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3,040 results on '"Gu, Jin"'

1. Feature Fusion Based on Mutual-Cross-Attention Mechanism for EEG Emotion Recognition

Author

Zhao, Yimin and Gu, Jin

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

An objective and accurate emotion diagnostic reference is vital to psychologists, especially when dealing with patients who are difficult to communicate with for pathological reasons. Nevertheless, current systems based on Electroencephalography (EEG) data utilized for sentiment discrimination have some problems, including excessive model complexity, mediocre accuracy, and limited interpretability. Consequently, we propose a novel and effective feature fusion mechanism named Mutual-Cross-Attention (MCA). Combining with a specially customized 3D Convolutional Neural Network (3D-CNN), this purely mathematical mechanism adeptly discovers the complementary relationship between time-domain and frequency-domain features in EEG data. Furthermore, the new designed Channel-PSD-DE 3D feature also contributes to the high performance. The proposed method eventually achieves 99.49% (valence) and 99.30% (arousal) accuracy on DEAP dataset., Comment: The work has been accepted by MICCAI 2024. The uploaded one is preprint which has not undergone peer review (when applicable) or any post-submission improvements or corrections. The official DOI link will be provided once available

Published
2024

2. Understanding Auditory Evoked Brain Signal via Physics-informed Embedding Network with Multi-Task Transformer

Author

Ma, Wanli, Tang, Xuegang, Gu, Jin, Wang, Ying, and Xia, Yuling

Subjects
Quantitative Biology - Neurons and Cognition, Computer Science - Machine Learning, Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

In the fields of brain-computer interaction and cognitive neuroscience, effective decoding of auditory signals from task-based functional magnetic resonance imaging (fMRI) is key to understanding how the brain processes complex auditory information. Although existing methods have enhanced decoding capabilities, limitations remain in information utilization and model representation. To overcome these challenges, we propose an innovative multi-task learning model, Physics-informed Embedding Network with Multi-Task Transformer (PEMT-Net), which enhances decoding performance through physics-informed embedding and deep learning techniques. PEMT-Net consists of two principal components: feature augmentation and classification. For feature augmentation, we propose a novel approach by creating neural embedding graphs via node embedding, utilizing random walks to simulate the physical diffusion of neural information. This method captures both local and non-local information overflow and proposes a position encoding based on relative physical coordinates. In the classification segment, we propose adaptive embedding fusion to maximally capture linear and non-linear characteristics. Furthermore, we propose an innovative parameter-sharing mechanism to optimize the retention and learning of extracted features. Experiments on a specific dataset demonstrate PEMT-Net's significant performance in multi-task auditory signal decoding, surpassing existing methods and offering new insights into the brain's mechanisms for processing complex auditory information.

Published
2024

3. Transient pacing in pigs with complete heart block via myocardial injection of mRNA coding for the T-box transcription factor 18

Author

Wolfson, David W., Kim, Nam Kyun, Lee, Ki Hong, Beyersdorf, Jared P., Langberg, Jonathan J., Fernandez, Natasha, Choi, Dahim, Zureick, Nadine, Kim, Tae Yun, Bae, Seongho, Gu, Jin-Mo, Kirschman, Jonathan L., Fan, Jinqi, Sheng, Christina Y., Gottlieb Sen, Danielle, Mettler, Bret, Sung, Jung Hoon, Yoon, Young-sup, Park, Sung-Jin, Santangelo, Philip J., and Cho, Hee Cheol

Published
2024
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4. Baryon electric charge correlation as a magnetometer of QCD

Author

Ding, Heng-Tong, Gu, Jin-Biao, Kumar, Arpith, Li, Sheng-Tai, and Liu, Jun-Hong

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

The correlation between net baryon number and electric charge, $\chi_{11}^{\rm BQ}$, can serve as a magnetometer of QCD. This is demonstrated by lattice QCD computations using the highly improved staggered quarks with physical pion mass of $M_\pi=135~$MeV on $N_\tau=8$ and 12 lattices. We find that $\chi_{11}^{\rm BQ}$ along the transition line starts to increase rapidly with magnetic field strength $eB\gtrsim 2M_\pi^2$ and by a factor 2 at $eB\simeq 8M_\pi^2$. Furthermore, the ratio of electric charge chemical potential to baryon chemical potential, $\mu_{\rm Q}/\mu_{\rm B}$, shows significant dependence on the magnetic field strength and varies from the ratio of electric charge to baryon number in the colliding nuclei in heavy ion collisions. These results can provide baselines for effective theory and model studies, and both $\chi_{11}^{\rm BQ}$ and $\mu_{\rm Q}/\mu_{\rm B}$ could be useful probes for the detection of magnetic fields in relativistic heavy ion collision experiments as compared with corresponding results from the hadron resonance gas model., Comment: 6 pages main text + 6 pages supplemental material, discussions added on the continuum estimate and extrapolation along with additional lattice QCD simulations on Nt=16 lattices, and the proxy of baryon electric charge correlation as well as the thermal fits to obtain the baryon and electric charge chemical potential

Published
2023
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6. Efficacy and safety of an innovative short-course regimen containing clofazimine for treatment of drug-susceptible tuberculosis: a clinical trial

Author

Zheng, Xubin, Gui, Xuwei, Yao, Lan, Ma, Jun, He, Yifan, Lou, Hai, Gu, Jin, Ying, Ruoyan, Chen, Liping, Sun, Qin, Liu, Yidian, Ho, Chih-Ming, Lee, Bai-Yu, Clemens, Daniel L, Horwitz, Marcus A, Ding, Xianting, Hao, Xiaohui, Yang, Hua, and Sha, Wei

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Lung, Clinical Trials and Supportive Activities, Rare Diseases, Orphan Drug, Infectious Diseases, Digestive Diseases, Tuberculosis, Clinical Research, 6.1 Pharmaceuticals, Evaluation of treatments and therapeutic interventions, Infection, Good Health and Well Being, Humans, Clofazimine, Prothionamide, Drug Therapy, Combination, Antitubercular Agents, Pyrazinamide, Treatment Outcome, Isoniazid, Short-course treatment, clofazimine, parabolic response surface, pulmonary tuberculosis, randomized clinical trial, Microbiology, Clinical sciences, Epidemiology
Abstract

In preclinical studies, a new antituberculosis drug regimen markedly reduced the time required to achieve relapse-free cure. This study aimed to preliminarily evaluate the efficacy and safety of this four-month regimen, consisting of clofazimine, prothionamide, pyrazinamide and ethambutol, with a standard six-month regimen in patients with drug-susceptible tuberculosis. An open-label pilot randomized clinical trial was conducted among the patients with newly diagnosed bacteriologically-confirmed pulmonary tuberculosis. The primary efficacy end-point was sputum culture negative conversion. Totally, 93 patients were included in the modified intention-to-treat population. The rates of sputum culture conversion were 65.2% (30/46) and 87.2% (41/47) for short-course and standard regimen group, respectively. There was no difference on two-month culture conversion rates, time to culture conversion, nor early bactericidal activity (P > 0.05). However, patients on short-course regimen were observed with lower rates of radiological improvement or recovery and sustained treatment success, which was mainly attributed to higher percent of patients permanently changed assigned regimen (32.1% vs. 12.3%, P = 0.012). The main cause for it was drug-induced hepatitis (16/17). Although lowering the dose of prothionamide was approved, the alternative option of changing assigned regimen was chosen in this study. While in per-protocol population, sputum culture conversion rates were 87.0% (20/23) and 94.4% (34/36) for the respective groups. Overall, the short-course regimen appeared to have inferior efficacy and higher incidence of hepatitis but desired efficacy in per-protocol population. It provides the first proof-of-concept in humans of the capacity of the short-course approach to identify drug regimens that can shorten the treatment time for tuberculosis.

Published
2023

7. Expert Consensus on the Diagnosis and Treatment of FGFR Gene-Altered Solid Tumors

Author

Chunwei Xu, Bin Lian, Juanjuan Ou, Qian Wang, Wenxian Wang, Ke Wang, Dong Wang, Zhengbo Song, Aijun Liu, Jinpu Yu, Wenzhao Zhong, Zhijie Wang, Yongchang Zhang, Jingjing Liu, Shirong Zhang, Xiuyu Cai, Anwen Liu, Wen Li, Lili Mao, Ping Zhan, Hongbing Liu, Tangfeng Lv, Liyun Miao, Lingfeng Min, Yu Chen, Jingping Yuan, Feng Wang, Zhansheng Jiang, Gen Lin, Long Huang, Xingxiang Pu, Rongbo Lin, Weifeng Liu, Chuangzhou Rao, Dongqing Lv, Zongyang Yu, Xiaoyan Li, Chuanhao Tang, Chengzhi Zhou, Junping Zhang, Junli Xue, Hui Guo, Qian Chu, Rui Meng, Jingxun Wu, Rui Zhang, Jin Zhou, Zhengfei Zhu, Yongheng Li, Hong Qiu, Fan Xia, Yuanyuan Lu, Xiaofeng Chen, Rui Ge, Enyong Dai, Yu Han, Weiwei Pan, Fei Pang, Jintao Huang, Kai Wang, Fan Wu, Bingwei Xu, Liping Wang, Youcai Zhu, Li Lin, Yanru Xie, Xinqing Lin, Jing Cai, Ling Xu, Jisheng Li, Xiaodong Jiao, Kainan Li, Jia Wei, Huijing Feng, Lin Wang, Yingying Du, Wang Yao, Xuefei Shi, Xiaomin Niu, Dongmei Yuan, Yanwen Yao, Jianhui Huang, Yue Feng, Yinbin Zhang, Pingli Sun, Hong Wang, Mingxiang Ye, Zhaofeng Wang, Yue Hao, Zhen Wang, Bin Wan, Donglai Lv, Zhanqiang Zhai, Shengjie Yang, Jing Kang, Jiatao Zhang, Chao Zhang, Lin Shi, Yina Wang, Bihui Li, Zhang Zhang, Zhongwu Li, Zhefeng Liu, Nong Yang, Lin Wu, Huijuan Wang, Gu Jin, Guansong Wang, Jiandong Wang, Meiyu Fang, Yong Fang, Yuan Li, Xiaojia Wang, Jing Chen, Yiping Zhang, Xixu Zhu, Yi Shen, Shenglin Ma, Biyun Wang, Lu Si, Yuanzhi Lu, Ziming Li, Wenfeng Fang, and Yong Song

Subjects
solid tumors, tyrosine receptor kinase, precision medicine, targeted therapy, Genetics, QH426-470, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

The fibroblast growth factor receptor (FGFR) is a crucial receptor tyrosine kinase involved in essential biological processes, including growth, development, and tissue repair. However, FGFR gene mutations, including amplification, fusion, and mutation, can disrupt epigenetics, transcriptional regulation, and tumor microenvironment interactions, leading to cancer development. Targeting these kinase mutations with small molecule drugs or antibodies has shown clinical benefits. For example, erdafitinib is approved for treating locally advanced or metastatic urothelial cancer patients with FGFR2/FGFR3 mutations, and pemigatinib is approved for treating cholangiocarcinoma with FGFR2 fusion/rearrangement. Effective screening of FGFR variant patients is crucial for the clinical application of FGFR inhibitors. Various detection methods, such as polymerase chain reaction, next-generation sequencing, fluorescence in situ hybridization, and immunohistochemistry, are available, and their selection should be based on diagnostic and treatment decision-making needs. Our developed expert consensus aims to standardize the diagnosis and treatment process for FGFR gene mutations and facilitate the practical application of FGFR inhibitors in clinical practice.

Published
2024
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16. Deep whole-genome analysis of 494 hepatocellular carcinomas

Author

Chen, Lei, Zhang, Chong, Xue, Ruidong, Liu, Mo, Bai, Jian, Bao, Jinxia, Wang, Yin, Jiang, Nanhai, Li, Zhixuan, Wang, Wenwen, Wang, Ruiru, Zheng, Bo, Yang, Airong, Hu, Ji, Liu, Ke, Shen, Siyun, Zhang, Yangqianwen, Bai, Mixue, Wang, Yan, Zhu, Yanjing, Yang, Shuai, Gao, Qiang, Gu, Jin, Gao, Dong, Wang, Xin Wei, Nakagawa, Hidewaki, Zhang, Ning, Wu, Lin, Rozen, Steven G., Bai, Fan, and Wang, Hongyang

Published
2024
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22. Expert Consensus on the Diagnosis and Treatment of NRG1/2 Gene Fusion Solid Tumors

Author

Chunwei Xu, Qian Wang, Dong Wang, Wenxian Wang, Wenfeng Fang, Ziming Li, Aijun Liu, Jinpu Yu, Wenzhao Zhong, Zhijie Wang, Yongchang Zhang, Jingjing Liu, Shirong Zhang, Xiuyu Cai, Anwen Liu, Wen Li, Ping Zhan, Hongbing Liu, Tangfeng Lv, Liyun Miao, Lingfeng Min, Yu Chen, Jingping Yuan, Feng Wang, Zhansheng Jiang, Gen Lin, Long Huang, Xingxiang Pu, Rongbo Lin, Weifeng Liu, Chuangzhou Rao, Dongqing Lv, Zongyang Yu, Xiaoyan Li, Chuanhao Tang, Chengzhi Zhou, Junping Zhang, Junli Xue, Hui Guo, Qian Chu, Rui Meng, Jingxun Wu, Rui Zhang, Jin Zhou, Zhengfei Zhu, Yongheng Li, Hong Qiu, Fan Xia, Yuanyuan Lu, Xiaofeng Chen, Rui Ge, Enyong Dai, Yu Han, Weiwei Pan, Fei Pang, Qingqing He, Jintao Huang, Kai Wang, Fan Wu, Bingwei Xu, Liping Wang, Youcai Zhu, Li Lin, Yanru Xie, Xinqing Lin, Jing Cai, Ling Xu, Jisheng Li, Xiaodong Jiao, Kainan Li, Jia Wei, Huijing Feng, Lin Wang, Yingying Du, Wang Yao, Xuefei Shi, Xiaomin Niu, Dongmei Yuan, Yanwen Yao, Jianhui Huang, Yue Feng, Yinbin Zhang, Pingli Sun, Hong Wang, Mingxiang Ye, Zhaofeng Wang, Yue Hao, Zhen Wang, Bin Wan, Donglai Lv, Shengjie Yang, Jin Kang, Jiatao Zhang, Chao Zhang, Juanjuan Ou, Lin Shi, Yina Wang, Bihui Li, Zhang Zhang, Zhongwu Li, Zhefeng Liu, Nong Yang, Lin Wu, Huijuan Wang, Gu Jin, Guansong Wang, Jiandong Wang, Meiyu Fang, Yong Fang, Yuan Li, Xiaojia Wang, Yiping Zhang, Xixu Zhu, Yi Shen, Shenglin Ma, Biyun Wang, Lu Si, Yong Song, Yuanzhi Lu, Jing Chen, and Zhengbo Song

Subjects
tyrosine receptor kinase, monoclonal antibodies, precision medicine, targeted therapy, solid tumor, fusion, Genetics, QH426-470, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

The fusion genes NRG1 and NRG2, members of the epidermal growth factor (EGF) receptor family, have emerged as key drivers in cancer. Upon fusion, NRG1 retains its EGF-like active domain, binds to the ERBB ligand family, and triggers intracellular signaling cascades, promoting uncontrolled cell proliferation. The incidence of NRG1 gene fusion varies across cancer types, with lung cancer being the most prevalent at 0.19 to 0.27%. CD74 and SLC3A2 are the most frequently observed fusion partners. RNA-based next-generation sequencing is the primary method for detecting NRG1 and NRG2 gene fusions, whereas pERBB3 immunohistochemistry can serve as a rapid prescreening tool for identifying NRG1-positive patients. Currently, there are no approved targeted drugs for NRG1 and NRG2. Common treatment approaches involve pan-ERBB inhibitors, small molecule inhibitors targeting ERBB2 or ERBB3, and monoclonal antibodies. Given the current landscape of NRG1 and NRG2 in solid tumors, a consensus among diagnostic and treatment experts is proposed, and clinical trials hold promise for benefiting more patients with NRG1 and NRG2 gene fusion solid tumors.

Published
2024
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29. CACA guidelines for holistic integrative management of rectal cancer

Author

Wang, Guiyu, Fan, Daiming, Gu, Jin, Ding, Kefeng, Fang, Xuedong, Shen, Lin, Xu, Zhongfa, Xu, Jianmin, Cai, Jianchun, Cai, Lianming, Cai, Sanjun, Chen, Gong, Chen, Jiansi, Cheng, Longwei, Cheng, Yong, Chi, Pan, Cui, Binbin, Dai, Guanghai, Fu, Chuangang, Gu, Yanhong, He, Guodong, Hu, Junhong, Huang, Jing, Huang, Rui, Huang, Zhongcheng, Jiang, Zheng, Jie, Zhigang, Ju, Haixing, Li, Hai, Li, Jian, Li, Jun, Li, Ming, Li, Yaoping, Li, Yunfeng, Lin, Guole, Liu, Haiying, Liu, Ming, Liu, Qian, Pan, Zhizhong, Peng, Yifan, Qian, Niansong, Qiu, Meng, Ren, Li, Sun, Yueming, Tang, Jianqiang, Tang, Qingchao, Tang, Yuan, Tao, Kaixiong, Tao, Min, Wang, Haijiang, Wang, Meng, Wang, Zejun, Wang, Zhengguang, Wang, Ziqiang, Wang, Ziwei, Wei, Shaozhong, Xing, Baocai, Xiong, Bin, Xu, Ye, Yan, Su, Yang, Bin, Yang, Chunkang, Yao, Qinghua, Ye, Yingjiang, Yuan, Ying, Zhang, Guozhi, Zhang, Haizeng, Zhang, Hongmei, Zhang, Zhen, Zhong, Yunshi, Zhu, Ji, Zhu, Yuan, Zhu, Yuping, Zou, Shuangmei, Wang, Yuliuming, Lv, Jingfang, Liu, Enrui, Yang, Ming, Zhang, Qian, Zhang, Weiyuan, Zhang, Lin, Luo, Jun, Zheng, Zhaoxu, Zhao, Zhixun, Liu, Zheng, Tao, Jinhua, Huang, Haiyang, Chen, Tianli, and Wang, Xishan

Published
2023
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32. Development and validation of postoperative circulating tumor DNA combined with clinicopathological risk factors for recurrence prediction in patients with stage I-III colorectal cancer

Author

Gao, Zhaoya, Huang, Dandan, Chen, Hui, Yang, Yong, An, Ke, Ding, Changmin, Yuan, Zheping, Zhai, Zhichao, Niu, Pengfei, Gao, Qingkun, Cai, Jinping, Zeng, Qingmin, Wang, Yanzhao, Hong, Yuming, Rong, Wanshui, Huang, Wensheng, Lei, Fuming, Wang, Xiaodong, Chen, Shiqing, Zhao, Xiaochen, Bai, Yuezong, and Gu, Jin

Published
2023
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