ReviewBiomedicines2017
Engineered Aptamers to Probe Molecular Interactions on the Cell Surface.
Review in Biomedicines, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 19 citations in OpenAlex.
- Making the Next Generation of Therapeutics: mRNA Meets Synthetic Biology.ACS synthetic biology · 2023Review
- Aptamers Targeting Membrane Proteins for Sensor and Diagnostic Applications.Molecules (Basel, Switzerland) · 2023Review
- AnBiochemistry · 2022Article
- Enhancing CAR-T Cell Therapy with Functional Nucleic Acids.ACS pharmacology & translational science · 2021Review
- Logic Gates Based on DNA Aptamers.Pharmaceuticals (Basel, Switzerland) · 2020Review
- A Homodimeric Aptamer Variant Generated from Ligand-Guided Selection Activates the T Cell Receptor Cluster of Differentiation 3 Complex.Molecular therapy. Nucleic acids · 2020Article
- Ligand Guided Selection (LIGS) of Artificial Nucleic Acid Ligands against Cell Surface Targets.ACS applied bio materials · 2020Article
- Ligand-Guided Selection with Artificially Expanded Genetic Information Systems against TCR-CD3ε.Biochemistry · 2020Article
- Integrating Ligand-Receptor Interactions and In Vitro Evolution for Streamlined Discovery of Artificial Nucleic Acid Ligands.Molecular therapy. Nucleic acids · 2019Article
- Dimerization of an aptamer generated from Ligand-guided selection (LIGS) yields a high affinity scaffold against B-cells.Biochimica et biophysica acta. General subjects · 2019Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
Significant progress has been made in understanding the nature of molecular interactions on the cell membrane. To decipher such interactions, molecular scaffolds can be engineered as a tool to modulate these events as they occur on the cell membrane. To guarantee reliability, scaffolds that function as modulators of cell membrane events must be coupled to a targeting moiety with superior chemical versatility. In this regard, nucleic acid aptamers are a suitable class of targeting moieties. Aptamers are inherently chemical in nature, allowing extensive site-specific chemical modification to engineer sensing molecules. Aptamers can be easily selected using a simple laboratory-based in vitro evolution method enabling the design and development of aptamer-based functional molecular scaffolds against wide range of cell surface molecules. This article reviews the application of aptamers as monitors and modulators of molecular interactions on the mammalian cell surface with the aim of increasing our understanding of cell-surface receptor response to external stimuli. The information gained from these types of studies could eventually prove useful in engineering improved medical diagnostics and therapeutics.
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.