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163. Results from Phase I Extension Study Assessing Pexidartinib Treatment in Six Cohorts with Solid Tumors including TGCT, and Abnormal CSF1 Transcripts in TGCT

Author

Tap, William D, Singh, Arun S, Anthony, Stephen Patrick, Sterba, Mike, Zhang, Chao, Healey, John H, Chmielowski, Bartosz, Cohn, Allen Lee, Shapiro, Geoffrey I, Keedy, Vicki L, Wainberg, Zev A, Puzanov, Igor, Cote, Gregory M, Wagner, Andrew J, Braiteh, Fadi, Sherman, Eric, Hsu, Henry H, Peterfy, Charles, Gelhorn, Heather L, Ye, Xin, Severson, Paul, West, Brian L, Lin, Paul S, and Tong-Starksen, Sandra

Subjects
Rare Diseases, Cancer, Genetics, Clinical Research, Urologic Diseases, Adult, Aminopyridines, Giant Cell Tumor of Tendon Sheath, Humans, Protein Kinase Inhibitors, Pyrroles, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

PurposeTo assess the response to pexidartinib treatment in six cohorts of adult patients with advanced, incurable solid tumors associated with colony-stimulating factor 1 receptor (CSF1R) and/or KIT proto-oncogene receptor tyrosine kinase activity.Patients and methodsFrom this two-part phase I, multicenter study, pexidartinib, a small-molecule tyrosine kinase inhibitor that targets CSF1R, KIT, and FMS-like tyrosine kinase 3 (FLT3), was evaluated in six adult patient cohorts (part 2, extension) with advanced solid tumors associated with dysregulated CSF1R. Adverse events, pharmacokinetics, and tumor responses were assessed for all patients; patients with tenosynovial giant cell tumor (TGCT) were also evaluated for tumor volume score (TVS) and patient-reported outcomes (PRO). CSF1 transcripts and gene expression were explored in TGCT biopsies.ResultsNinety-one patients were treated: TGCT patients (n = 39) had a median treatment duration of 511 days, while other solid tumor patients (n = 52) had a median treatment duration of 56 days. TGCT patients had response rates of 62% (RECIST 1.1) and 56% (TVS) for the full analysis set. PRO assessments for pain showed improvement in patient symptoms, and 76% (19/25) of TGCT tissue biopsy specimens showed evidence of abnormal CSF1 transcripts. Pexidartinib treatment of TGCT resulted in tumor regression and symptomatic benefit in most patients. Pexidartinib toxicity was manageable over the entire study.ConclusionsThese results offer insight into outcome patterns in cancers whose biology suggests use of a CSF1R inhibitor. Pexidartinib results in tumor regression in TGCT patients, providing prolonged control with an acceptable safety profile.

Published
2022

164. Speech2Slot: An End-to-End Knowledge-based Slot Filling from Speech

Author

Wang, Pengwei, Ye, Xin, Zhou, Xiaohuan, Xie, Jinghui, and Wang, Hao

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

In contrast to conventional pipeline Spoken Language Understanding (SLU) which consists of automatic speech recognition (ASR) and natural language understanding (NLU), end-to-end SLU infers the semantic meaning directly from speech and overcomes the error propagation caused by ASR. End-to-end slot filling (SF) from speech is an essential component of end-to-end SLU, and is usually regarded as a sequence-to-sequence generation problem, heavily relied on the performance of language model of ASR. However, it is hard to generate a correct slot when the slot is out-of-vovabulary (OOV) in training data, especially when a slot is an anti-linguistic entity without grammatical rule. Inspired by object detection in computer vision that is to detect the object from an image, we consider SF as the task of slot detection from speech. In this paper, we formulate the SF task as a matching task and propose an end-to-end knowledge-based SF model, named Speech-to-Slot (Speech2Slot), to leverage knowledge to detect the boundary of a slot from the speech. We also release a large-scale dataset of Chinese speech for slot filling, containing more than 830,000 samples. The experiments show that our approach is markedly superior to the conventional pipeline SLU approach, and outperforms the state-of-the-art end-to-end SF approach with 12.51% accuracy improvement.

Published
2021

166. Guilin Zhangtai Group Co., Ltd., Guangxi Lichengdong Investment Co., Ltd. et al. : (Enforcement Review of the Ruling on Dispute over Recovery of Financial Distressed Debt: Identification of Interest in Cases of Enforcement Against Dispute over Recovery of Financial Distressed Debt)

Author

Xiang, Guohui, Ye, Xin, China Applied Jurisprudence Institute, Zhu, Feng, With Contrib. by, Ding, Wenyan, With Contrib. by, Han, Hongyu, With Contrib. by, Ma, Qiujing, With Contrib. by, Zheng, Daxuan, Translated by, Cao, Zhijian, Translated by, Sun, Lin, Translated by, Zhu, Xiaohua, Translated by, Niu, Benlin, Translated by, Duan, Jing, Translated by, Xiao, Jialiu, Translated by, and Zheng, Yi, Translated by

Published
2023
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168. Domain Knowledge Adapted Semi-supervised Learning with Mean-Teacher Strategy for Circulating Abnormal Cells Identification

Author

Wang, Huajia, Kuang, Yinglan, Fan, Xianjun, Zhou, Yanling, Ye, Xin, Lu, Xing, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Qin, Wenjian, editor, Zaki, Nazar, editor, Zhang, Fa, editor, Wu, Jia, editor, Yang, Fan, editor, and Li, Chao, editor

Published
2023
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169. Deep Reinforcement Learning for Group-Aware Robot Navigation in Crowds

Author

Zhou, Xianwei, Ye, Xin, Zhang, Kun, Yu, Songsen, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Jin, Zhi, editor, Jiang, Yuncheng, editor, Buchmann, Robert Andrei, editor, Bi, Yaxin, editor, Ghiran, Ana-Maria, editor, and Ma, Wenjun, editor

Published
2023
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171. Research on Driving Cycle Recognition Strategy Based on Machine Learning

Author

Ye, Xin, Lu, Jintao, Tian, Shiming, Zhao, Zhichao, Lv, Qiang, Zhang, Zhiyong, 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, Sun, Fengchun, editor, Yang, Qingxin, editor, Dahlquist, Erik, editor, and Xiong, Rui, editor

Published
2023
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173. An allosteric pan-TEAD inhibitor blocks oncogenic YAP/TAZ signaling and overcomes KRAS G12C inhibitor resistance

Author

Hagenbeek, Thijs J., Zbieg, Jason R., Hafner, Marc, Mroue, Rana, Lacap, Jennifer A., Sodir, Nicole M., Noland, Cameron L., Afghani, Shervin, Kishore, Ayush, Bhat, Kamakoti P., Yao, Xiaosai, Schmidt, Stephen, Clausen, Saundra, Steffek, Micah, Lee, Wendy, Beroza, Paul, Martin, Scott, Lin, Eva, Fong, Rina, Di Lello, Paola, Kubala, Marta H., Yang, Michelle N.-Y., Lau, Jeffrey T., Chan, Emily, Arrazate, Alfonso, An, Le, Levy, Elizabeth, Lorenzo, Maria N., Lee, Ho-June, Pham, Trang H., Modrusan, Zora, Zang, Richard, Chen, Yi-Chen, Kabza, Michal, Ahmed, Musaddeque, Li, Jason, Chang, Matthew T., Maddalo, Danilo, Evangelista, Marie, Ye, Xin, Crawford, James J., and Dey, Anwesha

Published
2023
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196. Hierarchical and Partially Observable Goal-driven Policy Learning with Goals Relational Graph

Author

Ye, Xin and Yang, Yezhou

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Robotics
Abstract

We present a novel two-layer hierarchical reinforcement learning approach equipped with a Goals Relational Graph (GRG) for tackling the partially observable goal-driven task, such as goal-driven visual navigation. Our GRG captures the underlying relations of all goals in the goal space through a Dirichlet-categorical process that facilitates: 1) the high-level network raising a sub-goal towards achieving a designated final goal; 2) the low-level network towards an optimal policy; and 3) the overall system generalizing unseen environments and goals. We evaluate our approach with two settings of partially observable goal-driven tasks -- a grid-world domain and a robotic object search task. Our experimental results show that our approach exhibits superior generalization performance on both unseen environments and new goals., Comment: CVPR2021

Published
2021

198. The diffuse-type tenosynovial giant cell tumor (dt-TGCT) patient journey: a prospective multicenter study

Author

Bernthal, Nicholas M, Spierenburg, Geert, Healey, John H, Palmerini, Emanuela, Bauer, Sebastian, Gelderblom, Hans, Staals, Eric L, Lopez-Bastida, Julio, Fronk, Eva-Maria, Ye, Xin, Laeis, Petra, and van de Sande, Michiel AJ

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Clinical Trials and Supportive Activities, Rare Diseases, Pediatric, Clinical Research, Cancer, Good Health and Well Being, Adolescent, Adult, Europe, Giant Cell Tumor of Tendon Sheath, Humans, Neoplasm Recurrence, Local, Prospective Studies, Quality of Life, Retrospective Studies, Arthroscopy, Diagnosis, Patient journey, Surgery, Synovectomy, Systemic therapies, Diffuse TGCT, TOPP registry, TOPP Study Group, Other Medical and Health Sciences, Genetics & Heredity, Genetics, Clinical sciences
Abstract

BackgroundTenosynovial giant cell tumor (TGCT) is a rare, locally aggressive neoplasm arising from the synovium of joints, bursae, and tendon sheaths affecting small and large joints. It represents a wide spectrum ranging from minimally symptomatic to massively debilitating. Most findings to date are mainly from small, retrospective case series, and thus the morbidity and actual impact of this rare disease remain to be elucidated. This study prospectively explores the management of TGCT in tertiary sarcoma centers.MethodsThe TGCT Observational Platform Project registry was a multinational, multicenter, prospective observational study involving 12 tertiary sarcoma centers in 7 European countries, and 2 US sites. This study enrolled for 2 years all consecutive ≥ 18 years old patients, with histologically diagnosed primary or recurrent cases of diffuse-type TGCT. Patient demographic and clinical characteristics were collected at baseline and every 6 months for 24 months. Quality of life questionnaires (PROMIS-PF and EQ-5D) were also administered at the same time-points. Here we report baseline patient characteristics.Results166 patients were enrolled between November 2016 and March 2019. Baseline characteristics were: mean age 44 years (mean age at disease onset: 39 years), 139/166 (83.7%) had prior treatment, 71/166 patients (42.8%) had ≥ 1 recurrence after treatment of their primary tumor, 76/136 (55.9%) visited a medical specialist ≥ 5 times, 66/116 (56.9%) missed work in the 24 months prior to baseline, and 17/166 (11.6%) changed employment status or retired prematurely due to disease burden. Prior treatment consisted of surgery (i.e., arthroscopic, open synovectomy) (128/166; 77.1%) and systemic treatments (52/166; 31.3%) with imatinib (19/52; 36.5%) or pexidartinib (27/52; 51.9%). Treatment strategies at baseline visits consisted mainly of watchful waiting (81/166; 48.8%), surgery (41/166; 24.7%), or targeted systemic therapy (37/166; 22.3%). Patients indicated for treatment reported more impairment compared to patients indicated for watchful waiting: worst stiffness NRS 5.16/3.44, worst pain NRS 6.13/5.03, PROMIS-PF 39.48/43.85, and EQ-5D VAS 66.54/71.85.ConclusionThis study confirms that diffuse-type TGCT can highly impact quality of life. A prospective observational registry in rare disease is feasible and can be a tool to collect curated-population reflective data in orphan diseases. Name of registry: Tenosynovial Giant Cell Tumors (TGCT) Observational Platform Project (TOPP).Trial registration numberNCT02948088. Date of registration: 10 October 2016. URL of Trial registry record: https://clinicaltrials.gov/ct2/show/NCT02948088?term=NCT02948088&draw=2 .

Published
2021

200. Anisotropic Polarizability of Ultracold Ground-state $^{23}$Na$^{87}$Rb Molecules

Author

Lin, Junyu, He, Junyu, Ye, Xin, and Wang, Dajun

Subjects
Physics - Atomic Physics, Condensed Matter - Quantum Gases
Abstract

We report measurements of the ac polarizabilities of ultracold ground-state $^{23}\rm{Na}^{87}\rm{Rb}$ molecules. While the polarizability of the ground rotational state $J = 0$ is isotropic, that of the first excited rotational state $J = 1$ is anisotropic and depends strongly on the light polarization angle. We obtain both polarizabilities precisely by combining trap oscillation frequency measurement and high resolution rotational spectroscopy driven by microwave. With the optimized light polarization angle and intensity combination, the nonuniformity of the differential ac Stark shift between the two rotational states is minimized and the rotational coherence time is observed to be the longest., Comment: 6 pages, 5 figures

Published
2020
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