ArticleRSC advances2022
Sensitive and specific capture of polystyrene and polypropylene microplastics using engineered peptide biosensors.
Article in RSC advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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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.
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Who cites it
14 citing papers in PubMed, 45 citations in OpenAlex.
- Bionanotechnology at microplastic and nanoplastic interfaces: detection, adsorption and degradation.Nano convergence · 2026Review
- Rethinking peptide developability with sequence-only models: interpretable screening of microplastic-binding peptides with gated query pooling.Chemical science · 2026Article
- Microplastics in human body: accumulation, natural clearance, and biomedical detoxification strategies.Biomedical engineering letters · 2025Review
- Plastic-binding peptides as anchors for protein scaffolds on synthetic plastics: opportunities and challenges.RSC advances · 2025Article
- LCI Engineering for Improved Polystyrene Binding: The Impact of Aromatic Amino Acid Substitutions.ACS omega · 2025Article
- Microfluidic assessment of adhesion by surface display (MAPS-D): a novel method for evaluating peptide adhesion to polystyrene and poly(methyl methacrylate).RSC advances · 2025Article
- Label-Free Identification and Imaging of Microplastic and Nanoplastic Biouptake Using Optical Photothermal Infrared Microspectroscopy.Environmental science & technology · 2025Article
- Exploring Innovative Approaches for the Analysis of Micro- and Nanoplastics: Breakthroughs in (Bio)Sensing Techniques.Biosensors · 2025Review
- Integrating biophysical modeling, quantum computing, and AI to discover plastic-binding peptides that combat microplastic pollution.PNAS nexus · 2025Article
- Review
- Plastic Analysis with a Plasmonic Nano-Gold Sensor Coated with Plastic-Binding Peptides.Journal of xenobiotics · 2024Article
- Peptide-Decorated Microneedles for the Detection of Microplastics.Biosensors · 2024Article
- Magnetic Nanoparticle-Based Semi-automated Panning for High-Throughput Antibody Selection.Methods in molecular biology (Clifton, N.J.) · 2023Article
- A Novel Impedimetric Sensor Based on Cyanobacterial Extracellular Polymeric Substances for Microplastics Detection.Journal of polymers and the environment · 2022Article
Corrections and comments
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Authors and funding
11 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Owing to increased environmental pollution, active research regarding microplastics circulating in the ocean has attracted significant interest in recent times. Microplastics accumulate in the bodies of living organisms and adversely affect them. In this study, a new method for the rapid detection of microplastics using peptides was proposed. Among the various types of plastics distributed in the ocean, polystyrene and polypropylene were selected. The binding affinity of the hydrophobic peptides suitable for each type of plastic was evaluated. The binding affinities of peptides were confirmed in unoxidized plastics and plasma-oxidized plastics in deionised or 3.5% saline water. Also, the detection of microplastics in small animals' intestine extracts were possible with the reported peptide biosensors. We expect plastic-binding peptides to be used in sensors to increase the detection efficiency of microplastics and potentially help separate microplastics from seawater.
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.