Chimeric antigen receptors (CARs) consist of an antigen-binding region fused to intracellular signaling domains, enabling customized T cell responses against targets. Despite their major role in T cell activation, effector function and persistence, only a small set of immune signaling domains have been explored. Here we present speedingCARs, an integrated method for engineering CAR T cells via signaling domain shuffling and pooled functional screening. Leveraging the inherent modularity of natural signaling domains, we generate a library of 180 unique CAR variants genomically integrated into primary human T cells by CRISPR-Cas9. In vitro tumor cell co-culture, followed by single-cell RNA sequencing (scRNA-seq) and single-cell CAR sequencing (scCAR-seq), enables high-throughput screening for identifying several variants with tumor killing properties and T cell phenotypes markedly different from standard CARs. Mapping of the CAR scRNA-seq data onto that of tumor infiltrating lymphocytes further helps guide the selection of variants. These results thus help expand the CAR signaling domain combination space, and supports speedingCARs as a tool for the engineering of CARs for potential therapeutic development.
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http://dx.doi.org/10.1038/s41467-022-34141-8 | DOI Listing |
J Exp Bot
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Ministry of Education Key Laboratory of Molecular and Cellular Biology; Hebei Research Center of the Basic Discipline of Cell Biology; Hebei Collaboration Innovation Center for Cell Signaling and Environmental Adaptation; Hebei Key Laboratory of Molecular and Cellular Biology; College of Life Sciences, Hebei Normal University, 050024 Shijiazhuang, China.
A well-constructed pollen wall is essential for pollen fertility, which relies on the contribution of tapetum. Our results demonstrate an essential role of the tapetum-expressed protein phosphatase 2A (PP2A) B'α and B'β in pollen wall formation. The b'aβ double mutant pollen grains harbored sticky remnants and tectum breakages, resulting in failed release.
View Article and Find Full Text PDFJ Clin Med
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Pető András Faculty, Semmelweis University, 1125 Budapest, Hungary.
Cerebral palsy (CP) manifests with abnormal posture and impaired selective motor control, notably affecting trunk control and dynamic balance coordination, leading to inadequate postural control. Previous research has indicated the benefits of pulsed electromagnetic field (PEMF) therapy for various musculoskeletal and neurological conditions. Therefore, we conducted a randomized pilot study to assess the feasibility of our preliminary research design and examine the effect of the PEMF treatment among children with CP.
View Article and Find Full Text PDFSensors (Basel)
January 2025
State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China.
Satellite-ground communication is a critical component in the global communication system, significantly contributing to environmental monitoring, radio and television broadcasting, aerospace operations, and other domains. However, the technology encounters challenges in data transmission efficiency, due to the drastic alterations in the communication channel caused by the rapid movement of satellites. In comparison to traditional transmission methods, semantic communication (SemCom) technology enhances transmission efficiency by comprehending and leveraging the intrinsic meaning of information, making it ideal for image transmission in satellite communications.
View Article and Find Full Text PDFSensors (Basel)
January 2025
School of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China.
Breast cancer (BC) is one of the most lethal cancers worldwide, and its early diagnosis is critical for improving patient survival rates. However, the extraction of key information from complex medical images and the attainment of high-precision classification present a significant challenge. In the field of signal processing, texture-rich images typically exhibit periodic patterns and structures, which are manifested as significant energy concentrations at specific frequencies in the frequency domain.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Electronics Departament, University of Alcalá (UAH), 28805 Alcalá de Henares, Madrid, Spain.
The use of Deep Learning algorithms in the domain of Decision Making for Autonomous Vehicles has garnered significant attention in the literature in recent years, showcasing considerable potential. Nevertheless, most of the solutions proposed by the scientific community encounter difficulties in real-world applications. This paper aims to provide a realistic implementation of a hybrid Decision Making module in an Autonomous Driving stack, integrating the learning capabilities from the experience of Deep Reinforcement Learning algorithms and the reliability of classical methodologies.
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