Results 61 to 70 of about 3,363 (257)

Hyperspectral and Multispectral Image Fusion Using Coupled Non-Negative Tucker Tensor Decomposition

Remote Sensing, 2021
Fusing a low spatial resolution hyperspectral image (HSI) with a high spatial resolution multispectral image (MSI), aiming to produce a super-resolution hyperspectral image, has recently attracted increasing research interest.
Marzieh Zare, Mohammad Sadegh Helfroush, Kamran Kazemi, Paul Scheunders   +3 more
doaj   +1 more source

Icariin Enhances the Enzymatic Activity of N‐acetylgalactosaminidase to Augment Akkermansia Abundance in Gut Microbiota for Improved PD‐1 Blockade Efficacy in Tumor Suppression

Advanced Science, EarlyView.
Icariin promoted the growth of Akk by enhancing the activity of N‐acetylgalactosaminidase (Amuc_0920), which enhanced mucin utilization and provided a favorable nutrient environment for bacterial growth. This icariin‐mediated enrichment of Akk further reshaped the tumor microenvironment and promoted CD8+ T cell infiltration, ultimately synergizing with
Shuangying Qiao, Liu Yang, Haibang Hao, Qiuxia Ding, Feng Ding, Zheng Chen, Jinfang Zhang, Yun He, Meng Li, Jun Xu, Chao Wang, Aiping Lu, Fangfei Li   +12 more
wiley   +1 more source

Combining the spatiotemporal mobility patterns and MMC for next location prediction of fake base stations

Computational Urban Science
The spatiotemporal mobility patterns and next location prediction of fake base stations (FBS) provide important technical support for the police to prevent spam messages from FBS.
Yufei·Shi, Haiyan Tao, Li Zhuo
doaj   +1 more source

Multispectral image denoising using sparse and graph Laplacian Tucker decomposition

Computational Visual Media, 2020
Multispectral image denoising is a basic problem whose results affect subsequent processes such as target detection and classification. Numerous approaches have been proposed, but there are still many challenges, particularly in using prior knowledge of ...
Xiaoce Wu, Bingyin Zhou, Qingyun Ren, Wei Guo   +3 more
doaj   +1 more source

CD28‐Targeted Enzyme‐Responsive Conformation‐Switching Peptide Self‐Assembly for Selective T‐Cell Acute Lymphoblastic Leukemia (T‐ALL) Therapy

Advanced Science, EarlyView.
We developed the enzyme‐responsive peptide SAp‐CD28 to selectively target CD28‐overexpressing T‐ALL cells. Following phosphatase‐mediated activation, SAp‐CD28 undergoes conformational switching and nanooligomerization, resulting in the disruption of CD28 downstream signaling.
Jun Li, Ziyu Jia, Dekun Li, Zhi‐Wen Hu, Yinghao Ding, Shengyi Zhang, Shengkun Tuo, Zhimou Yang, Huisheng Fu, Ling Wang, Man‐Di Wang   +10 more
wiley   +1 more source

Tucker Decomposition Network: Expressive Power and Comparison

CoRR, 2019
Deep neural networks have achieved a great success in solving many machine learning and computer vision problems. The main contribution of this paper is to develop a deep network based on Tucker tensor decomposition, and analyze its expressive power. It is shown that the expressiveness of Tucker network is more powerful than that of shallow network. In
Ye Liu 0014, JunJun Pan, Michael K. Ng 0001   +2 more
openaire   +2 more sources

Pharmacologic Modulation of ARID3A with Rimegepant Reactivates Type I Interferon Signaling and Sensitizes Triple‐Negative Breast Cancer to PD‐1 Blockade

Advanced Science, EarlyView.
This study identifies ARID3A as a key immunosuppressive transcription factor in TNBC. Its inhibition activates the type I IFN pathway, boosting CD8+ T cell infiltration and sensitizing tumors to anti‐PD‐1. The FDA‐approved migraine drug Rimegepant targets ARID3A, enhances immunotherapy efficacy in preclinical models, and establishes a druggable axis to
Teng Zhou, Yifei Zhu, Cheng Zeng, Jinlu Han, Huiying Huang, Doudou Li, Mingxi Lin, Yizi Jin, Qin Guo, Yuxin Yan, Xinhui Mao, Yifei Zhou, Jian Zhang   +12 more
wiley   +1 more source

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

Nanomedicine Meets Immunotherapy: Advancing Adoptive Cell Therapy with Nanoparticles in the Treatment of Cancer with Sustainability Perspectives

Advanced Science, EarlyView.
This review surveys nanoparticle‐based strategies to enhance adoptive cell therapy, particularly CAR‐T cell approaches, in solid tumor treatment. It describes how nanoparticles can improve tumor immunogenicity and T‐cell infiltration while reducing toxicity, and how they enable in vivo CAR‐T cell generation.
Erica Frostegård, Tatiana Bobrova, Amalie Leinebø, Thibault Leray, Shayamita Ghosh, Lorena García‐Hevia, Chiara Puccinelli, Lorenzo Riccio, Jacopo Sorani, Davide Bonifazi, Julien Caumartin, Emmanuel Donnadieu, Florence Gazeau, Roland Hischier, Else Marit Inderberg, Mónica L. Fanarraga, Maria Loustau, Bernd Nowack, Sébastien Wälchli, Cécilia Ménard‐Moyon   +19 more
wiley   +1 more source

Accelerating the Tucker Decomposition with Compressed Sparse Tensors [PDF]

, 2017
The Tucker decomposition is a higher-order analogue of the singular value decomposition and is a popular method of performing analysis on multi-way data (tensors). Computing the Tucker decomposition of a sparse tensor is demanding in terms of both memory and computational resources.
Smith, Shaden, Karypis, George
openaire   +1 more source