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SciPi 770: Best Practices: Detecting and Quantifying Micro- Nanoplastics (MNP) in Biological Tissues
How do you build confidence that what is being measured is plastic compared to macromolecules or other confounding materials in the sample, and do sample preparation methods for tissues potentially skew the ability to make this distinction?
Results
(9 Answers)
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Expert 3
Spectrsocopic analyses allow to confirm the polymer's identity, despite the potential for organic matter contamination. Thermal analyses also allow for this, as the generated compounds are unique and not usually generated by other macromolecules (e.g., styrene).
This may be skewed when digestion is insufficient or overly aggressive, and some care is required when considering the matrix under analysis (for example, fat-rich tissues may generate some residues that can overlap with ions form plastics (important in methods such as py-GC/MS). -
Expert 9
The employed method must demonstrate its accuracy and reproducibility - e.g. via replicate analysis of one or more of standard/certified reference materials, appropriate matrix spikes, and/or successful participation in an interlaboatory comparison. -
Expert 4
There are several options, dependent on the combination of matrix, plastics, and sample preparation (digestion) method. Sample preparation methods are important to minimize background interference whilst combining validated methods will allow to integrate the results of various basically different methods.
Another issue to add is the need to verify that different mass tracers are present for the polymers of interest, as this increases the confidence in the assessment of the nature of the plastics identified. -
Expert 2
Confirming that a measured particle is truly plastic and not a macromolecule with similar properties, a natural fiber, or some degraded organic material needs a complex analysis that involves both sample preparation and analytical techniques. Spectroscopy analysis using FTIR, Raman, or PyGCMS is usually the best and the easiest way to determine if what is being measured is plastic compared to macromolecules or other confounding materials in the sample. In some cases, the use of techniques such as conformal prediction or cross-validation classifiers could offer a probability score indicating the likelihood that a particle is plastic, rather than relying solely on a binary identification. Also, matrix-matched blanks and data of known polymers should be used to assess the accuracy of the used method. The sample preparation method can significantly affect the accuracy of polymer identification in microplastic analysis. Strong acids, oxidizing agents, or high heat, used for the sample digestion can degrade some sensitive polymers like PVC, PET, PA, PU, and also certain polyacrylates which can interfere with their identification. Furthermore, a wrong choice of digestion method can also lead to residual proteins, lipids, or natural fibers that will interfere with the spectral analysis or that could disrupt the microscopic investigations by mimicking plastics in shape and appearance under microscopy. The obtained residues could also produce pyrolysis products that could overlap with the polymer signals in Py-GCMS, thus making it harder to identify the correct samples. Additionally, some reagents and laboratory consumables, like gloves, filters, or even detergents, can introduce plastic particles and could produce contamination that may be mistaken as being from the investigated samples. -
Expert 1
For human specimens, complementary methods to confirm the findings would yield confidence in data quality. Mass spec (pyrolysis GCMS) methods, proper sample prep methods (to remove all interferences) and interlab comparisons will help build confidence in data quality. -
Expert 5
Use a sample analysis regime that includes artificial samples (matrix free) constructed from the expected macromolecules and confounding materials. Using such "samples" will help one understand the possible interferences and how to deal with them through the procedure . -
Expert 8
QAQC and multiple methods build confidence. Yes, sample preparation is critical to reduce matrix interference and amplify the plastic signal. -
Expert 6
One challenging around the plastic confirmation is sample availability rather than sample preparation method. If there will be enough material available, additional analytical methods, like NMR for chemical identify, GPC for MW, and DSC for thermal properties, can help to measure the samples and differentiate plastics from macromolecules and other confounding materials. -
Expert 7
There are different ways to confirm the presence of a plastic.
1. Use marker ions on Pyr-GC/MS.
2. Compare FT-IR/Raman spectra with the spectra in library.
3. Run a polymer standard if that's available.
How sample preparation can skew identificaiton
The digestion process can degrade or change certain polymers.
The extraction process may not complete.
Filtration can miss certain sizes of polymers.
Experts generally agree that spectroscopic analysis (FTIR, Raman) and thermal analysis (Py-GCMS) are primary methods for confirming plastic identity versus other macromolecules. Multiple experts emphasize the importance of using complementary methods rather than relying on a single technique.
There is consensus that sample preparation methods can significantly impact identification accuracy. Experts note that:
- Insufficient or overly aggressive digestion can alter polymer structures (Expert 3)
- Certain polymers (PVC, PET, PA, PU, polyacrylates) are particularly vulnerable to degradation during preparation (Expert 2)
- Fat-rich tissues may generate residues that overlap with plastic signals (Expert 3)
For building confidence in measurements, experts recommend:
- Using reference materials and matrix spikes (Expert 9)
- Participating in interlaboratory comparisons (Experts 1, 9)
- Creating artificial samples with expected confounding materials (Expert 5)
- Verifying multiple mass tracers for polymers of interest (Expert 4)
- Using matrix-matched blanks and known polymer data (Expert 2)
Summary Generated by AI
Expert 6
07/28/2025 08:38Expert 5
07/31/2025 19:52