Results 201 to 210 of about 796,535 (249)

Tissue‐Agnostic Cellular Morphometric Biomarkers for Risk‐Adapted Management Across Gastrointestinal Precancerous Lesions and Cancers

Advanced Science, EarlyView.
An interpretable, unsupervised artificial intelligence framework identifies a 13‐cellular morphometric biomarker (CMB) signature from routine H&E whole‐slide images. Validated across 2,602 patients, the fixed signature generalizes across colorectal, gastric, and esophageal tissues without retraining, stratifies prognosis and precancerous lesion risk ...
Pin Wang, Chengfei Jiang, April W. Mao, Qi Sun, Yijun Lu, Jingjing Wei, Jamie L. Inman, Susan E. Celniker, Antoine M. Snijders, David W. Threadgill, Allan Balmain, Bo Hang, Hang Chang, Lei Wang, Jian‐Hua Mao   +14 more
wiley   +1 more source

Intrasplenic Thymus Organogenesis from Injectable Tissue Fragments Restores Functional T‐Cell Immunity

Advanced Science, EarlyView.
Clinical intramuscular thymus transplantation yields only short‐lived efficacy and marginal therapeutic benefits. Benefiting from the spleen's intrinsic strengths—rapid vascular perfusion, abundant developmental factors, and resident progenitors—the intrasplenic thymic grafts achieve robust thymic regeneration and substantial T‐cell reconstitution ...
Shaocong Wang, Zijian Zhang, Fulin Dai, Zhijie Yin, Zhen Xing, Yurong Li, Haochong Lei, Junfeng Zhang, Chunyan Liu, Yan Li, Lei Dong   +10 more
wiley   +1 more source

Formation, Transformation, and Synergistic Interplay of Crystalline Orientation in Conjugated Polymers via Solution‐State Aggregation Control

Advanced Science, EarlyView.
Molecular engineering (i.e., tuning donors) and three film processing strategies (i.e., drop‐casting from different solvents, thermal and solvent vapor annealing, and blending) were synergistically utilized to tailor the solution‐state aggregation and thus the formation, transformation, and interplay of solid‐state crystalline orientation (face‐on and ...
Hao Zheng, Lixin Li, Yanan Guo, Bingjie Wu, Xuebing Luo, Hao Zhan, Yongjie Dong, Ze‐Fan Yao, Juan Peng, Jian Pei   +9 more
wiley   +1 more source

Deep‐Learning‐Based Denoising for Improved Phase Precision in Electron Holography of Electromagnetic Fields in Nanoscale Materials

Advanced Science, EarlyView.
Low‐dose electron holography is limited by shot noise, which buries weak phase signals. HoloDenoiser, a physics‐informed network that works simultaneously in the spatial and frequency domains, locates and protects the holographic sideband while suppressing noise in the hologram.
Ye Luo, Luyang Wang, Zhiling Yu, Xiaowen Chen, Xiaoyu Wang, Ya‐Hui Jia, Thibaud Denneulin, Yu Han, Rafal E. Dunin‐Borkowski, Fengshan Zheng, Qi Liu   +10 more
wiley   +1 more source

An RNA‐Binding Protein RBMS1 Promotes Endothelial Cell Autophagy to Maintain Vascular Homeostasis and Suppress Deep Vein Thrombosis

Advanced Science, EarlyView.
RBMS1, an RNA‐binding protein, restores vascular endothelial homeostasis by enhancing ATG3‐mediated autophagy, thereby attenuating thrombus formation and suggesting a potential avenue for further therapeutic exploration in DVT. ABSTRACT Deep vein thrombosis (DVT) is a prevalent vascular disorder characterized by aberrant coagulation within the deep ...
Chu Chu, Xinkui Liu, Nannan Fan, Xiaoyan Yu, Qiaoqiao Han, Yunhong Zhang, Wei Li, Yongqing Cai, Miaomiao Zhou, Fang Li, Feifei Shi, Zhen Zhang, Bin Wang, Xia Li   +13 more
wiley   +1 more source

Predicting Single‐Cell Perturbation Responses Across Biological Contexts With a Deep Generative Model Integrating Optimal Transport

Advanced Science, EarlyView.
Single‐cell perturbation responses are predicted across held‐out biological contexts using scPILOT, a query‐conditioned two‐stage latent response‐transfer framework. A shared latent representation supports cell‐level response estimation by latent optimal transport, followed by Leiden‐localized query‐specific transfer and adaptive weighting.
Jialiang Wang, Ziqi Liu, Zhengqian Zhang, Yikun Cao, Junjun Ren, Peng Cheng, Jingjing Tian, Lingyun Xie, Xin Lu, Zhanwei Du, Yongzhuang Liu   +10 more
wiley   +1 more source

Robots and Minimal, Physics‐Informed Features: A Hybrid Framework for Enzyme Catalysis

Advanced Science, EarlyView.
Robotic experimentation and physics‐informed machine learning combine to predict enzyme substrate scope. With a handful of interpretable features derived from docking and quantum mechanics calculations, our model rivals descriptor‐heavy AI approaches and extrapolates to unseen substrates and enzyme classes.
Natalia Onishchenko, Eric S. Larsen, Govind Paneru, Kisung Lee, Diana V. Kolygina, Yankai Jia, Elizabeth Maria Clarissa, Wai‐Shing Wong, Bartosz A. Grzybowski   +8 more
wiley   +1 more source

Similarity‐Enhanced Representation Learning of Non‐Canonical Amino Acids for Therapeutic Peptide Modeling

Advanced Science, EarlyView.
Non‐canonical amino acids (ncAAs) enhance peptide therapeutics but remain difficult to model computationally. SinCAA, a similarity‐enhanced pretraining framework, jointly optimizes contrastive learning guided by a novel conformational similarity metric with masked node reconstruction, capturing both functional relationships and chemical identity of ...
Chencheng Xu, Lesong Wei, Jianmin Wang, Yuanpeng Xiong, Ruochi Zhang, Yu Wang, Chao Zha, Qiangcheng Zeng, Xin Gao   +8 more
wiley   +1 more source

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Discrete Sparse Coding

Neural Computation, 2017
Sparse coding algorithms with continuous latent variables have been the subject of a large number of studies. However, discrete latent spaces for sparse coding have been largely ignored. In this work, we study sparse coding with latents described by discrete instead of continuous prior distributions.
Georgios Exarchakis, Jörg Lücke
openaire   +3 more sources

Laplacian Sparse Coding, Hypergraph Laplacian Sparse Coding, and Applications

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013
Sparse coding exhibits good performance in many computer vision applications. However, due to the overcomplete codebook and the independent coding process, the locality and the similarity among the instances to be encoded are lost. To preserve such locality and similarity information, we propose a Laplacian sparse coding (LSc) framework.
Shenghua Gao, Ivor Wai-Hung Tsang, Liang-Tien Chia   +2 more
openaire   +2 more sources