the essential role of type I interferon-dependent innate immunity to SARS-CoV-2 infection. Conversely, an association between the HLA-B∗15:01 allele and asymptomatic SARS-CoV-2 infection in unvaccinated individuals was recently reported, suggesting a contribution of pre-existing T cell-dependent adaptive immunity. We report a lack of association of classical HLA alleles, including HLA-B∗15:01, with pre-omicron asymptomatic SARS-CoV-2 infection in unvaccinated participants in a prospective population-based study in the United States (191 asymptomatic vs. 945 symptomatic COVID-19 cases). Moreover, we found no such association in the international COVID Human Genetic Effort cohort (206 asymptomatic vs. 574 mild or moderate COVID-19 cases and 1,625 severe or critical COVID-19 cases). Finally, in the Human Challenge Characterisation study, the three HLA-B∗15:01 individuals infected with SARS-CoV-2 developed symptoms. As with other acute primary infections studied, no classical HLA alleles favoring an asymptomatic course of SARS-CoV-2 infection were identified.
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- 2024
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77. Vision-HD: road change detection and registration using images and high-definition maps.
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Nian Hui, Zijie Jiang, Zhongliang Cai, and Shen Ying
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- 2024
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78. Automatic Context Pattern Generation for Entity Set Expansion
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Li, Yinghui, Huang, Shulin, Zhang, Xinwei, Zhou, Qingyu, Li, Yangning, Liu, Ruiyang, Cao, Yunbo, Zheng, Hai-Tao, and Shen, Ying
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Computer Science - Computation and Language ,Computer Science - Information Retrieval - Abstract
Entity Set Expansion (ESE) is a valuable task that aims to find entities of the target semantic class described by given seed entities. Various Natural Language Processing (NLP) and Information Retrieval (IR) downstream applications have benefited from ESE due to its ability to discover knowledge. Although existing corpus-based ESE methods have achieved great progress, they still rely on corpora with high-quality entity information annotated, because most of them need to obtain the context patterns through the position of the entity in a sentence. Therefore, the quality of the given corpora and their entity annotation has become the bottleneck that limits the performance of such methods. To overcome this dilemma and make the ESE models free from the dependence on entity annotation, our work aims to explore a new ESE paradigm, namely corpus-independent ESE. Specifically, we devise a context pattern generation module that utilizes autoregressive language models (e.g., GPT-2) to automatically generate high-quality context patterns for entities. In addition, we propose the GAPA, a novel ESE framework that leverages the aforementioned GenerAted PAtterns to expand target entities. Extensive experiments and detailed analyses on three widely used datasets demonstrate the effectiveness of our method. All the codes of our experiments are available at https://github.com/geekjuruo/GAPA., Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible
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- 2022
79. Both real-valued and binary multi-feature fusion histograms for 3D local shape representation
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Hao, Linbo, Wang, Xincheng, Shen, Ying, Xu, Ke, and Wang, Huaming
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- 2023
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80. Alteration of serum bile acids in non-small cell lung cancer identified by a validated LC–MS/MS method
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Yin, Tongxin, Liu, Ke, Shen, Ying, Wang, Yi, Wang, Qiankun, Long, Tingting, Li, Jiaoyuan, and Cheng, Liming
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- 2023
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81. Validity and Reliability of an Evaluation Index System for Consultation Competency of General Practitioners Practicing in Primary Care Settings
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GU Jingmei, JI Shuyu, XI Qian, PENG Houxuan, QIN Li, ZHAO Can, CHEN Peimeng, HUANG Xiaocui, LIANG Ruiying, SHEN Ying
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general practitioners ,consultation competency ,reliability and validity ,confirmatory factor analysis ,second-order model ,Medicine - Abstract
Background Currently, there is a lack of clinical competence evaluation tools applicable of general practitioners (GPs) practicing in rural settings in China, resulting in the lack of researches on the clinical competence evaluation of GPs in rural. Objective To explore reliability and validity of an evaluation index system for consultation competency of rural GPs developed previously, and provide an evaluation tool with high reliability and validity for scientific and objective assessment of consultation competence of GPs in rural settings. Methods Based on the evaluation system for consultation competency of rural GPs, a corresponding questionnaire was designed, and points were assigned to each option on a 5-point Likert scale. From September to December 2022, GPs or assistant general practitioners (AGPs) who were working in rural township health centers in Guangxi Province were recruited as the research subjects by using the purposive sampling and stratified sampling methods, the questionnaire was distributed through a national web-based survey platform-"WJX" to them. Cronbach's α coefficient, split-half coefficient, critical ratio (CR) and correlation coefficients were calculated based on questionnaire data. Confirmative factor analysis was employed to fit questionnaire data and assumed model, and calculate three categories of indicators, including preliminary fit criteria (PFC), overall model fit (OMF), and fit of internal structural model (FISM), to verify the degree of fit and structural validity of the measured data. Results A total of 600 questionnaires were distributed and 366 were validly collected, with an effective recovery rate of 61.0%, 86.1% were registered as GPs and 13.9% as AGPs, who came from five cities, including Nanning, Guilin, Wuzhou, Baise, and Guigang, and 204 township health centers in Guangxi Province. Cronbach'α coefficient for the whole questionnaire or for every section was higher than 0.700, and Guttman Split-Half coefficient was 0.931. The initial first-order model met the PFC well; except for goodness of fit index (GFI), adjusted goodness of fit index (AGFI), and normed fit index (NFI), other indicators related to the OMF reached for the best levels in the modified first-order model. Apart from R2 for 9 observable variables less than 0.5, the FISM for the modified first-order model showed good effects. The initial second-order model indicated as similar effects on the PFC as the initial first-order model; the modified second-order model shared similar OMF with the modified first-order model; the modified second-order model was inferior to the modified first-order model in terms of the FISM. Eventually, questionnaire data fitted the modified first-order model better. Conclusion The evaluation index system for consultation competency of rural GPs shows high reliability and validity, which can be used for research and practical work on the evaluation of consultation competence evaluation of GPs in rural settings.
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- 2024
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82. Construction of an Evaluation Index System for Consultation Competency of General Practitioners in Primary Health Care Settings Based on Leicester Assessment Package
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GU Jingmei, QIN Li, ZHAO Can, PENG Houxuan, XI Qian, SHEN Ying
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general practitioners ,consultation competency ,analytic hierarchy process ,assessment system ,leicester assessment package ,Medicine - Abstract
Background Training general practitioners (GPs) and improving the practice competence of "GP-centered" primary health care personnel are important directions of the development of human resources for primary health care in China. At present, there is lack of an index system applicable to evaluate clinical competence of GPs in the circumstances of primary health care in China, which not only hampers accurate identification of gaps in clinical competence of GPs, but also impedes sustainable improvement of the education and training of GPs as well as primary health care personnel. Objective To develop an evaluation index system for consultation competency of GPs in the circumstances of primary health care in China based on the original version of Leicester Assessment Package (LAP), so as to provide an index model reference for the objective evaluation of consultation competency of GPs. Methods Between May to August in 2022, a total of 15 experts were invited by using the purposive sampling method to implement the Delphi method by correspondence, to evaluate the importance, feasibility, and textual representation of each index in the initial evaluation index system for consultation competency of GPs. Analytic hierarchy process was adopted to calculate weight and combined weight for the first-level and secondary-level indexes. Results A total of two rounds of Delphi were conducted. The positivity coefficient, familiarity level, judgment coefficient, and authority coefficient were 100%, 0.77, 0.91, and 0.84 in both rounds of consultation; the mean score of the importance and feasibility of each indicator was 3.5, and the variation coefficient was 0.3. The Kendall coefficients for the importance and feasibility of the indexes in the two rounds of consultation were statistically different (P
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- 2024
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83. Contrastive Learning with Hard Negative Entities for Entity Set Expansion
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Li, Yinghui, Li, Yangning, He, Yuxin, Yu, Tianyu, Shen, Ying, and Zheng, Hai-Tao
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Computer Science - Computation and Language ,Computer Science - Information Retrieval - Abstract
Entity Set Expansion (ESE) is a promising task which aims to expand entities of the target semantic class described by a small seed entity set. Various NLP and IR applications will benefit from ESE due to its ability to discover knowledge. Although previous ESE methods have achieved great progress, most of them still lack the ability to handle hard negative entities (i.e., entities that are difficult to distinguish from the target entities), since two entities may or may not belong to the same semantic class based on different granularity levels we analyze on. To address this challenge, we devise an entity-level masked language model with contrastive learning to refine the representation of entities. In addition, we propose the ProbExpan, a novel probabilistic ESE framework utilizing the entity representation obtained by the aforementioned language model to expand entities. Extensive experiments and detailed analyses on three datasets show that our method outperforms previous state-of-the-art methods., Comment: Accepted by SIGIR 2022 (Full Paper)
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- 2022
84. The 2023 American Orthopaedic Association-Japanese Orthopaedic Association (AOA-JOA) Traveling Fellowship
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Balach, Tessa, D’Alleyrand, Jean-Claude, Ma, Shen-Ying (Richard), and Scolaro, John A.
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- 2024
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85. Autoantibody discovery across monogenic, acquired, and COVID-19-associated autoimmunity with scalable PhIP-seq.
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Vazquez, Sara E, Mann, Sabrina A, Bodansky, Aaron, Kung, Andrew F, Quandt, Zoe, Ferré, Elise MN, Landegren, Nils, Eriksson, Daniel, Bastard, Paul, Zhang, Shen-Ying, Liu, Jamin, Mitchell, Anthea, Proekt, Irina, Yu, David, Mandel-Brehm, Caleigh, Wang, Chung-Yu, Miao, Brenda, Sowa, Gavin, Zorn, Kelsey, Chan, Alice Y, Tagi, Veronica M, Shimizu, Chisato, Tremoulet, Adriana, Lynch, Kara, Wilson, Michael R, Kämpe, Olle, Dobbs, Kerry, Delmonte, Ottavia M, Bacchetta, Rosa, Notarangelo, Luigi D, Burns, Jane C, Casanova, Jean-Laurent, Lionakis, Michail S, Torgerson, Troy R, Anderson, Mark S, and DeRisi, Joseph L
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Humans ,Bacteriophages ,Autoimmune Diseases ,Homeodomain Proteins ,Proteome ,Autoantibodies ,Autoantigens ,Immunoprecipitation ,Autoimmunity ,COVID-19 ,APS1 ,IPEX ,PhIP-seq ,autoantibody ,autoantigen ,human ,immunology ,inflammation ,Autoimmune Disease ,Aetiology ,2.1 Biological and endogenous factors ,Inflammatory and immune system ,Human ,Biochemistry and Cell Biology - Abstract
Phage immunoprecipitation sequencing (PhIP-seq) allows for unbiased, proteome-wide autoantibody discovery across a variety of disease settings, with identification of disease-specific autoantigens providing new insight into previously poorly understood forms of immune dysregulation. Despite several successful implementations of PhIP-seq for autoantigen discovery, including our previous work (Vazquez et al., 2020), current protocols are inherently difficult to scale to accommodate large cohorts of cases and importantly, healthy controls. Here, we develop and validate a high throughput extension of PhIP-seq in various etiologies of autoimmune and inflammatory diseases, including APS1, IPEX, RAG1/2 deficiency, Kawasaki disease (KD), multisystem inflammatory syndrome in children (MIS-C), and finally, mild and severe forms of COVID-19. We demonstrate that these scaled datasets enable machine-learning approaches that result in robust prediction of disease status, as well as the ability to detect both known and novel autoantigens, such as prodynorphin (PDYN) in APS1 patients, and intestinally expressed proteins BEST4 and BTNL8 in IPEX patients. Remarkably, BEST4 antibodies were also found in two patients with RAG1/2 deficiency, one of whom had very early onset IBD. Scaled PhIP-seq examination of both MIS-C and KD demonstrated rare, overlapping antigens, including CGNL1, as well as several strongly enriched putative pneumonia-associated antigens in severe COVID-19, including the endosomal protein EEA1. Together, scaled PhIP-seq provides a valuable tool for broadly assessing both rare and common autoantigen overlap between autoimmune diseases of varying origins and etiologies.
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- 2022
86. SYNTHESIS AND CHARACTERIZATION OF DIALKYLALUMINUM, GALLIUM AND INDIUM [2-(N,N-DIMETHYLAMINOΜΕΤΗYL)-4-METHYL]PHΕNOXIDES. CRYSTAL STRUCTURE OF DIMETHYLGALLIUM [2-(N, N-DIMETHYLAMINOMΕΤΗYL)-4-METHYL]PHENOXIDE
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Shen, Ying-Zhong, Pan, Yi, Gu, Hong-Wei, Wu, Tong, Huang, Xiao-Ying, and Hu, HongWen
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Chemistry ,QD1-999 - Published
- 2000
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87. Automatic Depression Detection: An Emotional Audio-Textual Corpus and a GRU/BiLSTM-based Model
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Shen, Ying, Yang, Huiyu, and Lin, Lin
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Electrical Engineering and Systems Science - Audio and Speech Processing ,Computer Science - Artificial Intelligence ,Computer Science - Sound ,Quantitative Biology - Quantitative Methods - Abstract
Depression is a global mental health problem, the worst case of which can lead to suicide. An automatic depression detection system provides great help in facilitating depression self-assessment and improving diagnostic accuracy. In this work, we propose a novel depression detection approach utilizing speech characteristics and linguistic contents from participants' interviews. In addition, we establish an Emotional Audio-Textual Depression Corpus (EATD-Corpus) which contains audios and extracted transcripts of responses from depressed and non-depressed volunteers. To the best of our knowledge, EATD-Corpus is the first and only public depression dataset that contains audio and text data in Chinese. Evaluated on two depression datasets, the proposed method achieves the state-of-the-art performances. The outperforming results demonstrate the effectiveness and generalization ability of the proposed method. The source code and EATD-Corpus are available at https://github.com/speechandlanguageprocessing/ICASSP2022-Depression.
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- 2022
88. Correction: Sepsis Impairs Purkinje Cell Functions and Motor Behaviors Through Microglia Activation
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Zhao, Yue, Jiang, Yao, Shen, Ying, and Su, Li-Da
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- 2024
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89. Plasticity of the Cerebellum
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Wang, Xin-Tai, Shen, Ying, Gruol, Donna L., editor, Koibuchi, Noriyuki, editor, Manto, Mario, editor, Molinari, Marco, editor, Schmahmann, Jeremy D., editor, and Shen, Ying, editor
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- 2023
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90. Correction: Rare predicted loss-of-function variants of type I IFN immunity genes are associated with life-threatening COVID-19
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Daniela Matuozzo, Estelle Talouarn, Astrid Marchal, Peng Zhang, Jeremy Manry, Yoann Seeleuthner, Yu Zhang, Alexandre Bolze, Matthieu Chaldebas, Baptiste Milisavljevic, Adrian Gervais, Paul Bastard, Takaki Asano, Lucy Bizien, Federica Barzaghi, Hassan Abolhassani, Ahmad Abou Tayoun, Alessandro Aiuti, Ilad Alavi Darazam, Luis M. Allende, Rebeca Alonso-Arias, Andrés Augusto Arias, Gokhan Aytekin, Peter Bergman, Simone Bondesan, Yenan T. Bryceson, Ingrid G. Bustos, Oscar Cabrera-Marante, Sheila Carcel, Paola Carrera, Giorgio Casari, Khalil Chaïbi, Roger Colobran, Antonio Condino-Neto, Laura E. Covill, Ottavia M. Delmonte, Loubna El Zein, Carlos Flores, Peter K. Gregersen, Marta Gut, Filomeen Haerynck, Rabih Halwani, Selda Hancerli, Lennart Hammarström, Nevin Hatipoğlu, Adem Karbuz, Sevgi Keles, Christèle Kyheng, Rafael Leon-Lopez, Jose Luis Franco, Davood Mansouri, Javier Martinez-Picado, Ozge Metin Akcan, Isabelle Migeotte, Pierre-Emmanuel Morange, Guillaume Morelle, Andrea Martin-Nalda, Giuseppe Novelli, Antonio Novelli, Tayfun Ozcelik, Figen Palabiyik, Qiang Pan-Hammarström, Rebeca Pérez de Diego, Laura Planas-Serra, Daniel E. Pleguezuelo, Carolina Prando, Aurora Pujol, Luis Felipe Reyes, Jacques G. Rivière, Carlos Rodriguez-Gallego, Julian Rojas, Patrizia Rovere-Querini, Agatha Schlüter, Mohammad Shahrooei, Ali Sobh, Pere Soler-Palacin, Yacine Tandjaoui-Lambiotte, Imran Tipu, Cristina Tresoldi, Jesus Troya, Diederik van de Beek, Mayana Zatz, Pawel Zawadzki, Saleh Zaid Al-Muhsen, Mohammed Faraj Alosaimi, Fahad M. Alsohime, Hagit Baris-Feldman, Manish J. Butte, Stefan N. Constantinescu, Megan A. Cooper, Clifton L. Dalgard, Jacques Fellay, James R. Heath, Yu-Lung Lau, Richard P. Lifton, Tom Maniatis, Trine H. Mogensen, Horst von Bernuth, Alban Lermine, Michel Vidaud, Anne Boland, Jean-François Deleuze, Robert Nussbaum, Amanda Kahn-Kirby, France Mentre, Sarah Tubiana, Guy Gorochov, Florence Tubach, Pierre Hausfater, COVID Human Genetic Effort, COVIDeF Study Group, French COVID Cohort Study Group, CoV-Contact Cohort, COVID Clinicians, Orchestra Working Group, Amsterdam UMC Covid-19 Biobank, NIAID-USUHS COVID Study Group, Isabelle Meyts, Shen-Ying Zhang, Anne Puel, Luigi D. Notarangelo, Stephanie Boisson-Dupuis, Helen C. Su, Bertrand Boisson, Emmanuelle Jouanguy, Jean-Laurent Casanova, Qian Zhang, Laurent Abel, and Aurélie Cobat
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Medicine ,Genetics ,QH426-470 - Published
- 2024
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91. Intact fruit intake is nonlinear inversely associated with visceral adipose tissue area in U.S. adults: a cross-sectional study
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Gu, Xi, Gao, Ping, Shen, Ying, and Lu, Leiqun
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- 2024
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92. Preparation of water-soluble dietary fiber from bamboo shoots by fungi fermentation and its supplementation in biscuits
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Shen, Ying, Yang, Ling, Peng, Hong, Shen, Limin, Fu, Guiming, Wan, Yin, Liu, Yuhuan, Wu, Xiaodan, and Zheng, Hongli
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- 2024
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93. Development of low-temperature polycrystalline silicon process and novel 2T2C driving circuits for electric paper
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Jin, Yu, Shen, Ying, Xu, Wen-Jie, Fan, Wen-Zhi, Xu, Lei, Gao, Xiao-Yu, Wu, Yong, Zhou, Zhi-Yi, Gu, Wei-Jie, Yu, Dong-Liang, Sun, Jian-Qiu, Ke, Li-Juan, Zhang, Wei-Bin, Xu, Wei-Qi, and Xu, Feng-Ying
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- 2024
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94. Repeated trans-spinal magnetic stimulation promotes microglial phagocytosis of myelin debris after spinal cord injury through LRP-1
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Zhai, Chenyuan, Wang, Zun, Cai, Jili, Fang, Lu, Li, Xiangzhe, Jiang, Kunmao, Shen, Ying, Wang, Yu, Xu, Xingjun, Liu, Wentao, Wang, Tong, and Wu, Qi
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- 2024
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95. Separation cathode materials from current collectors of spent lithium-ion battery through low-energy mechanical friction technology
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Lin, Keyi, Wu, Yusen, Shen, Ying, Zheng, Yanrui, Wang, Zicheng, Chen, Jinjuan, Wu, Taoli, Zhu, Jie, Huang, Zhe, Qin, Baojia, and Ruan, Jujun
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- 2024
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96. Self-powered sandwich-type dual-mode sensor built on open bipolar electrode
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Wang, Zheng, Shen, Ying-zhuo, Xu, Man, Zhu, Jiayuan, Ma, Cheng, Hu, Xiao-Ya, and Xu, Qin
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- 2024
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97. Phthalate exposure and markers of biological aging: The mediating role of inflammation and moderating role of dietary nutrient intake
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Xu, Xin, Zheng, Jianheng, Li, Jing, Shen, Ying, Zhu, Leiyan, Jin, Yan, Zhang, Mei, Yang, Shuyu, Du, Jun, Wang, Huatao, Chen, Bo, and Dong, Ruihua
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- 2024
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98. Long-term subsoiling and tillage rotation increase carbon storage in soil aggregates and the abundance of autotrophs
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Shen, Ying, Zhang, Renzheng, Yang, Qian, Liu, Zhen, Li, Geng, Han, Huifang, Kuzyakov, Yakov, and Ning, Tangyuan
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- 2024
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99. Combined Photothermal Therapy and Cancer Immunotherapy by Immunogenic Hollow Mesoporous Silicon-Shelled Gold Nanorods
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Cao, Keyue, Zhou, Yao, Shen, Ying, Wang, Yifei, Huang, Haiqin, and Zhu, Hongyan
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- 2024
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100. Lack of association between classical HLA genes and asymptomatic SARS-CoV-2 infection
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Abel, Laurent, Aiuti, Alessandro, Al-Muhsen, Saleh, Al-Mulla, Fahd, Amara, Ali, Anderson, Mark S., Andreakos, Evangelos, Arias, Andrés A., Arkin, Lisa M., Feldman, Hagit Baris, Bastard, Paul, Belot, Alexandre, Biggs, Catherine M., Bogunovic, Dusan, Bolze, Alexandre, Bondarenko, Anastasiia, Borghesi, Alessandro, Bousfiha, Ahmed A., Brodin, Petter, Bryceson, Yenan, Butte, Manish J., Casanova, Jean-Laurent, Casari, Giorgio, Christodoulou, John, Cobat, Aurélie, Colobran, Roger, Condino-Neto, Antonio, Constantinescu, Stefan N., Cooper, Megan A., Dalgard, Clifton L., Desai, Murkesh, Drolet, Beth A., Duval, Xavier, El Baghdadi, Jamila, Eloy, Philippine, Espinosa-Padilla, Sara, Fellay, Jacques, Flores, Carlos, Franco, José Luis, Froidure, Antoine, Gorochov, Guy, Gregersen, Peter K., Grimbacher, Bodo, Haerynck, Filomeen, Hagin, David, Halwani, Rabih, Hammarström, Lennart, Heath, James R., Hsieh, Elena W.Y., Husebye, Eystein, Imai, Kohsuke, Itan, Yuval, Jouanguy, Emmanuelle, Kaja, Elżbieta, Karamitros, Timokratis, Kisand, Kai, Ku, Cheng-Lung, Lau, Yu-Lung, Ling, Yun, Lucas, Carrie L., Maniatis, Tom, Mansouri, Davood, Maródi, László, Mentré, France, Meyts, Isabelle, Milner, Joshua D., Mironska, Kristina, Mogensen, Trine H., Morio, Tomohiro, Ng, Lisa F.P., Notarangelo, Luigi D., Novelli, Antonio, Novelli, Giuseppe, O'Farrelly, Cliona, Okada, Satoshi, Okamoto, Keisuke, Ozcelik, Tayfun, Pan-Hammarström, Qiang, Pape, Jean W., Perez de Diego, Rebeca, Perez-Tur, Jordi, Perlin, David S., Pesole, Graziano, Planas, Anna M., Prando, Carolina, Pujol, Aurora, Puel, Anne, Quintana-Murci, Lluis, Ramaswamy, Sathishkumar, Renia, Laurent, Resnick, Igor, Rodríguez-Gallego, Carlos, Sancho-Shimizu, Vanessa, Sediva, Anna, Seppänen, Mikko R.J., Shahrooei, Mohammad, Shcherbina, Anna, Slaby, Ondrej, Snow, Andrew L., Soler-Palacín, Pere, Soumelis, Vassili, Spaan, András N., Tancevski, Ivan, Tangye, Stuart G., Tayoun, Ahmad Abou, Temel, Şehime Gülsün, Thorball, Christian, Tiberghien, Pierre, Trouillet-Assant, Sophie, Turvey, Stuart E., Uddin, K. M. Furkan, Uddin, Mohammed J., van de Beek, Diederik, Vinh, Donald C., von Bernuth, Horst, Wauters, Joost, Zatz, Mayana, Zawadzki, Pawel, Zhang, Qian, Zhang, Shen-Ying, Bureau, Serge, Vacher, Yannick, Gysembergh-Houal, Anne, Demerville, Lauren, Benleulmi-Chaachoua, Abla, Abad, Sebastien, Abassi, Radhiya, Abdellaoui, Abdelrafie, Abdelmalek, Abdelkrim, Abdoul, Hendy, Abergel, Helene, Abeud, Fariza, Abgrall, Sophie, Abisror, Noemie, Adechian, Marylise, Aderdour, Nordine, Admane, Hakeem Farid, Adnet, Frederic, Afritt, Sara, Agostini, Helene, Aguilar, Claire, Agut, Sophie, Aiello, Tommaso Francesco, Kaci, Marc Ait, Oufella, Hafid Ait, Ajeenthiravasan, Gokula, Alauzy, Virginie, Alby-Laurent, Fanny, Allard, Lucie, Alyanakian, Marie-Alexandra, Borrero, Blanca Amador, Amam, Sabrina, Amrouche, Lucile, Andronikof, Marc, Anglicheau, Dany, Anguel, Nadia, Annane, Djillali, Aounzou, Mohammed, Aparicio, Caroline, Aratus, Gladys, Arlet, Jean-Benoit, Arzoine, Jeremy, Aslangul, Elisabeth, Assefi, Mona, Aubry, Adeline, Audiffred, Laetitia, Audureau, Etienne, Auger, Christelle Nathalie, Auregan, Jean-Charles, Awotar, Celine, Milla, Sonia Ayllon, Azan, Delphine, Azemar, Laurene, Azzouguen, Billal, Elrufaai, Marwa Bachir, Badsi, Aïda, Bakouboula, Prissile, Balcerowiak, Coline, Balde, Fanta, Baldivia, Elodie, Bangamingo, Eliane-Flore, Baptiste, Amandine, Baran-Marszak, Fanny, Barau, Caroline, Barget, Nathalie, Baronnet, Flore, Barthelemy, Romain, Baudel, Jean-Luc, Baudry, Camille, Baudry, Elodie, Beaugerie, Laurent, Belamri, Adel, Belaube, Nicolas, Belilita, Rhida, Bellassen, Pierre, Belmokhtar, Rawan, Beltran, Isabel, Benainous, Ruben, Benallaoua, Mourad, Benamouzig, Robert, Benbara, Amélie, Benhida, Jaouad, Benkhelouf, Anis, Benlagha, Jihene, Benmostafa, Chahinez, Benothmane, Skander, Bentifraouine, Miassa, Berard, Laurence, Bernier, Quentin, Berti, Enora, Bertier, Astrid, Berton, Laure, Bessis, Simon, Beurton, Alexandra, Bianco, Celine, Bianquis, Clara, Bidar, Frank, Blanche, Philippe, Blayau, Clarisse, Bleibtreu, Alexandre, Blin, Emmanuelle, Bloch-Queyrat, Coralie, Boissier, Marie-Christophe, Bollens, Diane, Bolzoni, Marion, Bompard, Rudy pierre, Bonnet, Nicolas, Bonnouvrier, Justine, Botha, Shirmonecrystal, Boucenna, Wissam, Bouchama, Fatiha, Bouchaud, Olivier, Bouchghoul, Hanane, Boudjebla, Taoueslylia, Boudjema, Noel, Bouffard, Catherine, Bougle, Adrien, Bouguerra, Meriem, Bouras, Leila, Bourcier, Agnes, Durand, Anne Bourgarit, Bourrier, Anne, Bouscarat, Fabrice, Bouvry, Diane, Bouziri, Nesrine, Bouzrara, Ons, Bribier, Sarah, Brugier, Delphine, Brunel, Melanie, Bui, Eida, Buisson, Anne, Bukreyeva, Iryna, Bureau, Côme, Cadranel, Jacques, Cailhol, Johann, Calin, Ruxandra, Vega, Clara Campos, Canavaggio, Pauline, Cancella, Marta, Cantin, Delphine, Cao, Albert, Carbillon, Lionel, Carlier, Nicolas, Cassard, Clementine, Castor, Guylaine, Cauchy, Marion, Cha, Olivier, Chaigne, Benjamin, Challal, Salima, Champion, Karine, Chariot, Patrick, Chas, Julie, Chauveau, Simon, 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Demeret, Sophie, Demoule, Alexandre, Deniau, Aurore, Depret, François, Derolez, Sophie, Derradji, Ouda, Derridj, Nawal, Descamps, Vincent, Deschamps, Lydia, Desconclois, Celine, Desnos, Cyrielle, Desongins, Karine, Dhote, Robin, Diallo, Benjamin, Didier, Morgane, Diemer, Myriam, Diez, Stephane, Djadi-Prat, Juliette, Djamouri Monnory, Fatima-Zohra, Djebara, Siham, Djebra, Naoual, Djietcheu, Minette, Djillali, Hadjer, Djouadi, Nouara, Donneger, Severine, Santos, Catarina Dos, Dournon, Nathalie, Dres, Martin, Droctove, Laura, Drogrey, Marie, Dropy, Margot, Drouet, Elodie, Dubosq, Valérie, Dubreucq, Evelyne, Dubus, Estelle, Duchemann, Boris, Duchenoy, Thibault, Dudoignon, Emmanuel, Dufau, Romain, Dumas, Florence, Duran, Clara, Duron, Emmanuelle, Durrbach, Antoine, Duvivier, Claudine, Ebstein, Nathan, El Khalifa, Jihane, Elabbadi, Alexandre, Elie, Caroline, Ernotte, Gabriel, Esling, Anne, Etienne, Martin, Eyer, Xavier, Fartoukh, Muriel Sarah, Fayali, Takoua, Fermaut, Marion, Fiorentino, 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Ghilas, Imarazene, Meriem, Ingiliz, Patrick, Iratni, Lina, Jaureguiberry, Stephane, Jean-Marc, Jean-Francois, Jeyarajasingham, Deleena, Jouany, Pauline, Jouis, Veronique, Jourdaine, Clement, Kafif, Ouifiya, Kallala, Rim, Katsahian, Sandrine, Kelesyan, Lilit, Keo, Vixra, Ketz, Flora, Khamis, Warda, Khelili, Enfel, Khellaf, Mehdi, Kotokpo Youkou, Christy Gaëlla, Kounis, Ilias, Kpalma, Gaelle, Krause, Jessica, Labbe, Vincent, Lacombe, Karine, Lacorte, Jean-Marc, Lafont, Anne Gaelle, Lafont, Emmanuel, Lagha, Lynda, Lamhaut, Lionel, Lancelot, Aymeric, Landman, Cecilia, Lanternier, Fanny, Larcheveque, Cecile, Combe, Caroline Lascoux, Lassel, Ludovic, Laverdant, Benjamin, Lavergne, Christophe, Lavillegrand, Jean-Rémi, Lazureanu, Pompilia, Le Guennec, Loïc, Leberre, Lamia, Leblanc, Claire, Leboyer, Marion, Lecomte, Francois, Lecorre, Marine, Leenhardt, Romain, Lefebvre, Marylou, Lefebvre, Bénédicte, Legendre, Paul, Leger, Anne, Legros, Laurence, Legrosse, Justyna, Lehuunghia, Sébastien, Lemarec, Julien, Leporrier-Ext, Jeremie, Lesein, Manon, Lesur, Hubert, Levy, Vincent, Levy, Albert, Lopes, Edwige, Lopes, Amanda, Lopez, Vanessa, Lopinto, Julien, Lortholary, Olivier, Louadah, Badr, Loze, Bénédicte, Lucas, Marie-Laure, Lucasamichi, Axelle, Luong, Liem Binh, Magazimama-Ext, Arouna, Maingret, David, Mameri, Lakhdar, Manivet, Philippe, Mansouri, Cylia, Marcault, Estelle, Marey, Jonathan, Marin, Nathalie, Marois, Clémence, Martin, Olivier, Martineau, Lou, Martinez-Lopez, Cannelle, Martyniuck, Pierre, De Farcy, Pauline Mary, Marzouk, Nessrine, Masmoudi, Rafik, Mebazaa, Alexandre, Mechai, Frédéric, Mecozzi, Fabio, Mediouni, Chamseddine, Megarbane, Bruno, Meghadecha, Mohamed, Mejean, Élodie, Mekinian, Arsene, Abdelhadi, Nour Mekki, Mekni, Rania, Meliti, Thinhinan Sabrina, Lima, Breno Melo, Meng, Paris, Merbah, Soraya, Messani, Fadhila, Messaoudi, Yasmine, Mewasing, Baboo-Irwinsingh, Meziane, Lydia, Michelot-Burger, Carole, Mignot, Françoise, Minka, Fadi Hillary, Miyara, Makoto, Moine, Pierre, Molina, Jean-Michel, Montegnies-Boulet, Anaïs, Monti, Alexandra, Montlahuc, Claire, Montout, Anne-Lise, Moores, Alexandre, Morbieu, Caroline, Mortelette, Helene, Mouly, Stéphane, Muzaffar, Rosita, Nacerddine, Cherifa Iness, Nadal, Marine, Nadif, Hajer, Nassarmadji, Kladoum, Natella, Pierre, Ndingamondze, Sandrine, Neraal, Stefan, Nguyen, Caroline, N'Guyen, Bao, Larmurier, Isabelle Nion, Nlomenyengue, Luc, Noel, Nicolas, Nunes, Hilario, Omar, Edris, Ouazene, Zineb, Ouedraogo, Elise, Ouelaa, Wassila, Oukhedouma, Anissa, Amara, Yasmina Ould, Oya, Herve, Oziel, Johanna, Padilla, Thomas, Paillaud, Elena, Paiva, Solenne, Parfait, Beatrice, Parize, Perrine, Parizot, Christophe, Parrot, Antoine, Pavot, Arthur, Peaudecerf, Laetitia, Pene, Frédéric, Pepin, Marion, Pernet, Julie, Pernin, Claire, Petit, Mylène, Peyrony, Olivier, Pietri, Marie-Pierre, Pietri, Olivia, De Chambrun, Marc Pineton, Pinson, Michelle, Pintado, Claire, Piquard, Valentine, Pires, Christine, Planquette, Benjamin, Poirier, Sandrine, Pomel, Anne-Laure, Pons, Stéphanie, Ponscarme, Diane, Pourcelot, Annegaelle, Pourcher, Valérie, Pouvaret, Anne, Prever, Florian, Previlon, Miresta, Prevost, Margot, Provoost, Marie-Julie, Quemeneur, Cyril, Rafat, Cédric, Rami, Agathe, Ranque, Brigitte, Raphael, Maurice, Raphalen, Jean Herle, Rastoin, Anna, Raux, Mathieu, Rebai, Amani, Reby, Michael, Regent, Alexis, Regrag, Asma, Resche-Rigon, Matthieu, Ressaire, Quentin, Richard, Christian, Richard, Mariecaroline, Robert, Maxence, Rohaut, Benjamin, Rolland-Debord, Camille, Ropers, Jacques, Roque-Afonso, Anne-Marie, Rosso, Charlotte, Rousseaux, Mélanie, Rousseaux, Nabila, Roux, Swasti, Roux, Lorène, Rouzaud, Claire, Rozes, Antoine, Rubenstein, Emma, Sabate, Jean-Marc, Sabet, Sheila, Sacleux, Sophie-Caroline, Kermanach, Nathalie Saidenberg, Saliba, Faouzi, Salmon, Dominique, Savale, Laurent, Savary, Guillaume, Sberro, Rebecca, Scemla, Anne, Schlemmer, Frederic, Schwartz, Mathieu, Sedfi, Saïd, Sefir-Kribel, Samia, Seksik, Philippe, Sellier, Pierre, Selves, Agathe, Sembach, Nicole, Semerano, Luca, Senat, Marie-Victoire, Sene, Damien, Serris, Alexandra, Sese, Lucile, Sghiouar, Naima, Sigaux, Johanna, Siguier, Martin, Silvain, Johanne, Simon, Noémie, Simon, Tabassome, Skandri, Lina Innes, Slimani, Miassa, Snauwaert, Aurélie, Sokol, Harry, Soliman, Heithem, Soltani, Nisrine, Soyer, Benjamin, Steg, Gabriel, Suarez, Lydia, Szwebel, Tali-Anne, Taffame, Kossi, Tandjaoui-Lambiotte, Yacine, Tantet, Claire, Tateo, Mariagrazia, Theodose, Igor, Thiebaud, Pierre clement, Thomas, Caroline, Tiercelet, Kelly, Tisserand, Julie, Tomczak, Carole, Torelino, Krystel, Touam-Ext, Fatima, Toumi, Lilia, Toury, Gustave, Toy-Miou, Mireille, Dinh Thanh Lien, Olivia Tran, Trandinh, Alexy, Treluyer, Jean-Marc, Trinque, Baptiste, Truchot, Jennifer, Tubach, Florence, Tubiana, Sarah, Tunesi, Simone, Turpin, Matthieu, Turpin, Agathe, Urbina, Tomas, Narvaez, Rafael Usubillaga, Uzunhan, Yurdagul, Vaittinadaayar, Prabakar, Valent, Arnaud, Valentian, Maelle, Valin, Nadia, Vallet, Hélène, Vaz, Marina, Vazquezibarra, Miguel-Alejandro, Vedie, Benoit, Velly, Laetitia, Verstuyft, Celine, Viallette, Cedric, Vicaut, Eric, Vignes, Dorothee, Vimpere, Damien, Virlouvet, Myriam, Voiriot, Guillaume, Voisot, Lena, Weiss, Emmanuel, Weiss, Nicolas, Winchenne, Anaïs, Yordanov, Youri, Zafrani, Lara, Zaidan, Mohamad, Zaidi, Wissem, Zak, Cathia, Zarhrate-Ghoul, Aida, Zatout, Ouassila, Zeino, Suzanne, Zeitouni, Michel, Zemirli, Naïma, Zerah, Lorene, Zia, Ounsa, Ziol, Marianne, Zolario, Oceane, Zuber, Julien, Andrejak, Claire, Angoulvant, François, Bachelet, Delphine, Bartoli, Marie, Basmaci, Romain, Behillil, Sylvie, Beluze, Marine, Benkerrou, Dehbia, Bhavsar, Krishna, Bouadma, Lila, Bouchez, Sabelline, Bouscambert, Maude, Cervantes-Gonzalez, Minerva, Chair, Anissa, Chirouze, Catherine, Coelho, Alexandra, Couffin-Cadiergues, Sandrine, d’Ortenzio, Eric, Debray, Marie-Pierre, Deconinck, Laurene, 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Huong, Picone, Olivier, Puéchal, Oriane, Rabaud, Christian, Rosa-Calatrava, Manuel, Rossignol, Bénédicte, Rossignol, Patrick, Roy, Carine, Schneider, Marion, Su, Richa, Tardivon, Coralie, Tellier, Marie-Capucine, Téoulé, François, Terrier, Olivier, Timsit, Jean-François, Tual, Christelle, Van Der Werf, Sylvie, Vanel, Noémie, Veislinger, Aurélie, Visseaux, Benoit, Wiedemann, Aurélie, Yazdanpanah, Yazdan, Alavoine, Loubna, Burdet, Charles, Charpentier, Charlotte, Dechanet, Aline, Ecobichon, Jean-Luc, Frezouls, Wahiba, Houhou, Nadhira, Lehacaut, Jonathan, Manchon, Pauline, Nouroudine, Mariama, Quintin, Caroline, Thy, Michael, van der Werf, Sylvie, Vignali, Valérie, Chahine, Abir, Waucquier, Nawal, Migaud, Maria-Claire, Djossou, Félix, Mergeay-Fabre, Mayka, Lucarelli, Aude, Demar, Magalie, Bruneau, Léa, Gérardin, Patrick, Maillot, Adrien, Payet, Christine, Laviolle, Bruno, Laine, Fabrice, Paris, Christophe, Desille-Dugast, Mireille, Fouchard, Julie, Pistone, Thierry, Perreau, Pauline, Gissot, Valérie, Goas, Carole L.E., Montagne, Samatha, Richard, Lucie, Bouiller, Kévin, Desmarets, Maxime, Meunier, Alexandre, Bourgeon, Marilou, Lefévre, Benjamin, Jeulin, Hélène, Legrand, Karine, Lomazzi, Sandra, Tardy, Bernard, Gagneux-Brunon, Amandine, Bertholon, Frédérique, Botelho-Nevers, Elisabeth, Kouakam, Christelle, Nicolas, Leturque, Roufai, Layidé, Amat, Karine, Espérou, Hélène, Hendou, Samia, Foti, Giuseppe, Citerio, Giuseppe, Contro, Ernesto, Pesci, Alberto, Valsecchi, Maria Grazia, Cazzaniga, Marina, Bellani, Giacomo, Abad, Jorge, Accordino, Giulia, Angelini, Micol, Aguilera-Albesa, Sergio, Aguiló-Cucurull, Aina, Özkan, Esra Akyüz, Darazam, Ilad Alavi, Roblero Albisures, Jonathan Antonio, Aldave, Juan C., Ramos, Miquel Alfonso, Khan, Taj Ali, Aliberti, Anna, Nadji, Seyed Alireza, Alkan, Gulsum, AlKhater, Suzan A., Allardet-Servent, Jerome, Allende, Luis M., Alonso-Arias, Rebeca, Alshahrani, Mohammed S., Alsina, Laia, Amoura, Zahir, Antolí, Arnau, Arrestier, Romain, Aubart, Mélodie, Auguet, Teresa, Avramenko, Iryna, Aytekin, Gökhan, Azot, Axelle, Bahram, Seiamak, Bajolle, Fanny, Baldanti, Fausto, Baldolli, Aurélie, Ballester, Maite, Barrou, Benoit, Barzaghi, Federica, Basso, Sabrina, Bayhan, Gulsum Iclal, Bezrodnik, Liliana, Bilbao, Agurtzane, Blanchard-Rohner, Geraldine, Blanco, Ignacio, Blandinières, Adeline, Blázquez-Gamero, Daniel, Bloomfield, Marketa, Bolivar-Prados, Mireia, Borie, Raphael, Botdhlo-Nevers, Elisabeth, Bousquet, Aurore, Boutolleau, David, Bouvattier, Claire, Boyarchuk, Oksana, Bravais, Juliette, Briones, M. 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Gonzalo, Oualha, Mehdi, Ouedrani, Amani, Özçelik, Tayfun, Ozkaya-Parlakay, Aslinur, Pagani, Michele, Papadaki, Maria, Parola, Philippe, Pascreau, Tiffany, Paul, Stéphane, Paz-Artal, Estela, Pedraza, Sigifredo, González Pellecer, Nancy Carolina, Pellegrini, Silvia, Pérez de Diego, Rebeca, Pérez-Fernández, Xosé Luis, Philippe, Aurélien, Philippot, Quentin, Picod, Adrien, Pineton de Chambrun, Marc, Piralla, Antonio, Planas-Serra, Laura, Ploin, Dominique, Poissy, Julien, Poncelet, Géraldine, Poulakou, Garyphallia, Pouletty, Marie S., Pourshahnazari, Persia, Qiu-Chen, Jia Li, Quentric, Paul, Rambaud, Thomas, Raoult, Didier, Raoult, Violette, Rebillat, Anne-Sophie, Redin, Claire, Resmini, Léa, Ricart, Pilar, Richard, Jean-Christophe, Rigo-Bonnin, Raúl, Rivet, Nadia, Rivière, Jacques G., Rocamora-Blanch, Gemma, Rodero, Mathieu P., Rodrigo, Carlos, Rodriguez, Luis Antonio, Rodriguez-Gallego, Carlos, Rodriguez-Palmero, Agustí, Romero, Carolina Soledad, Rothenbuhler, Anya, Roux, Damien, Rovina, Nikoletta, Rozenberg, Flore, Ruch, Yvon, Ruiz, Montse, Ruiz del Prado, Maria Yolanda, Ruiz-Rodriguez, Juan Carlos, Sabater-Riera, Joan, Saks, Kai, Salagianni, Maria, Sanchez, Oliver, Sánchez-Montalvá, Adrián, Sánchez-Ramón, Silvia, Schidlowski, Laire, Schluter, Agatha, Schmidt, Julien, Schmidt, Matthieu, Schuetz, Catharina, Schweitzer, Cyril E., Scolari, Francesco, Seijo, Luis, Seminario, Analia Gisela, Seng, Piseth, Senoglu, Sevtap, Seppänen, Mikko, Llovich, Alex Serra, Siguret, Virginie, Siouti, Eleni, Smadja, David M., Smith, Nikaia, Sobh, Ali, Solanich, Xavier, Solé-Violán, Jordi, Soler, Catherine, Sözeri, Betül, Stella, Giulia Maria, Stepanovskiy, Yuriy, Stoclin, Annabelle, Taccone, Fabio, Taupin, Jean-Luc, Tavernier, Simon J., Tello, Loreto Vidaur, Terrier, Benjamin, Thiery, Guillaume, Thorn, Karolina, Thumerelle, Caroline, Tipu, Imran, Tolstrup, Martin, Tomasoni, Gabriele, Toubiana, Julie, Alvarez, Josep Trenado, Triantafyllia, Vasiliki, Troya, Jesús, Tsang, Owen T.Y., Tserel, Liina, Tso, Eugene Y.K., Tucci, Alessandra, Tüter Öz, Şadiye Kübra, Ursini, Matilde Valeria, Utsumi, Takanori, Vabres, Pierre, Valencia-Ramos, Juan, Van Den Rym, Ana Maria, Vandernoot, Isabelle, Velez-Santamaria, Valentina, Zuniga Veliz, Silvia Patricia, Vidigal, Mateus C., Viel, Sébastien, Villain, Cédric, Vilaire-Meunier, Marie E., Villar-García, Judit, Vincent, Audrey, Van der Linden, Dimitri, Volokha, Alla, Vuotto, Fanny, Wauters, Els, Wu, Alan K.L., Wu, Tak-Chiu, Yahşi, Aysun, Yesilbas, Osman, Yildiz, Mehmet, Young, Barnaby E., Yükselmiş, Ufuk, Zecca, Marco, Zuccaro, Valentina, Van Praet, Jens, Lambrecht, Bart N., Van Braeckel, Eva, Bosteels, Cédric, Hoste, Levi, Hoste, Eric, Bauters, Fré, De Clercq, Jozefien, Heijmans, Catherine, Slabbynck, Hans, Naesens, Leslie, Florkin, Benoit, Young, Mary-Anne, Willis, Amanda, Lapuente-Suanzes, Paloma, de Andrés-Martín, Ana, Berkell, Matilda, Carelli, Valerio, Fiorentino, Alessia, Malhotra, Surbhi, Mattiaccio, Alessandro, Pippucci, Tommaso, Seri, Marco, Tacconelli, Evelina, van Agtmael, Michiel, Algera, Anne Geke, Appelman, Brent, van Baarle, Frank, Bax, Diane, Beudel, Martijn, Bogaard, Harm Jan, Bomers, Marije, Bonta, Peter, Bos, Lieuwe, Botta, Michela, de Brabander, Justin, de Bree, Godelieve, de Bruin, Sanne, Buis, David T.P., Bugiani, Marianna, Bulle, Esther, Chouchane, Osoul, Cloherty, Alex, Dijkstra, Mirjam, Dongelmans, Dave A., Dujardin, Romein W.G., Elbers, Paul, Fleuren, Lucas, Geerlings, Suzanne, Geijtenbeek, Theo, Girbes, Armand, Goorhuis, Bram, Grobusch, Martin P., Hafkamp, Florianne, Hagens, Laura, Hamann, Jorg, Harris, Vanessa, Hemke, Robert, Hermans, Sabine M., Heunks, Leo, Hollmann, Markus, Horn, Janneke, Hovius, Joppe W., de Jong, Menno D., Koning, Rutger, Lim, Endry H.T., van Mourik, Niels, Nellen, Jeaninne, Nossent, Esther J., Paulus, Frederique, Peters, Edgar, Pina-Fuentes, Dan A.I., van der Poll, Tom, Preckel, Bennedikt, Prins, Jan M., Raasveld, Jorinde, Reijnders, Tom, de Rotte, Maurits C.F. J., Schinkel, Michiel, Schultz, Marcus J., Schrauwen, Femke A.P., Schuurmans, Alex, Schuurmans, Jaap, Sigaloff, Kim, Slim, Marleen A., Smeele, Patrick, Smit, Marry, Stijnis, Cornelis S., Stilma, Willemke, Teunissen, Charlotte, Thoral, Patrick, Tsonas, Anissa M., Tuinman, Pieter R., van der Valk, Marc, Veelo, Denise P., Volleman, Carolien, de Vries, Heder, Vught, Lonneke A., van Vugt, Michèle, Wouters, Dorien, Zwinderman, A.H., Brouwer, Matthijs C., Wiersinga, W. Joost, Vlaar, Alexander P.J., Tompkins, Miranda F., Alba, Camille, Hupalo, Daniel N., Rosenberger, John, Sukumar, Gauthaman, Wilkerson, Matthew D., Zhang, Xijun, Lack, Justin, Oler, Andrew J., Dobbs, Kerry, Delmonte, Ottavia M., Danielson, Jeffrey J., Biondi, Andrea, Bettini, Laura Rachele, D’Angiò, Mariella, Beretta, Ilaria, Imberti, Luisa, Sottini, Alessandra, Quaresima, Virginia, Quiros-Roldan, Eugenia, Rossi, Camillo, Castagnoli, Riccardo, Montagna, Daniela, Licari, Amelia, Marseglia, Gian Luigi, Marchal, Astrid, Cirulli, Elizabeth T., Neveux, Iva, Bellos, Evangelos, Thwaites, Ryan S., Schiabor Barrett, Kelly M., Zhang, Yu, Nemes-Bokun, Ivana, Kalinova, Mariya, Catchpole, Andrew, Lack, Justin B., Chiu, Christopher, and Grzymski, Joseph J.
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