ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2020
Chemical Artificial Internalizing Receptors for Primary T Cells.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 10 citations in OpenAlex.
- Artificial Internalizing Receptors for Targeted Degradation of Extracellular Proteins.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Scaling Up Synthetic Cell Production Using Robotics and Machine Learning Toward Therapeutic Applications.Advanced biology · 2025Article
- Artificial Internalizing Receptors: Intracellular Delivery of Cargo Through Bio-Orthogonal Recognition.Advanced healthcare materials · 2024Article
- Supramolecularly engineered bacteria mediated calcium overload and immunotherapy of tumors.Theranostics · 2024Article
- Supramolecularly Engineered Conjugate of Bacteria and Cell Membrane-Coated Magnetic Nanoparticles for Enhanced Ferroptosis and Immunotherapy of Tumors.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- Synthetic Artificial Apoptosis-Inducing Receptor for On-Demand Deactivation of Engineered Cells.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2021Article
- Chemical Artificial Internalizing Receptors for Primary T Cells.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The newest generation of cell-based technologies relies heavily on methods to communicate to the engineered cells using artificial receptors, specifically to deactivate the cells administered to a patient in the event of adverse effects. Herein, artificial synthetic internalizing receptors are engineered that function in mammalian cells in 2D and in 3D and afford targeted, specific intracellular drug delivery with nanomolar potency in the most challenging cell type, namely primary, donor-derived T cells. Receptor design comprises a lipid bilayer anchor for receptor integration into cell membrane and a small xenobiotic molecule as a recognition ligand. Artificial receptors are successfully targeted by the corresponding antibody-drug conjugate (ADC) and exhibit efficient cargo cell entry with ensuing intracellular effects. Receptor integration into cells is fast and robust and affords targeted cell entry in under 2 h. Through a combination of the receptor design and the use of ADC, combined benefits previously made available by chimeric artificial receptors (performance in T cells) and the chemical counterpart (robustness and simplicity) in a single functional platform is achieved. Artificial synthetic receptors are poised to facilitate the maturation of engineered cells as tools of biotechnology and biomedicine.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.