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Article Tier 2 Detection Methods Environmental Sources Food & Water Human Health Effects Nanoplastics Remediation Sign in to save

Negotiation teams in multiagent systems

PubMed Central 2011 2 citations

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Despite the title suggesting a multi-agent systems paper, the abstract describes improvements to flow cytometry methods for detecting and quantifying microplastics and nanoplastics stained with the fluorescent dye Nile red. The optimized protocol improved detection accuracy and may help make microplastic monitoring more reliable and reproducible.

In recent years, the utilization of flow cytometry for quantitative microplastic analysis has gained prominence. However, the current methods have some drawbacks that need to be improved. The present study aims to enhance the flow cytometry detection protocols for Nile red (NR) stained microplastics, facilitating distinct microplastic and nanoplastic enumeration. By elevating dimethyl sulfoxide (DMSO) concentration to 20%–30% within the solution, NR solubility improved and agglomeration reduced. The analysis of 26 replicates of polystyrene (PS) liquid samples through four distinct dot plots highlighted the superior accuracy of dot plots integrating yellow fluorescence. Through systematic staining of varying NR concentrations across three microplastic liquid samples (polyethylene terephthalate, polyethylene, and polypropylene), the optimal staining concentration was determined to be 15–20 μg/mL. The distributions of agglomerated NR and NR stained PS under two scenarios—dissolved NR and partially agglomerated NR—were compared. Results showed their distinct distributions within the side scatter versus yellow fluorescence dot plot. Counting results from gradient-diluted PS liquid samples revealed a microplastic detection lower limit of 10(4) particles/mL, with an optimal concentration range of 10(5)–10(6) particles/mL. Flow cytometric assessment of PS microspheres spanning 150 nm to 40 μm indicated a 150 nm particle size detection minimum. Our investigation validated the efficacy of NR staining and subsequent flow cytometry analysis across eleven types of microplastics. Separation and concentration of microplastics (1.0–50.0 μm) and nanoplastics (0.2–1.0 μm) were achieved via sequential sieving through 50, 1.0, and 0.2 μm filter membranes. We used a combination of multiple filtration steps and flow cytometry to analyze microplastics and nanoplastics in nine simulated water samples. Our results showed that the combined amount of microplastics (1.0–50.0 μm) and nanoplastics (0.2–1.0 μm) after filtration had a ratio of 0.80–1.19 compared to the total microplastic concentration before filtration. This result confirms the practicality of our approach. By enhancing flow cytometry-based microplastic and nanoplastic detection protocols, our study provides pivotal technical support for research concerning quantitative toxicity assessment of microplastic and nanoplastic pollution.

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Researchers optimized a Nile Red/DAPI fluorescence co-staining method for quantifying small microplastics, identifying key interference factors and exposure time parameters that significantly improve accuracy of microplastic detection.

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Scientists developed an improved method for staining microplastics with a fluorescent dye (Nile red) that embeds the dye inside the plastic particles rather than just coating the surface, resulting in much brighter and more reliable detection. Combined with high-speed flow cytometry, the technique can rapidly count microplastic particles smaller than 10 µm in environmental water samples with recovery rates above 99%. Faster and more accurate counting methods like this are important for scaling up microplastic monitoring across many water sources.

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Researchers improved a flow cytometry method for counting and separating microplastics and nanoplastics stained with a fluorescent dye called Nile Red. By adjusting the chemical solution used in detection, they reduced particle clumping and improved measurement accuracy for plastic particles across a range of sizes. The refined technique offers a faster and more reliable way to quantify plastic pollution in environmental and biological samples.

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