ReviewMolecular & cellular toxicology2023
Physical and biomimetic treatment methods to reduce microplastic waste accumulation.
Review in Molecular & cellular toxicology, 2023. 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.
- Micro- and Nanoplastics in the Environment: Analytical Approaches, Environmental Fate, Life Cycle, and Remediation Strategies-A Scoping Review.Molecules (Basel, Switzerland) · 2026Review
- Micro- and Nano-Plastic-Induced Adverse Health Effects on Lungs and Kidneys Linked to Oxidative Stress and Inflammation.Life (Basel, Switzerland) · 2025Review
- Assessing Recent Technologies for Addressing Microplastic Pollution and Pushing the Case of Bioremediation as an Attractive Approach.Recent advances in food, nutrition & agriculture · 2025Review
- An Emerging Role of Micro- and Nanoplastics in Vascular Diseases.Life (Basel, Switzerland) · 2024Review
- Antimicrobial properties of hindered amine light stabilizers in polymer coating materials and their mechanism of action.Frontiers in bioengineering and biotechnology · 2024Article
- Insights into Anthropogenic Micro- and Nanoplastic Accumulation in Drinking Water Sources and Their Potential Effects on Human Health.Polymers · 2023Review
- Machine Learning to Predict the Adsorption Capacity of Microplastics.Nanomaterials (Basel, Switzerland) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Since the Covid-19 pandemic in 2019, the use of plastics has increased exponentially, so it is imperative to manage and dispose of these plastic wastes safely. Objectives: This review focuses on the management strategies governed by the policies of each country to reduce plastic waste through physical collection methods and methods that use eco-imitation technologies. Results: Thus far, physical treatment methods have been applied to sewage and drinking water treatment. The abilities of bio-inspired treatment methods are being assessed in terms of capturing microplastics (MPs) and nanoplastics (NPs), extracting substances from marine organisms, reducing toxicity, and developing alternatives to petroleum-based plastics. Conclusions: Various post-treatment methods have been proposed to collect and remove MPs and NPs that have reached into aquatic ecosystems and subsequently reduce their toxicity. However, there are limitations that the effectiveness of these methods is hindered by the lack of policies governing the entire process of plastic use before the post-treatment. Purpose of Review: We purpose to reduce plastic waste through methods that use eco-imitation technologies. Recent Findings: These eco-imitation methods are attracting attention as viable future plastic waste treatment options in line with the goals of sustainable development.
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.