Results 191 to 200 of about 204,985 (297)

Persistently Increased Expression of PKMzeta and Unbiased Gene Expression Profiles Identify Hippocampal Molecular Traces of a Long‐Term Active Place Avoidance Memory and “Shadow” Proteins

open access: yesAdvanced Science, EarlyView.
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

Rapid Proteome‐Wide Discovery of Protein–Protein Interactions With ppIRIS

open access: yesAdvanced Science, EarlyView.
ppIRIS is a lightweight deep learning framework for proteome‐wide protein–protein interaction prediction directly from sequence. By fusing evolutionary and structural embeddings with a regularized Siamese architecture, ppIRIS achieves state‐of‐the‐art accuracy across species, enables minute‐scale screening, and reveals biologically validated bacterial ...
Luiz Felipe Piochi   +4 more
wiley   +1 more source

Generation of CCR4/CD7 Bispecific CAR‐T Cells Resistant to Fratricide and Exhaustion

open access: yesAdvanced Science, EarlyView.
The applications of CAR T‐cell therapy in T‐cell malignancies face limitations such as fratricide, effector‐cell exhaustion, and antigen‐escape. Herein, we developed fratricide‐ and exhaustion‐resistant CAR‐T cells that targeted CCR4 and CD7 simultaneously, with optional EGFRt safety switch. Additionally, scRNA‐seq unveiled new molecular targets, which
Sile Li   +10 more
wiley   +1 more source

Atomic Defects in Layered Transition Metal Dichalcogenides for Sustainable Energy Storage and the Intelligent Trends in Data Analytics

open access: yesAdvanced Science, EarlyView.
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo   +6 more
wiley   +1 more source

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

open access: yesAdvanced 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   +4 more
wiley   +1 more source

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