Results 161 to 170 of about 404,230 (315)

Multimodal Cross‐Attentive Graph‐Based Framework for Predicting In Vivo Endocrine Disruptors

Advanced Science, EarlyView.
A multimodal cross‐attentive graph neural network integrates molecular graphs with androgen and estrogen adverse outcome pathway (AOP)–anchored in vitro assay signals to predict in vivo endocrine disruption. By fusing information on Tier‐1 AOP logits with chemical structures, the framework achieves high accuracy and provides assay‐traceable ...
Eder Soares de Almeida Santos, Gustavo Felizardo Santos Sandes, Artur Christian Garcia da Silva, Holli‐Joi Martin, Eugene N. Muratov, Rodolpho de Campos Braga, Bruno Junior Neves   +6 more
wiley   +1 more source

A NeuroD1 AAV‐Based Gene Therapy for Functional Brain Repair in Alzheimer's Disease‐Like Non‐Human Primate Model

Advanced Science, EarlyView.
This study tests NeuroD1 AAV‐based gene therapy in a non‐human primate Alzheimer's disease model. The therapy prevents neuronal damage, inhibits hippocampal atrophy, and reduces neuroinflammation. It also repairs vascular and blood‐brain barrier damage, restores cerebrospinal fluid biomarkers, enhances hippocampal glucose metabolism, and improves ...
Zhouquan Jiang, Yongpeng Qin, Bin Luo, Fan Bai, Jiangyue Liu, Long Ma, Shu He, Rongjie Chen, Yuchen Wang, Shanggong Liu, Ying Sun, Yi Chen, Shuo Zhang, Jiaqi Liang, Feng Liao, Huiyi Wei, Junjie Wei, Lu Wang, Hao Xu, Zheng Wu, Gong Chen, Wenliang Lei   +21 more
wiley   +1 more source

The Path Planning of Mobile Robot by Neural Networks and Hierarchical Reinforcement Learning. [PDF]

Front Neurorobot, 2020
Yu J, Su Y, Liao Y.
europepmc   +1 more source

Transcription Factor Promiscuity Drives Regulatory Rewiring and Evolvability in Gene Networks in Bacteria

Advanced Science, EarlyView.
When a master transcription factor (TF) is lost, bacteria can rapidly rewire gene regulatory networks by co‐opting related regulators. Using experimental evolution in Pseudomonas fluorescens, we show that TF promiscuity (low‐level, non‐cognate binding) provides the raw material for rewiring. Successful co‐option follows a predictable hierarchy governed
Tiffany B. Taylor, Alan M. Rice
wiley   +1 more source

Towards sentiment aided dialogue policy learning for multi-intent conversations using hierarchical reinforcement learning. [PDF]

PLoS One, 2020
Saha T, Saha S, Bhattacharyya P.
europepmc   +1 more source

Unsupervised Hierarchical Symbolic Regression for Interpretable Property Modeling in Complex Multi‐Variable Systems

Advanced Science, EarlyView.
UHSR translates complex chemical behavior into clear and explainable equations. Applied to thin‐layer chromatography, it automatically uncovers the mathematical rules linking a molecule's structure to its polarity. This approach matches the accuracy of advanced AI while providing interpretable results, earning greater trust from chemists. The method is
Siyu Lou, Chengchun Liu, Dongxiao Zhang, Yuntian Chen, Fanyang Mo   +4 more
wiley   +1 more source

Multi modal hierarchical reinforcement learning framework for dynamic sports sponsorship optimization. [PDF]

Sci Rep
Yu Q.
europepmc   +1 more source

Bacterial Outer Membrane Vesicles in Potentiating Cancer Vaccines: Progress and Prospects

Advanced Science, EarlyView.
Bacterial outer membrane vesicles (OMVs) have emerged as versatile platforms for cancer vaccine development owing to their intrinsic immunostimulatory properties and high engineering flexibility. This review summarizes OMV biology, immune mechanisms, and engineering strategies that enhance vaccine efficacy, discusses key translational challenges, and ...
Jiabeini Zhang, Tianyu Shao, Fengjiang Qu, Caiyun Bai, Sijie Li, Pin Gao, Wenna Li, Keman Cheng, Xiao Zhao, Zhimin Fan   +9 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

TBC-HRL: A Bio-Inspired Framework for Stable and Interpretable Hierarchical Reinforcement Learning. [PDF]

Biomimetics (Basel)
Li Z, Shan Y, Mo H.
europepmc   +1 more source