Results 181 to 190 of about 2,376,097 (347)

Deformation Prediction of 4D‐Printed Active Composite Structures Based on Data Mining

open access: yesAdvanced Science, EarlyView.
A curvature‐driven sequence point generation (CSPG) algorithm based on data mining is proposed to predict the deformation of double‐layer voxelized composite structures of arbitrary lengths. In addition, the CSPG algorithm is applied to predict the deformation of 2D and 3D structures assembled from beam elements, and its effectiveness is validated ...
Mengtao Wang   +6 more
wiley   +1 more source

Atypical Presentation of Infective Endocarditis: Reactive Arthritis as the First Clinical Clue. [PDF]

open access: yesCureus
Ahmed AH   +9 more
europepmc   +1 more source

GPCRs in CAR‐T Cell Immunotherapy: Expanding the Target Landscape and Enhancing Therapeutic Efficacy

open access: yesAdvanced Science, EarlyView.
Chimeric antigen receptor T cell therapy faces dual challenges of target scarcity and an immunosuppressive microenvironment in solid tumors. This review highlights how G protein‐coupled receptors can serve as both novel targets to expand the therapeutic scope and functional modules to enhance CAR‐T cell efficacy.
Zhuoqun Liu   +11 more
wiley   +1 more source

Inferring Gene Regulatory Networks From Single‐Cell RNA Sequencing Data by Dual‐Role Graph Contrastive Learning

open access: yesAdvanced Science, EarlyView.
RegGAIN is a novel and powerful deep learning framework for inferring gene regulatory networks (GRNs) from single‐cell RNA sequencing data. By integrating self‐supervised contrastive learning with dual‐role gene representations, it consistently outperforms existing methods in both accuracy and robustness.
Qiyuan Guan   +9 more
wiley   +1 more source

Generating Dynamic Structures Through Physics‐Based Sampling of Predicted Inter‐Residue Geometries

open access: yesAdvanced Science, EarlyView.
While static structure prediction has been revolutionized, modeling protein dynamics remains elusive. trRosettaX2‐Dynamics is presented to address this challenge. This framework leverages a Transformer‐based network to predict inter‐residue geometric constraints, guiding conformation generation via physics‐based iterative sampling. The resulting method
Chenxiao Xiang   +3 more
wiley   +1 more source

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