Results 51 to 60 of about 828 (176)

Aptamer‐Targeted PrPC Drives Colorectal Cancer Metastasis via a LYN‐STAT3 Complex and Enables Liquid Biopsy Detection

Advanced Science, EarlyView.
The aptamer WHY‐3E identifies PrPC as a CRC driver. Stabilized by USP18, endocytosed PrPC forms a LYN/STAT3 complex, upregulating MSN transcription to promote metastasis. Crucially, WHY‐3E sensitively detects PrPC‐positive circulating exosomes, establishing a robust theoretical foundation for non‐invasive clinical diagnostics.
Chunlin Wang, Hongyu Wu, Chaojing Zheng, Hao Zhang, Xiaoqiu Wu, Jiaqi Wang, Zewen Chang, Jun Xiang, Yunxiao Liu, Chenkai Zhang, Yuliuming Wang, Hao Jiang, Yuchen Zhong, Jun Luo, Ying Chen, NaNa Zhang, Weiyuan Zhang, Ziming Yuan, ChaoXia Zou, Weihong Tan, Meng Wang, Hanqing Hu, Tao Bing, Guiyu Wang   +23 more
wiley   +1 more source

Noninvasive Characterization of Tumor Heterogeneity in HNSCC: From Clinical Utility to Biological Correlates

Advanced Science, EarlyView.
This study establishes a CT‐based radiomics framework to quantify intratumoral heterogeneity (ITH) in HNSCC. Using unsupervised clustering, tumor ROIs and VOIs are analyzed to calculate 2D/3D ITH scores. The score shows strong predictive value for prognosis and immunotherapy response, and is associated with tumor metabolism and immune microenvironment,
Xinwei Chen, Rui Liu, Yuan Zhou, Yin Xiao, Chengmin Feng, Lin Chen, Yanshi Li, Mengna Wang, Zhaobo Cheng, Yuxi Luo, Long Liu, Lijing Niu, Yue Xiang, Juan Peng, Guohua Hu, Min Pan   +15 more
wiley   +1 more source

A Non‐Canonical Role of SMAD4 in Regulating 3D Genome Architecture to Inhibit Lung Squamous Cell Carcinoma Development

Advanced Science, EarlyView.
SMAD4 is identified as a guardian of 3D genome architecture in lung squamous cell carcinoma. Loss of SMAD4 unleashes EP300 at chromatin loop anchors, strengthening enhancer–promoter looping and H3K27ac at the SOX2 locus to drive aberrant SOX2 activation and tumor cell proliferation.
Qian Tang, Chen Lian, Xinyan Han, Xuhan Zhang, Zihan Wang, Boyu Wang, Taoyu Zhu, Xinrui Lin, Xiaolei Wang, Yaping Xu, Manyu Xiao, Zijin Wang, Junming Li, Silin Chen, Yunze Wang, Yufei Liu, Songsong Li, Zuolin Shen, Xi Lu, Xueqi Han, Yilu Zhou, Mingyang Xiao, Jiayi Ran, Xiaoran Cao, Xinyi Xu, Hugo Sámano‐Sánchez, Alfredo Rodríguez, Lian Wang, Shuifang Chen, Zhanyu Xu, Shirong Zhang, Nuo Yang, Yong Tang, Jian Liu   +33 more
wiley   +1 more source

Intramolecular Interactions between Folded and Disordered Regions Shape Ubiquilin Structure and Function

Advanced Science, EarlyView.
Ubiquilin (UBQLN), like many other human proteins, contains both well‐folded and disordered regions. Here, we show that intramolecular interactions between disordered regions and folded domains modulate between open and closed topologies of UBQLN proteins, altering their structure and function.
Jessica K. Niblo, Nirbhik Acharya, Maxwell B. Watkins, Carlos A. Castañeda, Shahar Sukenik   +4 more
wiley   +1 more source

ProSiteHunter: A Unified Framework for Sequence‐Based Prediction of Protein‐Nucleic Acid and Protein‐Protein Binding Sites

Advanced Science, EarlyView.
This study proposed a unified sequence‐based framework for protein binding site prediction, which adopted a tri‐track semantic multi‐source feature fusion strategy to effectively capture diverse macromolecular interaction sites and further improved the accuracy of antibody‐antigen interaction prediction.
Dongliang Hou, Qihang Zhen, Zexin Lv, Xinyue Cui, Suhui Wang, Minghua Hou, Zhan Zhou, Xiaogen Zhou, Guijun Zhang   +8 more
wiley   +1 more source

Accurately Deciphering Tissue Heterogeneity From Spatial Multi‐Modal and Multi‐Omics With STransformer

Advanced Science, EarlyView.
STransformer is a unified deep learning framework designed to seamlessly accommodate a comprehensive landscape of spatial data. By simultaneously capturing short‐range cellular interactions and tissue‐wide semantic patterns, it extracts robust representations to accurately dissect complex tissue heterogeneity.
Xingyi Li, Jialuo Xu, Gaoyuan Du, Xiangting Jia, Dongmin Zhao, Chunyan Zhou, Kexin Xiao, Jia Gu, Junnan Zhu, Xuequn Shang   +9 more
wiley   +1 more source

Machine Learning‐Assisted KCl‐CaCl2‐LiCl Electrolyte Design for Low‐Temperature, High‐Performance Calcium‐Based Liquid Metal Batteries

Advanced Science, EarlyView.
A machine learning‐assisted framework optimizes the KCl‐CaCl2‐LiCl ternary electrolyte. The optimized 13:35:52 mol% composition enables Ca‐based liquid metal batteries to operate stably at 480 °C, with >99.5% coulombic efficiency, ultralow self‐discharge, and excellent cycling stability, advancing low‐temperature large‐scale energy storage.
Xinglin Zhou, Lei Huang, Yan Zhou, Xiaohui Ning   +3 more
wiley   +1 more source

Large Language Model‐Informed Dual‐Track AI Framework for the Synergistic Design of Crack‐Free and High‐Strength Superalloys

Advanced Science, EarlyView.
This paper illustrates a knowledge‐augmented dual‐track AI framework for advanced superalloy design. First, Large Language Models translate metallurgical heuristics into explicit rules to rapidly prune a vast compositional search space. Subsequently, LLM‐distilled priors safely guide a reinforcement learning agent during autonomous process optimization,
Jian Yao, Junkang Wu, Jie Su, Fuzhu Wang, Zi Wang, Li Wang, Liming Tan, Lan Huang, Feng Liu, Yong Liu   +9 more
wiley   +1 more source

An exciting Approach to Theoretical Spectroscopy

Advanced Science, EarlyView.
ABSTRACT Theoretical spectroscopy, and more generally, electronic‐structure theory, are powerful concepts for describing the complex many‐body interactions in materials. They cover methods from ground‐state properties to lattice excitations and light‐matter interaction, including time‐resolved variants.
Martí Raya‐Moreno, Alexander Buccheri, Noah Alexy Dasch, Nasrin Farahani, Ignacio Gonzalez Oliva, Andris Gulans, Seokhyun Hong, Manoar Hossain, Hannah Kleine, Martin Kuban, Sven Lubeck, Benedikt Maurer, Pasquale Pavone, Fabian Peschel, Daria Popova‐Gorelova, Lu Qiao, Elias Richter, Santiago Rigamonti, Ronaldo Rodrigues Pela, Maximilian Schebek, Kshitij Sinha, Daniel T. Speckhard, Jan Stutz, Sebastian Tillack, Dmitry Tumakov, Jānis Užulis, Mara Voiculescu, Cecilia Vona, Mao Yang, Claudia Draxl   +29 more
wiley   +1 more source

CauFinder: Steering Cell‐State and Phenotype Transitions by Causal Disentanglement Learning

Advanced Science, EarlyView.
CauFinder combines causal disentanglement modeling and network control to prioritize causal drivers of cell‐state transitions from observational transcriptomic data. The framework separates transition‐relevant signals from spurious associations, nominates intervention targets across biological and disease contexts, and identifies DAAM1 as an actionable
Chengming Zhang, Zexi Chen, Yuanxiang Miao, Zuolin Shen, Deyu Cai, Shijie Tang, Yun Xue, Weifeng Guo, Hongbin Ji, Jian Liu, Kazuyuki Aihara, Luonan Chen   +11 more
wiley   +1 more source