Results 191 to 200 of about 484,155 (286)
Nonvolatile Reconfigurable Synthetic Antiferromagnetic Devices Induced by Spin-Orbit Torque for Multifunctional In-Memory Computing. [PDF]
Song M, Liu J, Zhu Z.
europepmc +1 more source
A cascade‐responsive MXene@Cu‐MOF/GelMA hydrogel is engineered as a “skeleton–backpack” platform for extensive tracheal repair. The MXene framework scavenges postoperative ROS and converts NIR light into mild hyperthermia, while the Cu‐MOF component provides pH/NIR‐responsive Cu2+ dosing for infection control, angiogenesis, and chondrogenesis.
Liang Guo +8 more
wiley +1 more source
Stiffness reprogrammable magnetorheological metamaterials inspired by spine for multibit visual mechanical information processing. [PDF]
Lou C +6 more
europepmc +1 more source
Protein complexes like KIBRA‐PKMζ are crucial for maintaining memories, forming month‐long protein traces in memory‐tagged neurons, but conventional RNA‐seq analysis fails to detect their transcript changes, leaving memory molecules undetected in the shadows of abundantly‐expressed genes.
Jiyeon Han +10 more
wiley +1 more source
A dataset for human-written and AI-generated code source classification. [PDF]
Boukili G, Garouani SE, Riffi J.
europepmc +1 more source
The inhibitory immune checkpoints HLA‐G and CD47 are expressed on certain tumor types and inhibit immune cells in the tumor microenvironment. DSP216 binds specifically to cancer cells expressing both HLA‐G and CD47, and blocks their inhibitory signaling.
Lisa J. Jacob +12 more
wiley +1 more source
Haplotype‐Resolved 3D Genomic Landscapes and Their Impacts on Agronomic Traits in Grapevine
This study presents a haplotype‐resolved 3D genomic landscape of grapevine, revealing that structural variations (SVs) are closely associated with phased topologically associating domain (TAD) boundary transitions. These rearrangements coordinate with allele‐specific DNA methylation (ASM) and allele‐biased gene expression (ASE) to shape key agronomic ...
Yanling Peng +18 more
wiley +1 more source
Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy
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 +4 more
wiley +1 more source

